1<html><body> 2<style> 3 4body, h1, h2, h3, div, span, p, pre, a { 5 margin: 0; 6 padding: 0; 7 border: 0; 8 font-weight: inherit; 9 font-style: inherit; 10 font-size: 100%; 11 font-family: inherit; 12 vertical-align: baseline; 13} 14 15body { 16 font-size: 13px; 17 padding: 1em; 18} 19 20h1 { 21 font-size: 26px; 22 margin-bottom: 1em; 23} 24 25h2 { 26 font-size: 24px; 27 margin-bottom: 1em; 28} 29 30h3 { 31 font-size: 20px; 32 margin-bottom: 1em; 33 margin-top: 1em; 34} 35 36pre, code { 37 line-height: 1.5; 38 font-family: Monaco, 'DejaVu Sans Mono', 'Bitstream Vera Sans Mono', 'Lucida Console', monospace; 39} 40 41pre { 42 margin-top: 0.5em; 43} 44 45h1, h2, h3, p { 46 font-family: Arial, sans serif; 47} 48 49h1, h2, h3 { 50 border-bottom: solid #CCC 1px; 51} 52 53.toc_element { 54 margin-top: 0.5em; 55} 56 57.firstline { 58 margin-left: 2 em; 59} 60 61.method { 62 margin-top: 1em; 63 border: solid 1px #CCC; 64 padding: 1em; 65 background: #EEE; 66} 67 68.details { 69 font-weight: bold; 70 font-size: 14px; 71} 72 73</style> 74 75<h1><a href="dataflow_v1b3.html">Dataflow API</a> . <a href="dataflow_v1b3.projects.html">projects</a> . <a href="dataflow_v1b3.projects.jobs.html">jobs</a></h1> 76<h2>Instance Methods</h2> 77<p class="toc_element"> 78 <code><a href="dataflow_v1b3.projects.jobs.debug.html">debug()</a></code> 79</p> 80<p class="firstline">Returns the debug Resource.</p> 81 82<p class="toc_element"> 83 <code><a href="dataflow_v1b3.projects.jobs.messages.html">messages()</a></code> 84</p> 85<p class="firstline">Returns the messages Resource.</p> 86 87<p class="toc_element"> 88 <code><a href="dataflow_v1b3.projects.jobs.workItems.html">workItems()</a></code> 89</p> 90<p class="firstline">Returns the workItems Resource.</p> 91 92<p class="toc_element"> 93 <code><a href="#aggregated">aggregated(projectId, filter=None, location=None, pageSize=None, pageToken=None, view=None, x__xgafv=None)</a></code></p> 94<p class="firstline">List the jobs of a project across all regions.</p> 95<p class="toc_element"> 96 <code><a href="#aggregated_next">aggregated_next(previous_request, previous_response)</a></code></p> 97<p class="firstline">Retrieves the next page of results.</p> 98<p class="toc_element"> 99 <code><a href="#close">close()</a></code></p> 100<p class="firstline">Close httplib2 connections.</p> 101<p class="toc_element"> 102 <code><a href="#create">create(projectId, body=None, location=None, replaceJobId=None, view=None, x__xgafv=None)</a></code></p> 103<p class="firstline">Creates a Cloud Dataflow job. To create a job, we recommend using `projects.locations.jobs.create` with a [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints). Using `projects.jobs.create` is not recommended, as your job will always start in `us-central1`.</p> 104<p class="toc_element"> 105 <code><a href="#get">get(projectId, jobId, location=None, view=None, x__xgafv=None)</a></code></p> 106<p class="firstline">Gets the state of the specified Cloud Dataflow job. To get the state of a job, we recommend using `projects.locations.jobs.get` with a [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints). Using `projects.jobs.get` is not recommended, as you can only get the state of jobs that are running in `us-central1`.</p> 107<p class="toc_element"> 108 <code><a href="#getMetrics">getMetrics(projectId, jobId, location=None, startTime=None, x__xgafv=None)</a></code></p> 109<p class="firstline">Request the job status. To request the status of a job, we recommend using `projects.locations.jobs.getMetrics` with a [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints). Using `projects.jobs.getMetrics` is not recommended, as you can only request the status of jobs that are running in `us-central1`.</p> 110<p class="toc_element"> 111 <code><a href="#list">list(projectId, filter=None, location=None, pageSize=None, pageToken=None, view=None, x__xgafv=None)</a></code></p> 112<p class="firstline">List the jobs of a project. To list the jobs of a project in a region, we recommend using `projects.locations.jobs.list` with a [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints). To list the all jobs across all regions, use `projects.jobs.aggregated`. Using `projects.jobs.list` is not recommended, as you can only get the list of jobs that are running in `us-central1`.</p> 113<p class="toc_element"> 114 <code><a href="#list_next">list_next(previous_request, previous_response)</a></code></p> 115<p class="firstline">Retrieves the next page of results.</p> 116<p class="toc_element"> 117 <code><a href="#snapshot">snapshot(projectId, jobId, body=None, x__xgafv=None)</a></code></p> 118<p class="firstline">Snapshot the state of a streaming job.</p> 119<p class="toc_element"> 120 <code><a href="#update">update(projectId, jobId, body=None, location=None, x__xgafv=None)</a></code></p> 121<p class="firstline">Updates the state of an existing Cloud Dataflow job. To update the state of an existing job, we recommend using `projects.locations.jobs.update` with a [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints). Using `projects.jobs.update` is not recommended, as you can only update the state of jobs that are running in `us-central1`.</p> 122<h3>Method Details</h3> 123<div class="method"> 124 <code class="details" id="aggregated">aggregated(projectId, filter=None, location=None, pageSize=None, pageToken=None, view=None, x__xgafv=None)</code> 125 <pre>List the jobs of a project across all regions. 126 127Args: 128 projectId: string, The project which owns the jobs. (required) 129 filter: string, The kind of filter to use. 130 Allowed values 131 UNKNOWN - The filter isn't specified, or is unknown. This returns all jobs ordered on descending `JobUuid`. 132 ALL - Returns all running jobs first ordered on creation timestamp, then returns all terminated jobs ordered on the termination timestamp. 133 TERMINATED - Filters the jobs that have a terminated state, ordered on the termination timestamp. Example terminated states: `JOB_STATE_STOPPED`, `JOB_STATE_UPDATED`, `JOB_STATE_DRAINED`, etc. 134 ACTIVE - Filters the jobs that are running ordered on the creation timestamp. 135 location: string, The [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints) that contains this job. 136 pageSize: integer, If there are many jobs, limit response to at most this many. The actual number of jobs returned will be the lesser of max_responses and an unspecified server-defined limit. 137 pageToken: string, Set this to the 'next_page_token' field of a previous response to request additional results in a long list. 138 view: string, Deprecated. ListJobs always returns summaries now. Use GetJob for other JobViews. 139 Allowed values 140 JOB_VIEW_UNKNOWN - The job view to return isn't specified, or is unknown. Responses will contain at least the `JOB_VIEW_SUMMARY` information, and may contain additional information. 141 JOB_VIEW_SUMMARY - Request summary information only: Project ID, Job ID, job name, job type, job status, start/end time, and Cloud SDK version details. 142 JOB_VIEW_ALL - Request all information available for this job. 143 JOB_VIEW_DESCRIPTION - Request summary info and limited job description data for steps, labels and environment. 144 x__xgafv: string, V1 error format. 145 Allowed values 146 1 - v1 error format 147 2 - v2 error format 148 149Returns: 150 An object of the form: 151 152 { # Response to a request to list Cloud Dataflow jobs in a project. This might be a partial response, depending on the page size in the ListJobsRequest. However, if the project does not have any jobs, an instance of ListJobsResponse is not returned and the requests's response body is empty {}. 153 "failedLocation": [ # Zero or more messages describing the [regional endpoints] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints) that failed to respond. 154 { # Indicates which [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints) failed to respond to a request for data. 155 "name": "A String", # The name of the [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints) that failed to respond. 156 }, 157 ], 158 "jobs": [ # A subset of the requested job information. 159 { # Defines a job to be run by the Cloud Dataflow service. nextID: 26 160 "clientRequestId": "A String", # The client's unique identifier of the job, re-used across retried attempts. If this field is set, the service will ensure its uniqueness. The request to create a job will fail if the service has knowledge of a previously submitted job with the same client's ID and job name. The caller may use this field to ensure idempotence of job creation across retried attempts to create a job. By default, the field is empty and, in that case, the service ignores it. 161 "createTime": "A String", # The timestamp when the job was initially created. Immutable and set by the Cloud Dataflow service. 162 "createdFromSnapshotId": "A String", # If this is specified, the job's initial state is populated from the given snapshot. 163 "currentState": "A String", # The current state of the job. Jobs are created in the `JOB_STATE_STOPPED` state unless otherwise specified. A job in the `JOB_STATE_RUNNING` state may asynchronously enter a terminal state. After a job has reached a terminal state, no further state updates may be made. This field may be mutated by the Cloud Dataflow service; callers cannot mutate it. 164 "currentStateTime": "A String", # The timestamp associated with the current state. 165 "environment": { # Describes the environment in which a Dataflow Job runs. # The environment for the job. 166 "clusterManagerApiService": "A String", # The type of cluster manager API to use. If unknown or unspecified, the service will attempt to choose a reasonable default. This should be in the form of the API service name, e.g. "compute.googleapis.com". 167 "dataset": "A String", # The dataset for the current project where various workflow related tables are stored. The supported resource type is: Google BigQuery: bigquery.googleapis.com/{dataset} 168 "debugOptions": { # Describes any options that have an effect on the debugging of pipelines. # Any debugging options to be supplied to the job. 169 "enableHotKeyLogging": True or False, # When true, enables the logging of the literal hot key to the user's Cloud Logging. 170 }, 171 "experiments": [ # The list of experiments to enable. This field should be used for SDK related experiments and not for service related experiments. The proper field for service related experiments is service_options. 172 "A String", 173 ], 174 "flexResourceSchedulingGoal": "A String", # Which Flexible Resource Scheduling mode to run in. 175 "internalExperiments": { # Experimental settings. 176 "a_key": "", # Properties of the object. Contains field @type with type URL. 177 }, 178 "sdkPipelineOptions": { # The Cloud Dataflow SDK pipeline options specified by the user. These options are passed through the service and are used to recreate the SDK pipeline options on the worker in a language agnostic and platform independent way. 179 "a_key": "", # Properties of the object. 180 }, 181 "serviceAccountEmail": "A String", # Identity to run virtual machines as. Defaults to the default account. 182 "serviceKmsKeyName": "A String", # If set, contains the Cloud KMS key identifier used to encrypt data at rest, AKA a Customer Managed Encryption Key (CMEK). Format: projects/PROJECT_ID/locations/LOCATION/keyRings/KEY_RING/cryptoKeys/KEY 183 "serviceOptions": [ # The list of service options to enable. This field should be used for service related experiments only. These experiments, when graduating to GA, should be replaced by dedicated fields or become default (i.e. always on). 184 "A String", 185 ], 186 "shuffleMode": "A String", # Output only. The shuffle mode used for the job. 187 "tempStoragePrefix": "A String", # The prefix of the resources the system should use for temporary storage. The system will append the suffix "/temp-{JOBNAME} to this resource prefix, where {JOBNAME} is the value of the job_name field. The resulting bucket and object prefix is used as the prefix of the resources used to store temporary data needed during the job execution. NOTE: This will override the value in taskrunner_settings. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object} 188 "userAgent": { # A description of the process that generated the request. 189 "a_key": "", # Properties of the object. 190 }, 191 "version": { # A structure describing which components and their versions of the service are required in order to run the job. 192 "a_key": "", # Properties of the object. 193 }, 194 "workerPools": [ # The worker pools. At least one "harness" worker pool must be specified in order for the job to have workers. 195 { # Describes one particular pool of Cloud Dataflow workers to be instantiated by the Cloud Dataflow service in order to perform the computations required by a job. Note that a workflow job may use multiple pools, in order to match the various computational requirements of the various stages of the job. 196 "autoscalingSettings": { # Settings for WorkerPool autoscaling. # Settings for autoscaling of this WorkerPool. 197 "algorithm": "A String", # The algorithm to use for autoscaling. 198 "maxNumWorkers": 42, # The maximum number of workers to cap scaling at. 199 }, 200 "dataDisks": [ # Data disks that are used by a VM in this workflow. 201 { # Describes the data disk used by a workflow job. 202 "diskType": "A String", # Disk storage type, as defined by Google Compute Engine. This must be a disk type appropriate to the project and zone in which the workers will run. If unknown or unspecified, the service will attempt to choose a reasonable default. For example, the standard persistent disk type is a resource name typically ending in "pd-standard". If SSD persistent disks are available, the resource name typically ends with "pd-ssd". The actual valid values are defined the Google Compute Engine API, not by the Cloud Dataflow API; consult the Google Compute Engine documentation for more information about determining the set of available disk types for a particular project and zone. Google Compute Engine Disk types are local to a particular project in a particular zone, and so the resource name will typically look something like this: compute.googleapis.com/projects/project-id/zones/zone/diskTypes/pd-standard 203 "mountPoint": "A String", # Directory in a VM where disk is mounted. 204 "sizeGb": 42, # Size of disk in GB. If zero or unspecified, the service will attempt to choose a reasonable default. 205 }, 206 ], 207 "defaultPackageSet": "A String", # The default package set to install. This allows the service to select a default set of packages which are useful to worker harnesses written in a particular language. 208 "diskSizeGb": 42, # Size of root disk for VMs, in GB. If zero or unspecified, the service will attempt to choose a reasonable default. 209 "diskSourceImage": "A String", # Fully qualified source image for disks. 210 "diskType": "A String", # Type of root disk for VMs. If empty or unspecified, the service will attempt to choose a reasonable default. 211 "ipConfiguration": "A String", # Configuration for VM IPs. 212 "kind": "A String", # The kind of the worker pool; currently only `harness` and `shuffle` are supported. 213 "machineType": "A String", # Machine type (e.g. "n1-standard-1"). If empty or unspecified, the service will attempt to choose a reasonable default. 214 "metadata": { # Metadata to set on the Google Compute Engine VMs. 215 "a_key": "A String", 216 }, 217 "network": "A String", # Network to which VMs will be assigned. If empty or unspecified, the service will use the network "default". 218 "numThreadsPerWorker": 42, # The number of threads per worker harness. If empty or unspecified, the service will choose a number of threads (according to the number of cores on the selected machine type for batch, or 1 by convention for streaming). 219 "numWorkers": 42, # Number of Google Compute Engine workers in this pool needed to execute the job. If zero or unspecified, the service will attempt to choose a reasonable default. 220 "onHostMaintenance": "A String", # The action to take on host maintenance, as defined by the Google Compute Engine API. 221 "packages": [ # Packages to be installed on workers. 222 { # The packages that must be installed in order for a worker to run the steps of the Cloud Dataflow job that will be assigned to its worker pool. This is the mechanism by which the Cloud Dataflow SDK causes code to be loaded onto the workers. For example, the Cloud Dataflow Java SDK might use this to install jars containing the user's code and all of the various dependencies (libraries, data files, etc.) required in order for that code to run. 223 "location": "A String", # The resource to read the package from. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket} bucket.storage.googleapis.com/ 224 "name": "A String", # The name of the package. 225 }, 226 ], 227 "poolArgs": { # Extra arguments for this worker pool. 228 "a_key": "", # Properties of the object. Contains field @type with type URL. 229 }, 230 "sdkHarnessContainerImages": [ # Set of SDK harness containers needed to execute this pipeline. This will only be set in the Fn API path. For non-cross-language pipelines this should have only one entry. Cross-language pipelines will have two or more entries. 231 { # Defines a SDK harness container for executing Dataflow pipelines. 232 "containerImage": "A String", # A docker container image that resides in Google Container Registry. 233 "environmentId": "A String", # Environment ID for the Beam runner API proto Environment that corresponds to the current SDK Harness. 234 "useSingleCorePerContainer": True or False, # If true, recommends the Dataflow service to use only one core per SDK container instance with this image. If false (or unset) recommends using more than one core per SDK container instance with this image for efficiency. Note that Dataflow service may choose to override this property if needed. 235 }, 236 ], 237 "subnetwork": "A String", # Subnetwork to which VMs will be assigned, if desired. Expected to be of the form "regions/REGION/subnetworks/SUBNETWORK". 238 "taskrunnerSettings": { # Taskrunner configuration settings. # Settings passed through to Google Compute Engine workers when using the standard Dataflow task runner. Users should ignore this field. 239 "alsologtostderr": True or False, # Whether to also send taskrunner log info to stderr. 240 "baseTaskDir": "A String", # The location on the worker for task-specific subdirectories. 241 "baseUrl": "A String", # The base URL for the taskrunner to use when accessing Google Cloud APIs. When workers access Google Cloud APIs, they logically do so via relative URLs. If this field is specified, it supplies the base URL to use for resolving these relative URLs. The normative algorithm used is defined by RFC 1808, "Relative Uniform Resource Locators". If not specified, the default value is "http://www.googleapis.com/" 242 "commandlinesFileName": "A String", # The file to store preprocessing commands in. 243 "continueOnException": True or False, # Whether to continue taskrunner if an exception is hit. 244 "dataflowApiVersion": "A String", # The API version of endpoint, e.g. "v1b3" 245 "harnessCommand": "A String", # The command to launch the worker harness. 246 "languageHint": "A String", # The suggested backend language. 247 "logDir": "A String", # The directory on the VM to store logs. 248 "logToSerialconsole": True or False, # Whether to send taskrunner log info to Google Compute Engine VM serial console. 249 "logUploadLocation": "A String", # Indicates where to put logs. If this is not specified, the logs will not be uploaded. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object} 250 "oauthScopes": [ # The OAuth2 scopes to be requested by the taskrunner in order to access the Cloud Dataflow API. 251 "A String", 252 ], 253 "parallelWorkerSettings": { # Provides data to pass through to the worker harness. # The settings to pass to the parallel worker harness. 254 "baseUrl": "A String", # The base URL for accessing Google Cloud APIs. When workers access Google Cloud APIs, they logically do so via relative URLs. If this field is specified, it supplies the base URL to use for resolving these relative URLs. The normative algorithm used is defined by RFC 1808, "Relative Uniform Resource Locators". If not specified, the default value is "http://www.googleapis.com/" 255 "reportingEnabled": True or False, # Whether to send work progress updates to the service. 256 "servicePath": "A String", # The Cloud Dataflow service path relative to the root URL, for example, "dataflow/v1b3/projects". 257 "shuffleServicePath": "A String", # The Shuffle service path relative to the root URL, for example, "shuffle/v1beta1". 258 "tempStoragePrefix": "A String", # The prefix of the resources the system should use for temporary storage. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object} 259 "workerId": "A String", # The ID of the worker running this pipeline. 260 }, 261 "streamingWorkerMainClass": "A String", # The streaming worker main class name. 262 "taskGroup": "A String", # The UNIX group ID on the worker VM to use for tasks launched by taskrunner; e.g. "wheel". 263 "taskUser": "A String", # The UNIX user ID on the worker VM to use for tasks launched by taskrunner; e.g. "root". 264 "tempStoragePrefix": "A String", # The prefix of the resources the taskrunner should use for temporary storage. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object} 265 "vmId": "A String", # The ID string of the VM. 266 "workflowFileName": "A String", # The file to store the workflow in. 267 }, 268 "teardownPolicy": "A String", # Sets the policy for determining when to turndown worker pool. Allowed values are: `TEARDOWN_ALWAYS`, `TEARDOWN_ON_SUCCESS`, and `TEARDOWN_NEVER`. `TEARDOWN_ALWAYS` means workers are always torn down regardless of whether the job succeeds. `TEARDOWN_ON_SUCCESS` means workers are torn down if the job succeeds. `TEARDOWN_NEVER` means the workers are never torn down. If the workers are not torn down by the service, they will continue to run and use Google Compute Engine VM resources in the user's project until they are explicitly terminated by the user. Because of this, Google recommends using the `TEARDOWN_ALWAYS` policy except for small, manually supervised test jobs. If unknown or unspecified, the service will attempt to choose a reasonable default. 269 "workerHarnessContainerImage": "A String", # Required. Docker container image that executes the Cloud Dataflow worker harness, residing in Google Container Registry. Deprecated for the Fn API path. Use sdk_harness_container_images instead. 270 "zone": "A String", # Zone to run the worker pools in. If empty or unspecified, the service will attempt to choose a reasonable default. 271 }, 272 ], 273 "workerRegion": "A String", # The Compute Engine region (https://cloud.google.com/compute/docs/regions-zones/regions-zones) in which worker processing should occur, e.g. "us-west1". Mutually exclusive with worker_zone. If neither worker_region nor worker_zone is specified, default to the control plane's region. 274 "workerZone": "A String", # The Compute Engine zone (https://cloud.google.com/compute/docs/regions-zones/regions-zones) in which worker processing should occur, e.g. "us-west1-a". Mutually exclusive with worker_region. If neither worker_region nor worker_zone is specified, a zone in the control plane's region is chosen based on available capacity. 275 }, 276 "executionInfo": { # Additional information about how a Cloud Dataflow job will be executed that isn't contained in the submitted job. # Deprecated. 277 "stages": { # A mapping from each stage to the information about that stage. 278 "a_key": { # Contains information about how a particular google.dataflow.v1beta3.Step will be executed. 279 "stepName": [ # The steps associated with the execution stage. Note that stages may have several steps, and that a given step might be run by more than one stage. 280 "A String", 281 ], 282 }, 283 }, 284 }, 285 "id": "A String", # The unique ID of this job. This field is set by the Cloud Dataflow service when the Job is created, and is immutable for the life of the job. 286 "jobMetadata": { # Metadata available primarily for filtering jobs. Will be included in the ListJob response and Job SUMMARY view. # This field is populated by the Dataflow service to support filtering jobs by the metadata values provided here. Populated for ListJobs and all GetJob views SUMMARY and higher. 287 "bigTableDetails": [ # Identification of a Cloud Bigtable source used in the Dataflow job. 288 { # Metadata for a Cloud Bigtable connector used by the job. 289 "instanceId": "A String", # InstanceId accessed in the connection. 290 "projectId": "A String", # ProjectId accessed in the connection. 291 "tableId": "A String", # TableId accessed in the connection. 292 }, 293 ], 294 "bigqueryDetails": [ # Identification of a BigQuery source used in the Dataflow job. 295 { # Metadata for a BigQuery connector used by the job. 296 "dataset": "A String", # Dataset accessed in the connection. 297 "projectId": "A String", # Project accessed in the connection. 298 "query": "A String", # Query used to access data in the connection. 299 "table": "A String", # Table accessed in the connection. 300 }, 301 ], 302 "datastoreDetails": [ # Identification of a Datastore source used in the Dataflow job. 303 { # Metadata for a Datastore connector used by the job. 304 "namespace": "A String", # Namespace used in the connection. 305 "projectId": "A String", # ProjectId accessed in the connection. 306 }, 307 ], 308 "fileDetails": [ # Identification of a File source used in the Dataflow job. 309 { # Metadata for a File connector used by the job. 310 "filePattern": "A String", # File Pattern used to access files by the connector. 311 }, 312 ], 313 "pubsubDetails": [ # Identification of a Pub/Sub source used in the Dataflow job. 314 { # Metadata for a Pub/Sub connector used by the job. 315 "subscription": "A String", # Subscription used in the connection. 316 "topic": "A String", # Topic accessed in the connection. 317 }, 318 ], 319 "sdkVersion": { # The version of the SDK used to run the job. # The SDK version used to run the job. 320 "sdkSupportStatus": "A String", # The support status for this SDK version. 321 "version": "A String", # The version of the SDK used to run the job. 322 "versionDisplayName": "A String", # A readable string describing the version of the SDK. 323 }, 324 "spannerDetails": [ # Identification of a Spanner source used in the Dataflow job. 325 { # Metadata for a Spanner connector used by the job. 326 "databaseId": "A String", # DatabaseId accessed in the connection. 327 "instanceId": "A String", # InstanceId accessed in the connection. 328 "projectId": "A String", # ProjectId accessed in the connection. 329 }, 330 ], 331 }, 332 "labels": { # User-defined labels for this job. The labels map can contain no more than 64 entries. Entries of the labels map are UTF8 strings that comply with the following restrictions: * Keys must conform to regexp: \p{Ll}\p{Lo}{0,62} * Values must conform to regexp: [\p{Ll}\p{Lo}\p{N}_-]{0,63} * Both keys and values are additionally constrained to be <= 128 bytes in size. 333 "a_key": "A String", 334 }, 335 "location": "A String", # The [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints) that contains this job. 336 "name": "A String", # The user-specified Cloud Dataflow job name. Only one Job with a given name may exist in a project at any given time. If a caller attempts to create a Job with the same name as an already-existing Job, the attempt returns the existing Job. The name must match the regular expression `[a-z]([-a-z0-9]{0,38}[a-z0-9])?` 337 "pipelineDescription": { # A descriptive representation of submitted pipeline as well as the executed form. This data is provided by the Dataflow service for ease of visualizing the pipeline and interpreting Dataflow provided metrics. # Preliminary field: The format of this data may change at any time. A description of the user pipeline and stages through which it is executed. Created by Cloud Dataflow service. Only retrieved with JOB_VIEW_DESCRIPTION or JOB_VIEW_ALL. 338 "displayData": [ # Pipeline level display data. 339 { # Data provided with a pipeline or transform to provide descriptive info. 340 "boolValue": True or False, # Contains value if the data is of a boolean type. 341 "durationValue": "A String", # Contains value if the data is of duration type. 342 "floatValue": 3.14, # Contains value if the data is of float type. 343 "int64Value": "A String", # Contains value if the data is of int64 type. 344 "javaClassValue": "A String", # Contains value if the data is of java class type. 345 "key": "A String", # The key identifying the display data. This is intended to be used as a label for the display data when viewed in a dax monitoring system. 346 "label": "A String", # An optional label to display in a dax UI for the element. 347 "namespace": "A String", # The namespace for the key. This is usually a class name or programming language namespace (i.e. python module) which defines the display data. This allows a dax monitoring system to specially handle the data and perform custom rendering. 348 "shortStrValue": "A String", # A possible additional shorter value to display. For example a java_class_name_value of com.mypackage.MyDoFn will be stored with MyDoFn as the short_str_value and com.mypackage.MyDoFn as the java_class_name value. short_str_value can be displayed and java_class_name_value will be displayed as a tooltip. 349 "strValue": "A String", # Contains value if the data is of string type. 350 "timestampValue": "A String", # Contains value if the data is of timestamp type. 351 "url": "A String", # An optional full URL. 352 }, 353 ], 354 "executionPipelineStage": [ # Description of each stage of execution of the pipeline. 355 { # Description of the composing transforms, names/ids, and input/outputs of a stage of execution. Some composing transforms and sources may have been generated by the Dataflow service during execution planning. 356 "componentSource": [ # Collections produced and consumed by component transforms of this stage. 357 { # Description of an interstitial value between transforms in an execution stage. 358 "name": "A String", # Dataflow service generated name for this source. 359 "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated. 360 "userName": "A String", # Human-readable name for this transform; may be user or system generated. 361 }, 362 ], 363 "componentTransform": [ # Transforms that comprise this execution stage. 364 { # Description of a transform executed as part of an execution stage. 365 "name": "A String", # Dataflow service generated name for this source. 366 "originalTransform": "A String", # User name for the original user transform with which this transform is most closely associated. 367 "userName": "A String", # Human-readable name for this transform; may be user or system generated. 368 }, 369 ], 370 "id": "A String", # Dataflow service generated id for this stage. 371 "inputSource": [ # Input sources for this stage. 372 { # Description of an input or output of an execution stage. 373 "name": "A String", # Dataflow service generated name for this source. 374 "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated. 375 "sizeBytes": "A String", # Size of the source, if measurable. 376 "userName": "A String", # Human-readable name for this source; may be user or system generated. 377 }, 378 ], 379 "kind": "A String", # Type of transform this stage is executing. 380 "name": "A String", # Dataflow service generated name for this stage. 381 "outputSource": [ # Output sources for this stage. 382 { # Description of an input or output of an execution stage. 383 "name": "A String", # Dataflow service generated name for this source. 384 "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated. 385 "sizeBytes": "A String", # Size of the source, if measurable. 386 "userName": "A String", # Human-readable name for this source; may be user or system generated. 387 }, 388 ], 389 "prerequisiteStage": [ # Other stages that must complete before this stage can run. 390 "A String", 391 ], 392 }, 393 ], 394 "originalPipelineTransform": [ # Description of each transform in the pipeline and collections between them. 395 { # Description of the type, names/ids, and input/outputs for a transform. 396 "displayData": [ # Transform-specific display data. 397 { # Data provided with a pipeline or transform to provide descriptive info. 398 "boolValue": True or False, # Contains value if the data is of a boolean type. 399 "durationValue": "A String", # Contains value if the data is of duration type. 400 "floatValue": 3.14, # Contains value if the data is of float type. 401 "int64Value": "A String", # Contains value if the data is of int64 type. 402 "javaClassValue": "A String", # Contains value if the data is of java class type. 403 "key": "A String", # The key identifying the display data. This is intended to be used as a label for the display data when viewed in a dax monitoring system. 404 "label": "A String", # An optional label to display in a dax UI for the element. 405 "namespace": "A String", # The namespace for the key. This is usually a class name or programming language namespace (i.e. python module) which defines the display data. This allows a dax monitoring system to specially handle the data and perform custom rendering. 406 "shortStrValue": "A String", # A possible additional shorter value to display. For example a java_class_name_value of com.mypackage.MyDoFn will be stored with MyDoFn as the short_str_value and com.mypackage.MyDoFn as the java_class_name value. short_str_value can be displayed and java_class_name_value will be displayed as a tooltip. 407 "strValue": "A String", # Contains value if the data is of string type. 408 "timestampValue": "A String", # Contains value if the data is of timestamp type. 409 "url": "A String", # An optional full URL. 410 }, 411 ], 412 "id": "A String", # SDK generated id of this transform instance. 413 "inputCollectionName": [ # User names for all collection inputs to this transform. 414 "A String", 415 ], 416 "kind": "A String", # Type of transform. 417 "name": "A String", # User provided name for this transform instance. 418 "outputCollectionName": [ # User names for all collection outputs to this transform. 419 "A String", 420 ], 421 }, 422 ], 423 }, 424 "projectId": "A String", # The ID of the Cloud Platform project that the job belongs to. 425 "replaceJobId": "A String", # If this job is an update of an existing job, this field is the job ID of the job it replaced. When sending a `CreateJobRequest`, you can update a job by specifying it here. The job named here is stopped, and its intermediate state is transferred to this job. 426 "replacedByJobId": "A String", # If another job is an update of this job (and thus, this job is in `JOB_STATE_UPDATED`), this field contains the ID of that job. 427 "requestedState": "A String", # The job's requested state. `UpdateJob` may be used to switch between the `JOB_STATE_STOPPED` and `JOB_STATE_RUNNING` states, by setting requested_state. `UpdateJob` may also be used to directly set a job's requested state to `JOB_STATE_CANCELLED` or `JOB_STATE_DONE`, irrevocably terminating the job if it has not already reached a terminal state. 428 "satisfiesPzs": True or False, # Reserved for future use. This field is set only in responses from the server; it is ignored if it is set in any requests. 429 "stageStates": [ # This field may be mutated by the Cloud Dataflow service; callers cannot mutate it. 430 { # A message describing the state of a particular execution stage. 431 "currentStateTime": "A String", # The time at which the stage transitioned to this state. 432 "executionStageName": "A String", # The name of the execution stage. 433 "executionStageState": "A String", # Executions stage states allow the same set of values as JobState. 434 }, 435 ], 436 "startTime": "A String", # The timestamp when the job was started (transitioned to JOB_STATE_PENDING). Flexible resource scheduling jobs are started with some delay after job creation, so start_time is unset before start and is updated when the job is started by the Cloud Dataflow service. For other jobs, start_time always equals to create_time and is immutable and set by the Cloud Dataflow service. 437 "steps": [ # Exactly one of step or steps_location should be specified. The top-level steps that constitute the entire job. Only retrieved with JOB_VIEW_ALL. 438 { # Defines a particular step within a Cloud Dataflow job. A job consists of multiple steps, each of which performs some specific operation as part of the overall job. Data is typically passed from one step to another as part of the job. Here's an example of a sequence of steps which together implement a Map-Reduce job: * Read a collection of data from some source, parsing the collection's elements. * Validate the elements. * Apply a user-defined function to map each element to some value and extract an element-specific key value. * Group elements with the same key into a single element with that key, transforming a multiply-keyed collection into a uniquely-keyed collection. * Write the elements out to some data sink. Note that the Cloud Dataflow service may be used to run many different types of jobs, not just Map-Reduce. 439 "kind": "A String", # The kind of step in the Cloud Dataflow job. 440 "name": "A String", # The name that identifies the step. This must be unique for each step with respect to all other steps in the Cloud Dataflow job. 441 "properties": { # Named properties associated with the step. Each kind of predefined step has its own required set of properties. Must be provided on Create. Only retrieved with JOB_VIEW_ALL. 442 "a_key": "", # Properties of the object. 443 }, 444 }, 445 ], 446 "stepsLocation": "A String", # The Cloud Storage location where the steps are stored. 447 "tempFiles": [ # A set of files the system should be aware of that are used for temporary storage. These temporary files will be removed on job completion. No duplicates are allowed. No file patterns are supported. The supported files are: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object} 448 "A String", 449 ], 450 "transformNameMapping": { # The map of transform name prefixes of the job to be replaced to the corresponding name prefixes of the new job. 451 "a_key": "A String", 452 }, 453 "type": "A String", # The type of Cloud Dataflow job. 454 }, 455 ], 456 "nextPageToken": "A String", # Set if there may be more results than fit in this response. 457}</pre> 458</div> 459 460<div class="method"> 461 <code class="details" id="aggregated_next">aggregated_next(previous_request, previous_response)</code> 462 <pre>Retrieves the next page of results. 463 464Args: 465 previous_request: The request for the previous page. (required) 466 previous_response: The response from the request for the previous page. (required) 467 468Returns: 469 A request object that you can call 'execute()' on to request the next 470 page. Returns None if there are no more items in the collection. 471 </pre> 472</div> 473 474<div class="method"> 475 <code class="details" id="close">close()</code> 476 <pre>Close httplib2 connections.</pre> 477</div> 478 479<div class="method"> 480 <code class="details" id="create">create(projectId, body=None, location=None, replaceJobId=None, view=None, x__xgafv=None)</code> 481 <pre>Creates a Cloud Dataflow job. To create a job, we recommend using `projects.locations.jobs.create` with a [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints). Using `projects.jobs.create` is not recommended, as your job will always start in `us-central1`. 482 483Args: 484 projectId: string, The ID of the Cloud Platform project that the job belongs to. (required) 485 body: object, The request body. 486 The object takes the form of: 487 488{ # Defines a job to be run by the Cloud Dataflow service. nextID: 26 489 "clientRequestId": "A String", # The client's unique identifier of the job, re-used across retried attempts. If this field is set, the service will ensure its uniqueness. The request to create a job will fail if the service has knowledge of a previously submitted job with the same client's ID and job name. The caller may use this field to ensure idempotence of job creation across retried attempts to create a job. By default, the field is empty and, in that case, the service ignores it. 490 "createTime": "A String", # The timestamp when the job was initially created. Immutable and set by the Cloud Dataflow service. 491 "createdFromSnapshotId": "A String", # If this is specified, the job's initial state is populated from the given snapshot. 492 "currentState": "A String", # The current state of the job. Jobs are created in the `JOB_STATE_STOPPED` state unless otherwise specified. A job in the `JOB_STATE_RUNNING` state may asynchronously enter a terminal state. After a job has reached a terminal state, no further state updates may be made. This field may be mutated by the Cloud Dataflow service; callers cannot mutate it. 493 "currentStateTime": "A String", # The timestamp associated with the current state. 494 "environment": { # Describes the environment in which a Dataflow Job runs. # The environment for the job. 495 "clusterManagerApiService": "A String", # The type of cluster manager API to use. If unknown or unspecified, the service will attempt to choose a reasonable default. This should be in the form of the API service name, e.g. "compute.googleapis.com". 496 "dataset": "A String", # The dataset for the current project where various workflow related tables are stored. The supported resource type is: Google BigQuery: bigquery.googleapis.com/{dataset} 497 "debugOptions": { # Describes any options that have an effect on the debugging of pipelines. # Any debugging options to be supplied to the job. 498 "enableHotKeyLogging": True or False, # When true, enables the logging of the literal hot key to the user's Cloud Logging. 499 }, 500 "experiments": [ # The list of experiments to enable. This field should be used for SDK related experiments and not for service related experiments. The proper field for service related experiments is service_options. 501 "A String", 502 ], 503 "flexResourceSchedulingGoal": "A String", # Which Flexible Resource Scheduling mode to run in. 504 "internalExperiments": { # Experimental settings. 505 "a_key": "", # Properties of the object. Contains field @type with type URL. 506 }, 507 "sdkPipelineOptions": { # The Cloud Dataflow SDK pipeline options specified by the user. These options are passed through the service and are used to recreate the SDK pipeline options on the worker in a language agnostic and platform independent way. 508 "a_key": "", # Properties of the object. 509 }, 510 "serviceAccountEmail": "A String", # Identity to run virtual machines as. Defaults to the default account. 511 "serviceKmsKeyName": "A String", # If set, contains the Cloud KMS key identifier used to encrypt data at rest, AKA a Customer Managed Encryption Key (CMEK). Format: projects/PROJECT_ID/locations/LOCATION/keyRings/KEY_RING/cryptoKeys/KEY 512 "serviceOptions": [ # The list of service options to enable. This field should be used for service related experiments only. These experiments, when graduating to GA, should be replaced by dedicated fields or become default (i.e. always on). 513 "A String", 514 ], 515 "shuffleMode": "A String", # Output only. The shuffle mode used for the job. 516 "tempStoragePrefix": "A String", # The prefix of the resources the system should use for temporary storage. The system will append the suffix "/temp-{JOBNAME} to this resource prefix, where {JOBNAME} is the value of the job_name field. The resulting bucket and object prefix is used as the prefix of the resources used to store temporary data needed during the job execution. NOTE: This will override the value in taskrunner_settings. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object} 517 "userAgent": { # A description of the process that generated the request. 518 "a_key": "", # Properties of the object. 519 }, 520 "version": { # A structure describing which components and their versions of the service are required in order to run the job. 521 "a_key": "", # Properties of the object. 522 }, 523 "workerPools": [ # The worker pools. At least one "harness" worker pool must be specified in order for the job to have workers. 524 { # Describes one particular pool of Cloud Dataflow workers to be instantiated by the Cloud Dataflow service in order to perform the computations required by a job. Note that a workflow job may use multiple pools, in order to match the various computational requirements of the various stages of the job. 525 "autoscalingSettings": { # Settings for WorkerPool autoscaling. # Settings for autoscaling of this WorkerPool. 526 "algorithm": "A String", # The algorithm to use for autoscaling. 527 "maxNumWorkers": 42, # The maximum number of workers to cap scaling at. 528 }, 529 "dataDisks": [ # Data disks that are used by a VM in this workflow. 530 { # Describes the data disk used by a workflow job. 531 "diskType": "A String", # Disk storage type, as defined by Google Compute Engine. This must be a disk type appropriate to the project and zone in which the workers will run. If unknown or unspecified, the service will attempt to choose a reasonable default. For example, the standard persistent disk type is a resource name typically ending in "pd-standard". If SSD persistent disks are available, the resource name typically ends with "pd-ssd". The actual valid values are defined the Google Compute Engine API, not by the Cloud Dataflow API; consult the Google Compute Engine documentation for more information about determining the set of available disk types for a particular project and zone. Google Compute Engine Disk types are local to a particular project in a particular zone, and so the resource name will typically look something like this: compute.googleapis.com/projects/project-id/zones/zone/diskTypes/pd-standard 532 "mountPoint": "A String", # Directory in a VM where disk is mounted. 533 "sizeGb": 42, # Size of disk in GB. If zero or unspecified, the service will attempt to choose a reasonable default. 534 }, 535 ], 536 "defaultPackageSet": "A String", # The default package set to install. This allows the service to select a default set of packages which are useful to worker harnesses written in a particular language. 537 "diskSizeGb": 42, # Size of root disk for VMs, in GB. If zero or unspecified, the service will attempt to choose a reasonable default. 538 "diskSourceImage": "A String", # Fully qualified source image for disks. 539 "diskType": "A String", # Type of root disk for VMs. If empty or unspecified, the service will attempt to choose a reasonable default. 540 "ipConfiguration": "A String", # Configuration for VM IPs. 541 "kind": "A String", # The kind of the worker pool; currently only `harness` and `shuffle` are supported. 542 "machineType": "A String", # Machine type (e.g. "n1-standard-1"). If empty or unspecified, the service will attempt to choose a reasonable default. 543 "metadata": { # Metadata to set on the Google Compute Engine VMs. 544 "a_key": "A String", 545 }, 546 "network": "A String", # Network to which VMs will be assigned. If empty or unspecified, the service will use the network "default". 547 "numThreadsPerWorker": 42, # The number of threads per worker harness. If empty or unspecified, the service will choose a number of threads (according to the number of cores on the selected machine type for batch, or 1 by convention for streaming). 548 "numWorkers": 42, # Number of Google Compute Engine workers in this pool needed to execute the job. If zero or unspecified, the service will attempt to choose a reasonable default. 549 "onHostMaintenance": "A String", # The action to take on host maintenance, as defined by the Google Compute Engine API. 550 "packages": [ # Packages to be installed on workers. 551 { # The packages that must be installed in order for a worker to run the steps of the Cloud Dataflow job that will be assigned to its worker pool. This is the mechanism by which the Cloud Dataflow SDK causes code to be loaded onto the workers. For example, the Cloud Dataflow Java SDK might use this to install jars containing the user's code and all of the various dependencies (libraries, data files, etc.) required in order for that code to run. 552 "location": "A String", # The resource to read the package from. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket} bucket.storage.googleapis.com/ 553 "name": "A String", # The name of the package. 554 }, 555 ], 556 "poolArgs": { # Extra arguments for this worker pool. 557 "a_key": "", # Properties of the object. Contains field @type with type URL. 558 }, 559 "sdkHarnessContainerImages": [ # Set of SDK harness containers needed to execute this pipeline. This will only be set in the Fn API path. For non-cross-language pipelines this should have only one entry. Cross-language pipelines will have two or more entries. 560 { # Defines a SDK harness container for executing Dataflow pipelines. 561 "containerImage": "A String", # A docker container image that resides in Google Container Registry. 562 "environmentId": "A String", # Environment ID for the Beam runner API proto Environment that corresponds to the current SDK Harness. 563 "useSingleCorePerContainer": True or False, # If true, recommends the Dataflow service to use only one core per SDK container instance with this image. If false (or unset) recommends using more than one core per SDK container instance with this image for efficiency. Note that Dataflow service may choose to override this property if needed. 564 }, 565 ], 566 "subnetwork": "A String", # Subnetwork to which VMs will be assigned, if desired. Expected to be of the form "regions/REGION/subnetworks/SUBNETWORK". 567 "taskrunnerSettings": { # Taskrunner configuration settings. # Settings passed through to Google Compute Engine workers when using the standard Dataflow task runner. Users should ignore this field. 568 "alsologtostderr": True or False, # Whether to also send taskrunner log info to stderr. 569 "baseTaskDir": "A String", # The location on the worker for task-specific subdirectories. 570 "baseUrl": "A String", # The base URL for the taskrunner to use when accessing Google Cloud APIs. When workers access Google Cloud APIs, they logically do so via relative URLs. If this field is specified, it supplies the base URL to use for resolving these relative URLs. The normative algorithm used is defined by RFC 1808, "Relative Uniform Resource Locators". If not specified, the default value is "http://www.googleapis.com/" 571 "commandlinesFileName": "A String", # The file to store preprocessing commands in. 572 "continueOnException": True or False, # Whether to continue taskrunner if an exception is hit. 573 "dataflowApiVersion": "A String", # The API version of endpoint, e.g. "v1b3" 574 "harnessCommand": "A String", # The command to launch the worker harness. 575 "languageHint": "A String", # The suggested backend language. 576 "logDir": "A String", # The directory on the VM to store logs. 577 "logToSerialconsole": True or False, # Whether to send taskrunner log info to Google Compute Engine VM serial console. 578 "logUploadLocation": "A String", # Indicates where to put logs. If this is not specified, the logs will not be uploaded. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object} 579 "oauthScopes": [ # The OAuth2 scopes to be requested by the taskrunner in order to access the Cloud Dataflow API. 580 "A String", 581 ], 582 "parallelWorkerSettings": { # Provides data to pass through to the worker harness. # The settings to pass to the parallel worker harness. 583 "baseUrl": "A String", # The base URL for accessing Google Cloud APIs. When workers access Google Cloud APIs, they logically do so via relative URLs. If this field is specified, it supplies the base URL to use for resolving these relative URLs. The normative algorithm used is defined by RFC 1808, "Relative Uniform Resource Locators". If not specified, the default value is "http://www.googleapis.com/" 584 "reportingEnabled": True or False, # Whether to send work progress updates to the service. 585 "servicePath": "A String", # The Cloud Dataflow service path relative to the root URL, for example, "dataflow/v1b3/projects". 586 "shuffleServicePath": "A String", # The Shuffle service path relative to the root URL, for example, "shuffle/v1beta1". 587 "tempStoragePrefix": "A String", # The prefix of the resources the system should use for temporary storage. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object} 588 "workerId": "A String", # The ID of the worker running this pipeline. 589 }, 590 "streamingWorkerMainClass": "A String", # The streaming worker main class name. 591 "taskGroup": "A String", # The UNIX group ID on the worker VM to use for tasks launched by taskrunner; e.g. "wheel". 592 "taskUser": "A String", # The UNIX user ID on the worker VM to use for tasks launched by taskrunner; e.g. "root". 593 "tempStoragePrefix": "A String", # The prefix of the resources the taskrunner should use for temporary storage. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object} 594 "vmId": "A String", # The ID string of the VM. 595 "workflowFileName": "A String", # The file to store the workflow in. 596 }, 597 "teardownPolicy": "A String", # Sets the policy for determining when to turndown worker pool. Allowed values are: `TEARDOWN_ALWAYS`, `TEARDOWN_ON_SUCCESS`, and `TEARDOWN_NEVER`. `TEARDOWN_ALWAYS` means workers are always torn down regardless of whether the job succeeds. `TEARDOWN_ON_SUCCESS` means workers are torn down if the job succeeds. `TEARDOWN_NEVER` means the workers are never torn down. If the workers are not torn down by the service, they will continue to run and use Google Compute Engine VM resources in the user's project until they are explicitly terminated by the user. Because of this, Google recommends using the `TEARDOWN_ALWAYS` policy except for small, manually supervised test jobs. If unknown or unspecified, the service will attempt to choose a reasonable default. 598 "workerHarnessContainerImage": "A String", # Required. Docker container image that executes the Cloud Dataflow worker harness, residing in Google Container Registry. Deprecated for the Fn API path. Use sdk_harness_container_images instead. 599 "zone": "A String", # Zone to run the worker pools in. If empty or unspecified, the service will attempt to choose a reasonable default. 600 }, 601 ], 602 "workerRegion": "A String", # The Compute Engine region (https://cloud.google.com/compute/docs/regions-zones/regions-zones) in which worker processing should occur, e.g. "us-west1". Mutually exclusive with worker_zone. If neither worker_region nor worker_zone is specified, default to the control plane's region. 603 "workerZone": "A String", # The Compute Engine zone (https://cloud.google.com/compute/docs/regions-zones/regions-zones) in which worker processing should occur, e.g. "us-west1-a". Mutually exclusive with worker_region. If neither worker_region nor worker_zone is specified, a zone in the control plane's region is chosen based on available capacity. 604 }, 605 "executionInfo": { # Additional information about how a Cloud Dataflow job will be executed that isn't contained in the submitted job. # Deprecated. 606 "stages": { # A mapping from each stage to the information about that stage. 607 "a_key": { # Contains information about how a particular google.dataflow.v1beta3.Step will be executed. 608 "stepName": [ # The steps associated with the execution stage. Note that stages may have several steps, and that a given step might be run by more than one stage. 609 "A String", 610 ], 611 }, 612 }, 613 }, 614 "id": "A String", # The unique ID of this job. This field is set by the Cloud Dataflow service when the Job is created, and is immutable for the life of the job. 615 "jobMetadata": { # Metadata available primarily for filtering jobs. Will be included in the ListJob response and Job SUMMARY view. # This field is populated by the Dataflow service to support filtering jobs by the metadata values provided here. Populated for ListJobs and all GetJob views SUMMARY and higher. 616 "bigTableDetails": [ # Identification of a Cloud Bigtable source used in the Dataflow job. 617 { # Metadata for a Cloud Bigtable connector used by the job. 618 "instanceId": "A String", # InstanceId accessed in the connection. 619 "projectId": "A String", # ProjectId accessed in the connection. 620 "tableId": "A String", # TableId accessed in the connection. 621 }, 622 ], 623 "bigqueryDetails": [ # Identification of a BigQuery source used in the Dataflow job. 624 { # Metadata for a BigQuery connector used by the job. 625 "dataset": "A String", # Dataset accessed in the connection. 626 "projectId": "A String", # Project accessed in the connection. 627 "query": "A String", # Query used to access data in the connection. 628 "table": "A String", # Table accessed in the connection. 629 }, 630 ], 631 "datastoreDetails": [ # Identification of a Datastore source used in the Dataflow job. 632 { # Metadata for a Datastore connector used by the job. 633 "namespace": "A String", # Namespace used in the connection. 634 "projectId": "A String", # ProjectId accessed in the connection. 635 }, 636 ], 637 "fileDetails": [ # Identification of a File source used in the Dataflow job. 638 { # Metadata for a File connector used by the job. 639 "filePattern": "A String", # File Pattern used to access files by the connector. 640 }, 641 ], 642 "pubsubDetails": [ # Identification of a Pub/Sub source used in the Dataflow job. 643 { # Metadata for a Pub/Sub connector used by the job. 644 "subscription": "A String", # Subscription used in the connection. 645 "topic": "A String", # Topic accessed in the connection. 646 }, 647 ], 648 "sdkVersion": { # The version of the SDK used to run the job. # The SDK version used to run the job. 649 "sdkSupportStatus": "A String", # The support status for this SDK version. 650 "version": "A String", # The version of the SDK used to run the job. 651 "versionDisplayName": "A String", # A readable string describing the version of the SDK. 652 }, 653 "spannerDetails": [ # Identification of a Spanner source used in the Dataflow job. 654 { # Metadata for a Spanner connector used by the job. 655 "databaseId": "A String", # DatabaseId accessed in the connection. 656 "instanceId": "A String", # InstanceId accessed in the connection. 657 "projectId": "A String", # ProjectId accessed in the connection. 658 }, 659 ], 660 }, 661 "labels": { # User-defined labels for this job. The labels map can contain no more than 64 entries. Entries of the labels map are UTF8 strings that comply with the following restrictions: * Keys must conform to regexp: \p{Ll}\p{Lo}{0,62} * Values must conform to regexp: [\p{Ll}\p{Lo}\p{N}_-]{0,63} * Both keys and values are additionally constrained to be <= 128 bytes in size. 662 "a_key": "A String", 663 }, 664 "location": "A String", # The [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints) that contains this job. 665 "name": "A String", # The user-specified Cloud Dataflow job name. Only one Job with a given name may exist in a project at any given time. If a caller attempts to create a Job with the same name as an already-existing Job, the attempt returns the existing Job. The name must match the regular expression `[a-z]([-a-z0-9]{0,38}[a-z0-9])?` 666 "pipelineDescription": { # A descriptive representation of submitted pipeline as well as the executed form. This data is provided by the Dataflow service for ease of visualizing the pipeline and interpreting Dataflow provided metrics. # Preliminary field: The format of this data may change at any time. A description of the user pipeline and stages through which it is executed. Created by Cloud Dataflow service. Only retrieved with JOB_VIEW_DESCRIPTION or JOB_VIEW_ALL. 667 "displayData": [ # Pipeline level display data. 668 { # Data provided with a pipeline or transform to provide descriptive info. 669 "boolValue": True or False, # Contains value if the data is of a boolean type. 670 "durationValue": "A String", # Contains value if the data is of duration type. 671 "floatValue": 3.14, # Contains value if the data is of float type. 672 "int64Value": "A String", # Contains value if the data is of int64 type. 673 "javaClassValue": "A String", # Contains value if the data is of java class type. 674 "key": "A String", # The key identifying the display data. This is intended to be used as a label for the display data when viewed in a dax monitoring system. 675 "label": "A String", # An optional label to display in a dax UI for the element. 676 "namespace": "A String", # The namespace for the key. This is usually a class name or programming language namespace (i.e. python module) which defines the display data. This allows a dax monitoring system to specially handle the data and perform custom rendering. 677 "shortStrValue": "A String", # A possible additional shorter value to display. For example a java_class_name_value of com.mypackage.MyDoFn will be stored with MyDoFn as the short_str_value and com.mypackage.MyDoFn as the java_class_name value. short_str_value can be displayed and java_class_name_value will be displayed as a tooltip. 678 "strValue": "A String", # Contains value if the data is of string type. 679 "timestampValue": "A String", # Contains value if the data is of timestamp type. 680 "url": "A String", # An optional full URL. 681 }, 682 ], 683 "executionPipelineStage": [ # Description of each stage of execution of the pipeline. 684 { # Description of the composing transforms, names/ids, and input/outputs of a stage of execution. Some composing transforms and sources may have been generated by the Dataflow service during execution planning. 685 "componentSource": [ # Collections produced and consumed by component transforms of this stage. 686 { # Description of an interstitial value between transforms in an execution stage. 687 "name": "A String", # Dataflow service generated name for this source. 688 "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated. 689 "userName": "A String", # Human-readable name for this transform; may be user or system generated. 690 }, 691 ], 692 "componentTransform": [ # Transforms that comprise this execution stage. 693 { # Description of a transform executed as part of an execution stage. 694 "name": "A String", # Dataflow service generated name for this source. 695 "originalTransform": "A String", # User name for the original user transform with which this transform is most closely associated. 696 "userName": "A String", # Human-readable name for this transform; may be user or system generated. 697 }, 698 ], 699 "id": "A String", # Dataflow service generated id for this stage. 700 "inputSource": [ # Input sources for this stage. 701 { # Description of an input or output of an execution stage. 702 "name": "A String", # Dataflow service generated name for this source. 703 "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated. 704 "sizeBytes": "A String", # Size of the source, if measurable. 705 "userName": "A String", # Human-readable name for this source; may be user or system generated. 706 }, 707 ], 708 "kind": "A String", # Type of transform this stage is executing. 709 "name": "A String", # Dataflow service generated name for this stage. 710 "outputSource": [ # Output sources for this stage. 711 { # Description of an input or output of an execution stage. 712 "name": "A String", # Dataflow service generated name for this source. 713 "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated. 714 "sizeBytes": "A String", # Size of the source, if measurable. 715 "userName": "A String", # Human-readable name for this source; may be user or system generated. 716 }, 717 ], 718 "prerequisiteStage": [ # Other stages that must complete before this stage can run. 719 "A String", 720 ], 721 }, 722 ], 723 "originalPipelineTransform": [ # Description of each transform in the pipeline and collections between them. 724 { # Description of the type, names/ids, and input/outputs for a transform. 725 "displayData": [ # Transform-specific display data. 726 { # Data provided with a pipeline or transform to provide descriptive info. 727 "boolValue": True or False, # Contains value if the data is of a boolean type. 728 "durationValue": "A String", # Contains value if the data is of duration type. 729 "floatValue": 3.14, # Contains value if the data is of float type. 730 "int64Value": "A String", # Contains value if the data is of int64 type. 731 "javaClassValue": "A String", # Contains value if the data is of java class type. 732 "key": "A String", # The key identifying the display data. This is intended to be used as a label for the display data when viewed in a dax monitoring system. 733 "label": "A String", # An optional label to display in a dax UI for the element. 734 "namespace": "A String", # The namespace for the key. This is usually a class name or programming language namespace (i.e. python module) which defines the display data. This allows a dax monitoring system to specially handle the data and perform custom rendering. 735 "shortStrValue": "A String", # A possible additional shorter value to display. For example a java_class_name_value of com.mypackage.MyDoFn will be stored with MyDoFn as the short_str_value and com.mypackage.MyDoFn as the java_class_name value. short_str_value can be displayed and java_class_name_value will be displayed as a tooltip. 736 "strValue": "A String", # Contains value if the data is of string type. 737 "timestampValue": "A String", # Contains value if the data is of timestamp type. 738 "url": "A String", # An optional full URL. 739 }, 740 ], 741 "id": "A String", # SDK generated id of this transform instance. 742 "inputCollectionName": [ # User names for all collection inputs to this transform. 743 "A String", 744 ], 745 "kind": "A String", # Type of transform. 746 "name": "A String", # User provided name for this transform instance. 747 "outputCollectionName": [ # User names for all collection outputs to this transform. 748 "A String", 749 ], 750 }, 751 ], 752 }, 753 "projectId": "A String", # The ID of the Cloud Platform project that the job belongs to. 754 "replaceJobId": "A String", # If this job is an update of an existing job, this field is the job ID of the job it replaced. When sending a `CreateJobRequest`, you can update a job by specifying it here. The job named here is stopped, and its intermediate state is transferred to this job. 755 "replacedByJobId": "A String", # If another job is an update of this job (and thus, this job is in `JOB_STATE_UPDATED`), this field contains the ID of that job. 756 "requestedState": "A String", # The job's requested state. `UpdateJob` may be used to switch between the `JOB_STATE_STOPPED` and `JOB_STATE_RUNNING` states, by setting requested_state. `UpdateJob` may also be used to directly set a job's requested state to `JOB_STATE_CANCELLED` or `JOB_STATE_DONE`, irrevocably terminating the job if it has not already reached a terminal state. 757 "satisfiesPzs": True or False, # Reserved for future use. This field is set only in responses from the server; it is ignored if it is set in any requests. 758 "stageStates": [ # This field may be mutated by the Cloud Dataflow service; callers cannot mutate it. 759 { # A message describing the state of a particular execution stage. 760 "currentStateTime": "A String", # The time at which the stage transitioned to this state. 761 "executionStageName": "A String", # The name of the execution stage. 762 "executionStageState": "A String", # Executions stage states allow the same set of values as JobState. 763 }, 764 ], 765 "startTime": "A String", # The timestamp when the job was started (transitioned to JOB_STATE_PENDING). Flexible resource scheduling jobs are started with some delay after job creation, so start_time is unset before start and is updated when the job is started by the Cloud Dataflow service. For other jobs, start_time always equals to create_time and is immutable and set by the Cloud Dataflow service. 766 "steps": [ # Exactly one of step or steps_location should be specified. The top-level steps that constitute the entire job. Only retrieved with JOB_VIEW_ALL. 767 { # Defines a particular step within a Cloud Dataflow job. A job consists of multiple steps, each of which performs some specific operation as part of the overall job. Data is typically passed from one step to another as part of the job. Here's an example of a sequence of steps which together implement a Map-Reduce job: * Read a collection of data from some source, parsing the collection's elements. * Validate the elements. * Apply a user-defined function to map each element to some value and extract an element-specific key value. * Group elements with the same key into a single element with that key, transforming a multiply-keyed collection into a uniquely-keyed collection. * Write the elements out to some data sink. Note that the Cloud Dataflow service may be used to run many different types of jobs, not just Map-Reduce. 768 "kind": "A String", # The kind of step in the Cloud Dataflow job. 769 "name": "A String", # The name that identifies the step. This must be unique for each step with respect to all other steps in the Cloud Dataflow job. 770 "properties": { # Named properties associated with the step. Each kind of predefined step has its own required set of properties. Must be provided on Create. Only retrieved with JOB_VIEW_ALL. 771 "a_key": "", # Properties of the object. 772 }, 773 }, 774 ], 775 "stepsLocation": "A String", # The Cloud Storage location where the steps are stored. 776 "tempFiles": [ # A set of files the system should be aware of that are used for temporary storage. These temporary files will be removed on job completion. No duplicates are allowed. No file patterns are supported. The supported files are: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object} 777 "A String", 778 ], 779 "transformNameMapping": { # The map of transform name prefixes of the job to be replaced to the corresponding name prefixes of the new job. 780 "a_key": "A String", 781 }, 782 "type": "A String", # The type of Cloud Dataflow job. 783} 784 785 location: string, The [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints) that contains this job. 786 replaceJobId: string, Deprecated. This field is now in the Job message. 787 view: string, The level of information requested in response. 788 Allowed values 789 JOB_VIEW_UNKNOWN - The job view to return isn't specified, or is unknown. Responses will contain at least the `JOB_VIEW_SUMMARY` information, and may contain additional information. 790 JOB_VIEW_SUMMARY - Request summary information only: Project ID, Job ID, job name, job type, job status, start/end time, and Cloud SDK version details. 791 JOB_VIEW_ALL - Request all information available for this job. 792 JOB_VIEW_DESCRIPTION - Request summary info and limited job description data for steps, labels and environment. 793 x__xgafv: string, V1 error format. 794 Allowed values 795 1 - v1 error format 796 2 - v2 error format 797 798Returns: 799 An object of the form: 800 801 { # Defines a job to be run by the Cloud Dataflow service. nextID: 26 802 "clientRequestId": "A String", # The client's unique identifier of the job, re-used across retried attempts. If this field is set, the service will ensure its uniqueness. The request to create a job will fail if the service has knowledge of a previously submitted job with the same client's ID and job name. The caller may use this field to ensure idempotence of job creation across retried attempts to create a job. By default, the field is empty and, in that case, the service ignores it. 803 "createTime": "A String", # The timestamp when the job was initially created. Immutable and set by the Cloud Dataflow service. 804 "createdFromSnapshotId": "A String", # If this is specified, the job's initial state is populated from the given snapshot. 805 "currentState": "A String", # The current state of the job. Jobs are created in the `JOB_STATE_STOPPED` state unless otherwise specified. A job in the `JOB_STATE_RUNNING` state may asynchronously enter a terminal state. After a job has reached a terminal state, no further state updates may be made. This field may be mutated by the Cloud Dataflow service; callers cannot mutate it. 806 "currentStateTime": "A String", # The timestamp associated with the current state. 807 "environment": { # Describes the environment in which a Dataflow Job runs. # The environment for the job. 808 "clusterManagerApiService": "A String", # The type of cluster manager API to use. If unknown or unspecified, the service will attempt to choose a reasonable default. This should be in the form of the API service name, e.g. "compute.googleapis.com". 809 "dataset": "A String", # The dataset for the current project where various workflow related tables are stored. The supported resource type is: Google BigQuery: bigquery.googleapis.com/{dataset} 810 "debugOptions": { # Describes any options that have an effect on the debugging of pipelines. # Any debugging options to be supplied to the job. 811 "enableHotKeyLogging": True or False, # When true, enables the logging of the literal hot key to the user's Cloud Logging. 812 }, 813 "experiments": [ # The list of experiments to enable. This field should be used for SDK related experiments and not for service related experiments. The proper field for service related experiments is service_options. 814 "A String", 815 ], 816 "flexResourceSchedulingGoal": "A String", # Which Flexible Resource Scheduling mode to run in. 817 "internalExperiments": { # Experimental settings. 818 "a_key": "", # Properties of the object. Contains field @type with type URL. 819 }, 820 "sdkPipelineOptions": { # The Cloud Dataflow SDK pipeline options specified by the user. These options are passed through the service and are used to recreate the SDK pipeline options on the worker in a language agnostic and platform independent way. 821 "a_key": "", # Properties of the object. 822 }, 823 "serviceAccountEmail": "A String", # Identity to run virtual machines as. Defaults to the default account. 824 "serviceKmsKeyName": "A String", # If set, contains the Cloud KMS key identifier used to encrypt data at rest, AKA a Customer Managed Encryption Key (CMEK). Format: projects/PROJECT_ID/locations/LOCATION/keyRings/KEY_RING/cryptoKeys/KEY 825 "serviceOptions": [ # The list of service options to enable. This field should be used for service related experiments only. These experiments, when graduating to GA, should be replaced by dedicated fields or become default (i.e. always on). 826 "A String", 827 ], 828 "shuffleMode": "A String", # Output only. The shuffle mode used for the job. 829 "tempStoragePrefix": "A String", # The prefix of the resources the system should use for temporary storage. The system will append the suffix "/temp-{JOBNAME} to this resource prefix, where {JOBNAME} is the value of the job_name field. The resulting bucket and object prefix is used as the prefix of the resources used to store temporary data needed during the job execution. NOTE: This will override the value in taskrunner_settings. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object} 830 "userAgent": { # A description of the process that generated the request. 831 "a_key": "", # Properties of the object. 832 }, 833 "version": { # A structure describing which components and their versions of the service are required in order to run the job. 834 "a_key": "", # Properties of the object. 835 }, 836 "workerPools": [ # The worker pools. At least one "harness" worker pool must be specified in order for the job to have workers. 837 { # Describes one particular pool of Cloud Dataflow workers to be instantiated by the Cloud Dataflow service in order to perform the computations required by a job. Note that a workflow job may use multiple pools, in order to match the various computational requirements of the various stages of the job. 838 "autoscalingSettings": { # Settings for WorkerPool autoscaling. # Settings for autoscaling of this WorkerPool. 839 "algorithm": "A String", # The algorithm to use for autoscaling. 840 "maxNumWorkers": 42, # The maximum number of workers to cap scaling at. 841 }, 842 "dataDisks": [ # Data disks that are used by a VM in this workflow. 843 { # Describes the data disk used by a workflow job. 844 "diskType": "A String", # Disk storage type, as defined by Google Compute Engine. This must be a disk type appropriate to the project and zone in which the workers will run. If unknown or unspecified, the service will attempt to choose a reasonable default. For example, the standard persistent disk type is a resource name typically ending in "pd-standard". If SSD persistent disks are available, the resource name typically ends with "pd-ssd". The actual valid values are defined the Google Compute Engine API, not by the Cloud Dataflow API; consult the Google Compute Engine documentation for more information about determining the set of available disk types for a particular project and zone. Google Compute Engine Disk types are local to a particular project in a particular zone, and so the resource name will typically look something like this: compute.googleapis.com/projects/project-id/zones/zone/diskTypes/pd-standard 845 "mountPoint": "A String", # Directory in a VM where disk is mounted. 846 "sizeGb": 42, # Size of disk in GB. If zero or unspecified, the service will attempt to choose a reasonable default. 847 }, 848 ], 849 "defaultPackageSet": "A String", # The default package set to install. This allows the service to select a default set of packages which are useful to worker harnesses written in a particular language. 850 "diskSizeGb": 42, # Size of root disk for VMs, in GB. If zero or unspecified, the service will attempt to choose a reasonable default. 851 "diskSourceImage": "A String", # Fully qualified source image for disks. 852 "diskType": "A String", # Type of root disk for VMs. If empty or unspecified, the service will attempt to choose a reasonable default. 853 "ipConfiguration": "A String", # Configuration for VM IPs. 854 "kind": "A String", # The kind of the worker pool; currently only `harness` and `shuffle` are supported. 855 "machineType": "A String", # Machine type (e.g. "n1-standard-1"). If empty or unspecified, the service will attempt to choose a reasonable default. 856 "metadata": { # Metadata to set on the Google Compute Engine VMs. 857 "a_key": "A String", 858 }, 859 "network": "A String", # Network to which VMs will be assigned. If empty or unspecified, the service will use the network "default". 860 "numThreadsPerWorker": 42, # The number of threads per worker harness. If empty or unspecified, the service will choose a number of threads (according to the number of cores on the selected machine type for batch, or 1 by convention for streaming). 861 "numWorkers": 42, # Number of Google Compute Engine workers in this pool needed to execute the job. If zero or unspecified, the service will attempt to choose a reasonable default. 862 "onHostMaintenance": "A String", # The action to take on host maintenance, as defined by the Google Compute Engine API. 863 "packages": [ # Packages to be installed on workers. 864 { # The packages that must be installed in order for a worker to run the steps of the Cloud Dataflow job that will be assigned to its worker pool. This is the mechanism by which the Cloud Dataflow SDK causes code to be loaded onto the workers. For example, the Cloud Dataflow Java SDK might use this to install jars containing the user's code and all of the various dependencies (libraries, data files, etc.) required in order for that code to run. 865 "location": "A String", # The resource to read the package from. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket} bucket.storage.googleapis.com/ 866 "name": "A String", # The name of the package. 867 }, 868 ], 869 "poolArgs": { # Extra arguments for this worker pool. 870 "a_key": "", # Properties of the object. Contains field @type with type URL. 871 }, 872 "sdkHarnessContainerImages": [ # Set of SDK harness containers needed to execute this pipeline. This will only be set in the Fn API path. For non-cross-language pipelines this should have only one entry. Cross-language pipelines will have two or more entries. 873 { # Defines a SDK harness container for executing Dataflow pipelines. 874 "containerImage": "A String", # A docker container image that resides in Google Container Registry. 875 "environmentId": "A String", # Environment ID for the Beam runner API proto Environment that corresponds to the current SDK Harness. 876 "useSingleCorePerContainer": True or False, # If true, recommends the Dataflow service to use only one core per SDK container instance with this image. If false (or unset) recommends using more than one core per SDK container instance with this image for efficiency. Note that Dataflow service may choose to override this property if needed. 877 }, 878 ], 879 "subnetwork": "A String", # Subnetwork to which VMs will be assigned, if desired. Expected to be of the form "regions/REGION/subnetworks/SUBNETWORK". 880 "taskrunnerSettings": { # Taskrunner configuration settings. # Settings passed through to Google Compute Engine workers when using the standard Dataflow task runner. Users should ignore this field. 881 "alsologtostderr": True or False, # Whether to also send taskrunner log info to stderr. 882 "baseTaskDir": "A String", # The location on the worker for task-specific subdirectories. 883 "baseUrl": "A String", # The base URL for the taskrunner to use when accessing Google Cloud APIs. When workers access Google Cloud APIs, they logically do so via relative URLs. If this field is specified, it supplies the base URL to use for resolving these relative URLs. The normative algorithm used is defined by RFC 1808, "Relative Uniform Resource Locators". If not specified, the default value is "http://www.googleapis.com/" 884 "commandlinesFileName": "A String", # The file to store preprocessing commands in. 885 "continueOnException": True or False, # Whether to continue taskrunner if an exception is hit. 886 "dataflowApiVersion": "A String", # The API version of endpoint, e.g. "v1b3" 887 "harnessCommand": "A String", # The command to launch the worker harness. 888 "languageHint": "A String", # The suggested backend language. 889 "logDir": "A String", # The directory on the VM to store logs. 890 "logToSerialconsole": True or False, # Whether to send taskrunner log info to Google Compute Engine VM serial console. 891 "logUploadLocation": "A String", # Indicates where to put logs. If this is not specified, the logs will not be uploaded. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object} 892 "oauthScopes": [ # The OAuth2 scopes to be requested by the taskrunner in order to access the Cloud Dataflow API. 893 "A String", 894 ], 895 "parallelWorkerSettings": { # Provides data to pass through to the worker harness. # The settings to pass to the parallel worker harness. 896 "baseUrl": "A String", # The base URL for accessing Google Cloud APIs. When workers access Google Cloud APIs, they logically do so via relative URLs. If this field is specified, it supplies the base URL to use for resolving these relative URLs. The normative algorithm used is defined by RFC 1808, "Relative Uniform Resource Locators". If not specified, the default value is "http://www.googleapis.com/" 897 "reportingEnabled": True or False, # Whether to send work progress updates to the service. 898 "servicePath": "A String", # The Cloud Dataflow service path relative to the root URL, for example, "dataflow/v1b3/projects". 899 "shuffleServicePath": "A String", # The Shuffle service path relative to the root URL, for example, "shuffle/v1beta1". 900 "tempStoragePrefix": "A String", # The prefix of the resources the system should use for temporary storage. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object} 901 "workerId": "A String", # The ID of the worker running this pipeline. 902 }, 903 "streamingWorkerMainClass": "A String", # The streaming worker main class name. 904 "taskGroup": "A String", # The UNIX group ID on the worker VM to use for tasks launched by taskrunner; e.g. "wheel". 905 "taskUser": "A String", # The UNIX user ID on the worker VM to use for tasks launched by taskrunner; e.g. "root". 906 "tempStoragePrefix": "A String", # The prefix of the resources the taskrunner should use for temporary storage. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object} 907 "vmId": "A String", # The ID string of the VM. 908 "workflowFileName": "A String", # The file to store the workflow in. 909 }, 910 "teardownPolicy": "A String", # Sets the policy for determining when to turndown worker pool. Allowed values are: `TEARDOWN_ALWAYS`, `TEARDOWN_ON_SUCCESS`, and `TEARDOWN_NEVER`. `TEARDOWN_ALWAYS` means workers are always torn down regardless of whether the job succeeds. `TEARDOWN_ON_SUCCESS` means workers are torn down if the job succeeds. `TEARDOWN_NEVER` means the workers are never torn down. If the workers are not torn down by the service, they will continue to run and use Google Compute Engine VM resources in the user's project until they are explicitly terminated by the user. Because of this, Google recommends using the `TEARDOWN_ALWAYS` policy except for small, manually supervised test jobs. If unknown or unspecified, the service will attempt to choose a reasonable default. 911 "workerHarnessContainerImage": "A String", # Required. Docker container image that executes the Cloud Dataflow worker harness, residing in Google Container Registry. Deprecated for the Fn API path. Use sdk_harness_container_images instead. 912 "zone": "A String", # Zone to run the worker pools in. If empty or unspecified, the service will attempt to choose a reasonable default. 913 }, 914 ], 915 "workerRegion": "A String", # The Compute Engine region (https://cloud.google.com/compute/docs/regions-zones/regions-zones) in which worker processing should occur, e.g. "us-west1". Mutually exclusive with worker_zone. If neither worker_region nor worker_zone is specified, default to the control plane's region. 916 "workerZone": "A String", # The Compute Engine zone (https://cloud.google.com/compute/docs/regions-zones/regions-zones) in which worker processing should occur, e.g. "us-west1-a". Mutually exclusive with worker_region. If neither worker_region nor worker_zone is specified, a zone in the control plane's region is chosen based on available capacity. 917 }, 918 "executionInfo": { # Additional information about how a Cloud Dataflow job will be executed that isn't contained in the submitted job. # Deprecated. 919 "stages": { # A mapping from each stage to the information about that stage. 920 "a_key": { # Contains information about how a particular google.dataflow.v1beta3.Step will be executed. 921 "stepName": [ # The steps associated with the execution stage. Note that stages may have several steps, and that a given step might be run by more than one stage. 922 "A String", 923 ], 924 }, 925 }, 926 }, 927 "id": "A String", # The unique ID of this job. This field is set by the Cloud Dataflow service when the Job is created, and is immutable for the life of the job. 928 "jobMetadata": { # Metadata available primarily for filtering jobs. Will be included in the ListJob response and Job SUMMARY view. # This field is populated by the Dataflow service to support filtering jobs by the metadata values provided here. Populated for ListJobs and all GetJob views SUMMARY and higher. 929 "bigTableDetails": [ # Identification of a Cloud Bigtable source used in the Dataflow job. 930 { # Metadata for a Cloud Bigtable connector used by the job. 931 "instanceId": "A String", # InstanceId accessed in the connection. 932 "projectId": "A String", # ProjectId accessed in the connection. 933 "tableId": "A String", # TableId accessed in the connection. 934 }, 935 ], 936 "bigqueryDetails": [ # Identification of a BigQuery source used in the Dataflow job. 937 { # Metadata for a BigQuery connector used by the job. 938 "dataset": "A String", # Dataset accessed in the connection. 939 "projectId": "A String", # Project accessed in the connection. 940 "query": "A String", # Query used to access data in the connection. 941 "table": "A String", # Table accessed in the connection. 942 }, 943 ], 944 "datastoreDetails": [ # Identification of a Datastore source used in the Dataflow job. 945 { # Metadata for a Datastore connector used by the job. 946 "namespace": "A String", # Namespace used in the connection. 947 "projectId": "A String", # ProjectId accessed in the connection. 948 }, 949 ], 950 "fileDetails": [ # Identification of a File source used in the Dataflow job. 951 { # Metadata for a File connector used by the job. 952 "filePattern": "A String", # File Pattern used to access files by the connector. 953 }, 954 ], 955 "pubsubDetails": [ # Identification of a Pub/Sub source used in the Dataflow job. 956 { # Metadata for a Pub/Sub connector used by the job. 957 "subscription": "A String", # Subscription used in the connection. 958 "topic": "A String", # Topic accessed in the connection. 959 }, 960 ], 961 "sdkVersion": { # The version of the SDK used to run the job. # The SDK version used to run the job. 962 "sdkSupportStatus": "A String", # The support status for this SDK version. 963 "version": "A String", # The version of the SDK used to run the job. 964 "versionDisplayName": "A String", # A readable string describing the version of the SDK. 965 }, 966 "spannerDetails": [ # Identification of a Spanner source used in the Dataflow job. 967 { # Metadata for a Spanner connector used by the job. 968 "databaseId": "A String", # DatabaseId accessed in the connection. 969 "instanceId": "A String", # InstanceId accessed in the connection. 970 "projectId": "A String", # ProjectId accessed in the connection. 971 }, 972 ], 973 }, 974 "labels": { # User-defined labels for this job. The labels map can contain no more than 64 entries. Entries of the labels map are UTF8 strings that comply with the following restrictions: * Keys must conform to regexp: \p{Ll}\p{Lo}{0,62} * Values must conform to regexp: [\p{Ll}\p{Lo}\p{N}_-]{0,63} * Both keys and values are additionally constrained to be <= 128 bytes in size. 975 "a_key": "A String", 976 }, 977 "location": "A String", # The [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints) that contains this job. 978 "name": "A String", # The user-specified Cloud Dataflow job name. Only one Job with a given name may exist in a project at any given time. If a caller attempts to create a Job with the same name as an already-existing Job, the attempt returns the existing Job. The name must match the regular expression `[a-z]([-a-z0-9]{0,38}[a-z0-9])?` 979 "pipelineDescription": { # A descriptive representation of submitted pipeline as well as the executed form. This data is provided by the Dataflow service for ease of visualizing the pipeline and interpreting Dataflow provided metrics. # Preliminary field: The format of this data may change at any time. A description of the user pipeline and stages through which it is executed. Created by Cloud Dataflow service. Only retrieved with JOB_VIEW_DESCRIPTION or JOB_VIEW_ALL. 980 "displayData": [ # Pipeline level display data. 981 { # Data provided with a pipeline or transform to provide descriptive info. 982 "boolValue": True or False, # Contains value if the data is of a boolean type. 983 "durationValue": "A String", # Contains value if the data is of duration type. 984 "floatValue": 3.14, # Contains value if the data is of float type. 985 "int64Value": "A String", # Contains value if the data is of int64 type. 986 "javaClassValue": "A String", # Contains value if the data is of java class type. 987 "key": "A String", # The key identifying the display data. This is intended to be used as a label for the display data when viewed in a dax monitoring system. 988 "label": "A String", # An optional label to display in a dax UI for the element. 989 "namespace": "A String", # The namespace for the key. This is usually a class name or programming language namespace (i.e. python module) which defines the display data. This allows a dax monitoring system to specially handle the data and perform custom rendering. 990 "shortStrValue": "A String", # A possible additional shorter value to display. For example a java_class_name_value of com.mypackage.MyDoFn will be stored with MyDoFn as the short_str_value and com.mypackage.MyDoFn as the java_class_name value. short_str_value can be displayed and java_class_name_value will be displayed as a tooltip. 991 "strValue": "A String", # Contains value if the data is of string type. 992 "timestampValue": "A String", # Contains value if the data is of timestamp type. 993 "url": "A String", # An optional full URL. 994 }, 995 ], 996 "executionPipelineStage": [ # Description of each stage of execution of the pipeline. 997 { # Description of the composing transforms, names/ids, and input/outputs of a stage of execution. Some composing transforms and sources may have been generated by the Dataflow service during execution planning. 998 "componentSource": [ # Collections produced and consumed by component transforms of this stage. 999 { # Description of an interstitial value between transforms in an execution stage. 1000 "name": "A String", # Dataflow service generated name for this source. 1001 "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated. 1002 "userName": "A String", # Human-readable name for this transform; may be user or system generated. 1003 }, 1004 ], 1005 "componentTransform": [ # Transforms that comprise this execution stage. 1006 { # Description of a transform executed as part of an execution stage. 1007 "name": "A String", # Dataflow service generated name for this source. 1008 "originalTransform": "A String", # User name for the original user transform with which this transform is most closely associated. 1009 "userName": "A String", # Human-readable name for this transform; may be user or system generated. 1010 }, 1011 ], 1012 "id": "A String", # Dataflow service generated id for this stage. 1013 "inputSource": [ # Input sources for this stage. 1014 { # Description of an input or output of an execution stage. 1015 "name": "A String", # Dataflow service generated name for this source. 1016 "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated. 1017 "sizeBytes": "A String", # Size of the source, if measurable. 1018 "userName": "A String", # Human-readable name for this source; may be user or system generated. 1019 }, 1020 ], 1021 "kind": "A String", # Type of transform this stage is executing. 1022 "name": "A String", # Dataflow service generated name for this stage. 1023 "outputSource": [ # Output sources for this stage. 1024 { # Description of an input or output of an execution stage. 1025 "name": "A String", # Dataflow service generated name for this source. 1026 "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated. 1027 "sizeBytes": "A String", # Size of the source, if measurable. 1028 "userName": "A String", # Human-readable name for this source; may be user or system generated. 1029 }, 1030 ], 1031 "prerequisiteStage": [ # Other stages that must complete before this stage can run. 1032 "A String", 1033 ], 1034 }, 1035 ], 1036 "originalPipelineTransform": [ # Description of each transform in the pipeline and collections between them. 1037 { # Description of the type, names/ids, and input/outputs for a transform. 1038 "displayData": [ # Transform-specific display data. 1039 { # Data provided with a pipeline or transform to provide descriptive info. 1040 "boolValue": True or False, # Contains value if the data is of a boolean type. 1041 "durationValue": "A String", # Contains value if the data is of duration type. 1042 "floatValue": 3.14, # Contains value if the data is of float type. 1043 "int64Value": "A String", # Contains value if the data is of int64 type. 1044 "javaClassValue": "A String", # Contains value if the data is of java class type. 1045 "key": "A String", # The key identifying the display data. This is intended to be used as a label for the display data when viewed in a dax monitoring system. 1046 "label": "A String", # An optional label to display in a dax UI for the element. 1047 "namespace": "A String", # The namespace for the key. This is usually a class name or programming language namespace (i.e. python module) which defines the display data. This allows a dax monitoring system to specially handle the data and perform custom rendering. 1048 "shortStrValue": "A String", # A possible additional shorter value to display. For example a java_class_name_value of com.mypackage.MyDoFn will be stored with MyDoFn as the short_str_value and com.mypackage.MyDoFn as the java_class_name value. short_str_value can be displayed and java_class_name_value will be displayed as a tooltip. 1049 "strValue": "A String", # Contains value if the data is of string type. 1050 "timestampValue": "A String", # Contains value if the data is of timestamp type. 1051 "url": "A String", # An optional full URL. 1052 }, 1053 ], 1054 "id": "A String", # SDK generated id of this transform instance. 1055 "inputCollectionName": [ # User names for all collection inputs to this transform. 1056 "A String", 1057 ], 1058 "kind": "A String", # Type of transform. 1059 "name": "A String", # User provided name for this transform instance. 1060 "outputCollectionName": [ # User names for all collection outputs to this transform. 1061 "A String", 1062 ], 1063 }, 1064 ], 1065 }, 1066 "projectId": "A String", # The ID of the Cloud Platform project that the job belongs to. 1067 "replaceJobId": "A String", # If this job is an update of an existing job, this field is the job ID of the job it replaced. When sending a `CreateJobRequest`, you can update a job by specifying it here. The job named here is stopped, and its intermediate state is transferred to this job. 1068 "replacedByJobId": "A String", # If another job is an update of this job (and thus, this job is in `JOB_STATE_UPDATED`), this field contains the ID of that job. 1069 "requestedState": "A String", # The job's requested state. `UpdateJob` may be used to switch between the `JOB_STATE_STOPPED` and `JOB_STATE_RUNNING` states, by setting requested_state. `UpdateJob` may also be used to directly set a job's requested state to `JOB_STATE_CANCELLED` or `JOB_STATE_DONE`, irrevocably terminating the job if it has not already reached a terminal state. 1070 "satisfiesPzs": True or False, # Reserved for future use. This field is set only in responses from the server; it is ignored if it is set in any requests. 1071 "stageStates": [ # This field may be mutated by the Cloud Dataflow service; callers cannot mutate it. 1072 { # A message describing the state of a particular execution stage. 1073 "currentStateTime": "A String", # The time at which the stage transitioned to this state. 1074 "executionStageName": "A String", # The name of the execution stage. 1075 "executionStageState": "A String", # Executions stage states allow the same set of values as JobState. 1076 }, 1077 ], 1078 "startTime": "A String", # The timestamp when the job was started (transitioned to JOB_STATE_PENDING). Flexible resource scheduling jobs are started with some delay after job creation, so start_time is unset before start and is updated when the job is started by the Cloud Dataflow service. For other jobs, start_time always equals to create_time and is immutable and set by the Cloud Dataflow service. 1079 "steps": [ # Exactly one of step or steps_location should be specified. The top-level steps that constitute the entire job. Only retrieved with JOB_VIEW_ALL. 1080 { # Defines a particular step within a Cloud Dataflow job. A job consists of multiple steps, each of which performs some specific operation as part of the overall job. Data is typically passed from one step to another as part of the job. Here's an example of a sequence of steps which together implement a Map-Reduce job: * Read a collection of data from some source, parsing the collection's elements. * Validate the elements. * Apply a user-defined function to map each element to some value and extract an element-specific key value. * Group elements with the same key into a single element with that key, transforming a multiply-keyed collection into a uniquely-keyed collection. * Write the elements out to some data sink. Note that the Cloud Dataflow service may be used to run many different types of jobs, not just Map-Reduce. 1081 "kind": "A String", # The kind of step in the Cloud Dataflow job. 1082 "name": "A String", # The name that identifies the step. This must be unique for each step with respect to all other steps in the Cloud Dataflow job. 1083 "properties": { # Named properties associated with the step. Each kind of predefined step has its own required set of properties. Must be provided on Create. Only retrieved with JOB_VIEW_ALL. 1084 "a_key": "", # Properties of the object. 1085 }, 1086 }, 1087 ], 1088 "stepsLocation": "A String", # The Cloud Storage location where the steps are stored. 1089 "tempFiles": [ # A set of files the system should be aware of that are used for temporary storage. These temporary files will be removed on job completion. No duplicates are allowed. No file patterns are supported. The supported files are: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object} 1090 "A String", 1091 ], 1092 "transformNameMapping": { # The map of transform name prefixes of the job to be replaced to the corresponding name prefixes of the new job. 1093 "a_key": "A String", 1094 }, 1095 "type": "A String", # The type of Cloud Dataflow job. 1096}</pre> 1097</div> 1098 1099<div class="method"> 1100 <code class="details" id="get">get(projectId, jobId, location=None, view=None, x__xgafv=None)</code> 1101 <pre>Gets the state of the specified Cloud Dataflow job. To get the state of a job, we recommend using `projects.locations.jobs.get` with a [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints). Using `projects.jobs.get` is not recommended, as you can only get the state of jobs that are running in `us-central1`. 1102 1103Args: 1104 projectId: string, The ID of the Cloud Platform project that the job belongs to. (required) 1105 jobId: string, The job ID. (required) 1106 location: string, The [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints) that contains this job. 1107 view: string, The level of information requested in response. 1108 Allowed values 1109 JOB_VIEW_UNKNOWN - The job view to return isn't specified, or is unknown. Responses will contain at least the `JOB_VIEW_SUMMARY` information, and may contain additional information. 1110 JOB_VIEW_SUMMARY - Request summary information only: Project ID, Job ID, job name, job type, job status, start/end time, and Cloud SDK version details. 1111 JOB_VIEW_ALL - Request all information available for this job. 1112 JOB_VIEW_DESCRIPTION - Request summary info and limited job description data for steps, labels and environment. 1113 x__xgafv: string, V1 error format. 1114 Allowed values 1115 1 - v1 error format 1116 2 - v2 error format 1117 1118Returns: 1119 An object of the form: 1120 1121 { # Defines a job to be run by the Cloud Dataflow service. nextID: 26 1122 "clientRequestId": "A String", # The client's unique identifier of the job, re-used across retried attempts. If this field is set, the service will ensure its uniqueness. The request to create a job will fail if the service has knowledge of a previously submitted job with the same client's ID and job name. The caller may use this field to ensure idempotence of job creation across retried attempts to create a job. By default, the field is empty and, in that case, the service ignores it. 1123 "createTime": "A String", # The timestamp when the job was initially created. Immutable and set by the Cloud Dataflow service. 1124 "createdFromSnapshotId": "A String", # If this is specified, the job's initial state is populated from the given snapshot. 1125 "currentState": "A String", # The current state of the job. Jobs are created in the `JOB_STATE_STOPPED` state unless otherwise specified. A job in the `JOB_STATE_RUNNING` state may asynchronously enter a terminal state. After a job has reached a terminal state, no further state updates may be made. This field may be mutated by the Cloud Dataflow service; callers cannot mutate it. 1126 "currentStateTime": "A String", # The timestamp associated with the current state. 1127 "environment": { # Describes the environment in which a Dataflow Job runs. # The environment for the job. 1128 "clusterManagerApiService": "A String", # The type of cluster manager API to use. If unknown or unspecified, the service will attempt to choose a reasonable default. This should be in the form of the API service name, e.g. "compute.googleapis.com". 1129 "dataset": "A String", # The dataset for the current project where various workflow related tables are stored. The supported resource type is: Google BigQuery: bigquery.googleapis.com/{dataset} 1130 "debugOptions": { # Describes any options that have an effect on the debugging of pipelines. # Any debugging options to be supplied to the job. 1131 "enableHotKeyLogging": True or False, # When true, enables the logging of the literal hot key to the user's Cloud Logging. 1132 }, 1133 "experiments": [ # The list of experiments to enable. This field should be used for SDK related experiments and not for service related experiments. The proper field for service related experiments is service_options. 1134 "A String", 1135 ], 1136 "flexResourceSchedulingGoal": "A String", # Which Flexible Resource Scheduling mode to run in. 1137 "internalExperiments": { # Experimental settings. 1138 "a_key": "", # Properties of the object. Contains field @type with type URL. 1139 }, 1140 "sdkPipelineOptions": { # The Cloud Dataflow SDK pipeline options specified by the user. These options are passed through the service and are used to recreate the SDK pipeline options on the worker in a language agnostic and platform independent way. 1141 "a_key": "", # Properties of the object. 1142 }, 1143 "serviceAccountEmail": "A String", # Identity to run virtual machines as. Defaults to the default account. 1144 "serviceKmsKeyName": "A String", # If set, contains the Cloud KMS key identifier used to encrypt data at rest, AKA a Customer Managed Encryption Key (CMEK). Format: projects/PROJECT_ID/locations/LOCATION/keyRings/KEY_RING/cryptoKeys/KEY 1145 "serviceOptions": [ # The list of service options to enable. This field should be used for service related experiments only. These experiments, when graduating to GA, should be replaced by dedicated fields or become default (i.e. always on). 1146 "A String", 1147 ], 1148 "shuffleMode": "A String", # Output only. The shuffle mode used for the job. 1149 "tempStoragePrefix": "A String", # The prefix of the resources the system should use for temporary storage. The system will append the suffix "/temp-{JOBNAME} to this resource prefix, where {JOBNAME} is the value of the job_name field. The resulting bucket and object prefix is used as the prefix of the resources used to store temporary data needed during the job execution. NOTE: This will override the value in taskrunner_settings. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object} 1150 "userAgent": { # A description of the process that generated the request. 1151 "a_key": "", # Properties of the object. 1152 }, 1153 "version": { # A structure describing which components and their versions of the service are required in order to run the job. 1154 "a_key": "", # Properties of the object. 1155 }, 1156 "workerPools": [ # The worker pools. At least one "harness" worker pool must be specified in order for the job to have workers. 1157 { # Describes one particular pool of Cloud Dataflow workers to be instantiated by the Cloud Dataflow service in order to perform the computations required by a job. Note that a workflow job may use multiple pools, in order to match the various computational requirements of the various stages of the job. 1158 "autoscalingSettings": { # Settings for WorkerPool autoscaling. # Settings for autoscaling of this WorkerPool. 1159 "algorithm": "A String", # The algorithm to use for autoscaling. 1160 "maxNumWorkers": 42, # The maximum number of workers to cap scaling at. 1161 }, 1162 "dataDisks": [ # Data disks that are used by a VM in this workflow. 1163 { # Describes the data disk used by a workflow job. 1164 "diskType": "A String", # Disk storage type, as defined by Google Compute Engine. This must be a disk type appropriate to the project and zone in which the workers will run. If unknown or unspecified, the service will attempt to choose a reasonable default. For example, the standard persistent disk type is a resource name typically ending in "pd-standard". If SSD persistent disks are available, the resource name typically ends with "pd-ssd". The actual valid values are defined the Google Compute Engine API, not by the Cloud Dataflow API; consult the Google Compute Engine documentation for more information about determining the set of available disk types for a particular project and zone. Google Compute Engine Disk types are local to a particular project in a particular zone, and so the resource name will typically look something like this: compute.googleapis.com/projects/project-id/zones/zone/diskTypes/pd-standard 1165 "mountPoint": "A String", # Directory in a VM where disk is mounted. 1166 "sizeGb": 42, # Size of disk in GB. If zero or unspecified, the service will attempt to choose a reasonable default. 1167 }, 1168 ], 1169 "defaultPackageSet": "A String", # The default package set to install. This allows the service to select a default set of packages which are useful to worker harnesses written in a particular language. 1170 "diskSizeGb": 42, # Size of root disk for VMs, in GB. If zero or unspecified, the service will attempt to choose a reasonable default. 1171 "diskSourceImage": "A String", # Fully qualified source image for disks. 1172 "diskType": "A String", # Type of root disk for VMs. If empty or unspecified, the service will attempt to choose a reasonable default. 1173 "ipConfiguration": "A String", # Configuration for VM IPs. 1174 "kind": "A String", # The kind of the worker pool; currently only `harness` and `shuffle` are supported. 1175 "machineType": "A String", # Machine type (e.g. "n1-standard-1"). If empty or unspecified, the service will attempt to choose a reasonable default. 1176 "metadata": { # Metadata to set on the Google Compute Engine VMs. 1177 "a_key": "A String", 1178 }, 1179 "network": "A String", # Network to which VMs will be assigned. If empty or unspecified, the service will use the network "default". 1180 "numThreadsPerWorker": 42, # The number of threads per worker harness. If empty or unspecified, the service will choose a number of threads (according to the number of cores on the selected machine type for batch, or 1 by convention for streaming). 1181 "numWorkers": 42, # Number of Google Compute Engine workers in this pool needed to execute the job. If zero or unspecified, the service will attempt to choose a reasonable default. 1182 "onHostMaintenance": "A String", # The action to take on host maintenance, as defined by the Google Compute Engine API. 1183 "packages": [ # Packages to be installed on workers. 1184 { # The packages that must be installed in order for a worker to run the steps of the Cloud Dataflow job that will be assigned to its worker pool. This is the mechanism by which the Cloud Dataflow SDK causes code to be loaded onto the workers. For example, the Cloud Dataflow Java SDK might use this to install jars containing the user's code and all of the various dependencies (libraries, data files, etc.) required in order for that code to run. 1185 "location": "A String", # The resource to read the package from. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket} bucket.storage.googleapis.com/ 1186 "name": "A String", # The name of the package. 1187 }, 1188 ], 1189 "poolArgs": { # Extra arguments for this worker pool. 1190 "a_key": "", # Properties of the object. Contains field @type with type URL. 1191 }, 1192 "sdkHarnessContainerImages": [ # Set of SDK harness containers needed to execute this pipeline. This will only be set in the Fn API path. For non-cross-language pipelines this should have only one entry. Cross-language pipelines will have two or more entries. 1193 { # Defines a SDK harness container for executing Dataflow pipelines. 1194 "containerImage": "A String", # A docker container image that resides in Google Container Registry. 1195 "environmentId": "A String", # Environment ID for the Beam runner API proto Environment that corresponds to the current SDK Harness. 1196 "useSingleCorePerContainer": True or False, # If true, recommends the Dataflow service to use only one core per SDK container instance with this image. If false (or unset) recommends using more than one core per SDK container instance with this image for efficiency. Note that Dataflow service may choose to override this property if needed. 1197 }, 1198 ], 1199 "subnetwork": "A String", # Subnetwork to which VMs will be assigned, if desired. Expected to be of the form "regions/REGION/subnetworks/SUBNETWORK". 1200 "taskrunnerSettings": { # Taskrunner configuration settings. # Settings passed through to Google Compute Engine workers when using the standard Dataflow task runner. Users should ignore this field. 1201 "alsologtostderr": True or False, # Whether to also send taskrunner log info to stderr. 1202 "baseTaskDir": "A String", # The location on the worker for task-specific subdirectories. 1203 "baseUrl": "A String", # The base URL for the taskrunner to use when accessing Google Cloud APIs. When workers access Google Cloud APIs, they logically do so via relative URLs. If this field is specified, it supplies the base URL to use for resolving these relative URLs. The normative algorithm used is defined by RFC 1808, "Relative Uniform Resource Locators". If not specified, the default value is "http://www.googleapis.com/" 1204 "commandlinesFileName": "A String", # The file to store preprocessing commands in. 1205 "continueOnException": True or False, # Whether to continue taskrunner if an exception is hit. 1206 "dataflowApiVersion": "A String", # The API version of endpoint, e.g. "v1b3" 1207 "harnessCommand": "A String", # The command to launch the worker harness. 1208 "languageHint": "A String", # The suggested backend language. 1209 "logDir": "A String", # The directory on the VM to store logs. 1210 "logToSerialconsole": True or False, # Whether to send taskrunner log info to Google Compute Engine VM serial console. 1211 "logUploadLocation": "A String", # Indicates where to put logs. If this is not specified, the logs will not be uploaded. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object} 1212 "oauthScopes": [ # The OAuth2 scopes to be requested by the taskrunner in order to access the Cloud Dataflow API. 1213 "A String", 1214 ], 1215 "parallelWorkerSettings": { # Provides data to pass through to the worker harness. # The settings to pass to the parallel worker harness. 1216 "baseUrl": "A String", # The base URL for accessing Google Cloud APIs. When workers access Google Cloud APIs, they logically do so via relative URLs. If this field is specified, it supplies the base URL to use for resolving these relative URLs. The normative algorithm used is defined by RFC 1808, "Relative Uniform Resource Locators". If not specified, the default value is "http://www.googleapis.com/" 1217 "reportingEnabled": True or False, # Whether to send work progress updates to the service. 1218 "servicePath": "A String", # The Cloud Dataflow service path relative to the root URL, for example, "dataflow/v1b3/projects". 1219 "shuffleServicePath": "A String", # The Shuffle service path relative to the root URL, for example, "shuffle/v1beta1". 1220 "tempStoragePrefix": "A String", # The prefix of the resources the system should use for temporary storage. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object} 1221 "workerId": "A String", # The ID of the worker running this pipeline. 1222 }, 1223 "streamingWorkerMainClass": "A String", # The streaming worker main class name. 1224 "taskGroup": "A String", # The UNIX group ID on the worker VM to use for tasks launched by taskrunner; e.g. "wheel". 1225 "taskUser": "A String", # The UNIX user ID on the worker VM to use for tasks launched by taskrunner; e.g. "root". 1226 "tempStoragePrefix": "A String", # The prefix of the resources the taskrunner should use for temporary storage. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object} 1227 "vmId": "A String", # The ID string of the VM. 1228 "workflowFileName": "A String", # The file to store the workflow in. 1229 }, 1230 "teardownPolicy": "A String", # Sets the policy for determining when to turndown worker pool. Allowed values are: `TEARDOWN_ALWAYS`, `TEARDOWN_ON_SUCCESS`, and `TEARDOWN_NEVER`. `TEARDOWN_ALWAYS` means workers are always torn down regardless of whether the job succeeds. `TEARDOWN_ON_SUCCESS` means workers are torn down if the job succeeds. `TEARDOWN_NEVER` means the workers are never torn down. If the workers are not torn down by the service, they will continue to run and use Google Compute Engine VM resources in the user's project until they are explicitly terminated by the user. Because of this, Google recommends using the `TEARDOWN_ALWAYS` policy except for small, manually supervised test jobs. If unknown or unspecified, the service will attempt to choose a reasonable default. 1231 "workerHarnessContainerImage": "A String", # Required. Docker container image that executes the Cloud Dataflow worker harness, residing in Google Container Registry. Deprecated for the Fn API path. Use sdk_harness_container_images instead. 1232 "zone": "A String", # Zone to run the worker pools in. If empty or unspecified, the service will attempt to choose a reasonable default. 1233 }, 1234 ], 1235 "workerRegion": "A String", # The Compute Engine region (https://cloud.google.com/compute/docs/regions-zones/regions-zones) in which worker processing should occur, e.g. "us-west1". Mutually exclusive with worker_zone. If neither worker_region nor worker_zone is specified, default to the control plane's region. 1236 "workerZone": "A String", # The Compute Engine zone (https://cloud.google.com/compute/docs/regions-zones/regions-zones) in which worker processing should occur, e.g. "us-west1-a". Mutually exclusive with worker_region. If neither worker_region nor worker_zone is specified, a zone in the control plane's region is chosen based on available capacity. 1237 }, 1238 "executionInfo": { # Additional information about how a Cloud Dataflow job will be executed that isn't contained in the submitted job. # Deprecated. 1239 "stages": { # A mapping from each stage to the information about that stage. 1240 "a_key": { # Contains information about how a particular google.dataflow.v1beta3.Step will be executed. 1241 "stepName": [ # The steps associated with the execution stage. Note that stages may have several steps, and that a given step might be run by more than one stage. 1242 "A String", 1243 ], 1244 }, 1245 }, 1246 }, 1247 "id": "A String", # The unique ID of this job. This field is set by the Cloud Dataflow service when the Job is created, and is immutable for the life of the job. 1248 "jobMetadata": { # Metadata available primarily for filtering jobs. Will be included in the ListJob response and Job SUMMARY view. # This field is populated by the Dataflow service to support filtering jobs by the metadata values provided here. Populated for ListJobs and all GetJob views SUMMARY and higher. 1249 "bigTableDetails": [ # Identification of a Cloud Bigtable source used in the Dataflow job. 1250 { # Metadata for a Cloud Bigtable connector used by the job. 1251 "instanceId": "A String", # InstanceId accessed in the connection. 1252 "projectId": "A String", # ProjectId accessed in the connection. 1253 "tableId": "A String", # TableId accessed in the connection. 1254 }, 1255 ], 1256 "bigqueryDetails": [ # Identification of a BigQuery source used in the Dataflow job. 1257 { # Metadata for a BigQuery connector used by the job. 1258 "dataset": "A String", # Dataset accessed in the connection. 1259 "projectId": "A String", # Project accessed in the connection. 1260 "query": "A String", # Query used to access data in the connection. 1261 "table": "A String", # Table accessed in the connection. 1262 }, 1263 ], 1264 "datastoreDetails": [ # Identification of a Datastore source used in the Dataflow job. 1265 { # Metadata for a Datastore connector used by the job. 1266 "namespace": "A String", # Namespace used in the connection. 1267 "projectId": "A String", # ProjectId accessed in the connection. 1268 }, 1269 ], 1270 "fileDetails": [ # Identification of a File source used in the Dataflow job. 1271 { # Metadata for a File connector used by the job. 1272 "filePattern": "A String", # File Pattern used to access files by the connector. 1273 }, 1274 ], 1275 "pubsubDetails": [ # Identification of a Pub/Sub source used in the Dataflow job. 1276 { # Metadata for a Pub/Sub connector used by the job. 1277 "subscription": "A String", # Subscription used in the connection. 1278 "topic": "A String", # Topic accessed in the connection. 1279 }, 1280 ], 1281 "sdkVersion": { # The version of the SDK used to run the job. # The SDK version used to run the job. 1282 "sdkSupportStatus": "A String", # The support status for this SDK version. 1283 "version": "A String", # The version of the SDK used to run the job. 1284 "versionDisplayName": "A String", # A readable string describing the version of the SDK. 1285 }, 1286 "spannerDetails": [ # Identification of a Spanner source used in the Dataflow job. 1287 { # Metadata for a Spanner connector used by the job. 1288 "databaseId": "A String", # DatabaseId accessed in the connection. 1289 "instanceId": "A String", # InstanceId accessed in the connection. 1290 "projectId": "A String", # ProjectId accessed in the connection. 1291 }, 1292 ], 1293 }, 1294 "labels": { # User-defined labels for this job. The labels map can contain no more than 64 entries. Entries of the labels map are UTF8 strings that comply with the following restrictions: * Keys must conform to regexp: \p{Ll}\p{Lo}{0,62} * Values must conform to regexp: [\p{Ll}\p{Lo}\p{N}_-]{0,63} * Both keys and values are additionally constrained to be <= 128 bytes in size. 1295 "a_key": "A String", 1296 }, 1297 "location": "A String", # The [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints) that contains this job. 1298 "name": "A String", # The user-specified Cloud Dataflow job name. Only one Job with a given name may exist in a project at any given time. If a caller attempts to create a Job with the same name as an already-existing Job, the attempt returns the existing Job. The name must match the regular expression `[a-z]([-a-z0-9]{0,38}[a-z0-9])?` 1299 "pipelineDescription": { # A descriptive representation of submitted pipeline as well as the executed form. This data is provided by the Dataflow service for ease of visualizing the pipeline and interpreting Dataflow provided metrics. # Preliminary field: The format of this data may change at any time. A description of the user pipeline and stages through which it is executed. Created by Cloud Dataflow service. Only retrieved with JOB_VIEW_DESCRIPTION or JOB_VIEW_ALL. 1300 "displayData": [ # Pipeline level display data. 1301 { # Data provided with a pipeline or transform to provide descriptive info. 1302 "boolValue": True or False, # Contains value if the data is of a boolean type. 1303 "durationValue": "A String", # Contains value if the data is of duration type. 1304 "floatValue": 3.14, # Contains value if the data is of float type. 1305 "int64Value": "A String", # Contains value if the data is of int64 type. 1306 "javaClassValue": "A String", # Contains value if the data is of java class type. 1307 "key": "A String", # The key identifying the display data. This is intended to be used as a label for the display data when viewed in a dax monitoring system. 1308 "label": "A String", # An optional label to display in a dax UI for the element. 1309 "namespace": "A String", # The namespace for the key. This is usually a class name or programming language namespace (i.e. python module) which defines the display data. This allows a dax monitoring system to specially handle the data and perform custom rendering. 1310 "shortStrValue": "A String", # A possible additional shorter value to display. For example a java_class_name_value of com.mypackage.MyDoFn will be stored with MyDoFn as the short_str_value and com.mypackage.MyDoFn as the java_class_name value. short_str_value can be displayed and java_class_name_value will be displayed as a tooltip. 1311 "strValue": "A String", # Contains value if the data is of string type. 1312 "timestampValue": "A String", # Contains value if the data is of timestamp type. 1313 "url": "A String", # An optional full URL. 1314 }, 1315 ], 1316 "executionPipelineStage": [ # Description of each stage of execution of the pipeline. 1317 { # Description of the composing transforms, names/ids, and input/outputs of a stage of execution. Some composing transforms and sources may have been generated by the Dataflow service during execution planning. 1318 "componentSource": [ # Collections produced and consumed by component transforms of this stage. 1319 { # Description of an interstitial value between transforms in an execution stage. 1320 "name": "A String", # Dataflow service generated name for this source. 1321 "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated. 1322 "userName": "A String", # Human-readable name for this transform; may be user or system generated. 1323 }, 1324 ], 1325 "componentTransform": [ # Transforms that comprise this execution stage. 1326 { # Description of a transform executed as part of an execution stage. 1327 "name": "A String", # Dataflow service generated name for this source. 1328 "originalTransform": "A String", # User name for the original user transform with which this transform is most closely associated. 1329 "userName": "A String", # Human-readable name for this transform; may be user or system generated. 1330 }, 1331 ], 1332 "id": "A String", # Dataflow service generated id for this stage. 1333 "inputSource": [ # Input sources for this stage. 1334 { # Description of an input or output of an execution stage. 1335 "name": "A String", # Dataflow service generated name for this source. 1336 "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated. 1337 "sizeBytes": "A String", # Size of the source, if measurable. 1338 "userName": "A String", # Human-readable name for this source; may be user or system generated. 1339 }, 1340 ], 1341 "kind": "A String", # Type of transform this stage is executing. 1342 "name": "A String", # Dataflow service generated name for this stage. 1343 "outputSource": [ # Output sources for this stage. 1344 { # Description of an input or output of an execution stage. 1345 "name": "A String", # Dataflow service generated name for this source. 1346 "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated. 1347 "sizeBytes": "A String", # Size of the source, if measurable. 1348 "userName": "A String", # Human-readable name for this source; may be user or system generated. 1349 }, 1350 ], 1351 "prerequisiteStage": [ # Other stages that must complete before this stage can run. 1352 "A String", 1353 ], 1354 }, 1355 ], 1356 "originalPipelineTransform": [ # Description of each transform in the pipeline and collections between them. 1357 { # Description of the type, names/ids, and input/outputs for a transform. 1358 "displayData": [ # Transform-specific display data. 1359 { # Data provided with a pipeline or transform to provide descriptive info. 1360 "boolValue": True or False, # Contains value if the data is of a boolean type. 1361 "durationValue": "A String", # Contains value if the data is of duration type. 1362 "floatValue": 3.14, # Contains value if the data is of float type. 1363 "int64Value": "A String", # Contains value if the data is of int64 type. 1364 "javaClassValue": "A String", # Contains value if the data is of java class type. 1365 "key": "A String", # The key identifying the display data. This is intended to be used as a label for the display data when viewed in a dax monitoring system. 1366 "label": "A String", # An optional label to display in a dax UI for the element. 1367 "namespace": "A String", # The namespace for the key. This is usually a class name or programming language namespace (i.e. python module) which defines the display data. This allows a dax monitoring system to specially handle the data and perform custom rendering. 1368 "shortStrValue": "A String", # A possible additional shorter value to display. For example a java_class_name_value of com.mypackage.MyDoFn will be stored with MyDoFn as the short_str_value and com.mypackage.MyDoFn as the java_class_name value. short_str_value can be displayed and java_class_name_value will be displayed as a tooltip. 1369 "strValue": "A String", # Contains value if the data is of string type. 1370 "timestampValue": "A String", # Contains value if the data is of timestamp type. 1371 "url": "A String", # An optional full URL. 1372 }, 1373 ], 1374 "id": "A String", # SDK generated id of this transform instance. 1375 "inputCollectionName": [ # User names for all collection inputs to this transform. 1376 "A String", 1377 ], 1378 "kind": "A String", # Type of transform. 1379 "name": "A String", # User provided name for this transform instance. 1380 "outputCollectionName": [ # User names for all collection outputs to this transform. 1381 "A String", 1382 ], 1383 }, 1384 ], 1385 }, 1386 "projectId": "A String", # The ID of the Cloud Platform project that the job belongs to. 1387 "replaceJobId": "A String", # If this job is an update of an existing job, this field is the job ID of the job it replaced. When sending a `CreateJobRequest`, you can update a job by specifying it here. The job named here is stopped, and its intermediate state is transferred to this job. 1388 "replacedByJobId": "A String", # If another job is an update of this job (and thus, this job is in `JOB_STATE_UPDATED`), this field contains the ID of that job. 1389 "requestedState": "A String", # The job's requested state. `UpdateJob` may be used to switch between the `JOB_STATE_STOPPED` and `JOB_STATE_RUNNING` states, by setting requested_state. `UpdateJob` may also be used to directly set a job's requested state to `JOB_STATE_CANCELLED` or `JOB_STATE_DONE`, irrevocably terminating the job if it has not already reached a terminal state. 1390 "satisfiesPzs": True or False, # Reserved for future use. This field is set only in responses from the server; it is ignored if it is set in any requests. 1391 "stageStates": [ # This field may be mutated by the Cloud Dataflow service; callers cannot mutate it. 1392 { # A message describing the state of a particular execution stage. 1393 "currentStateTime": "A String", # The time at which the stage transitioned to this state. 1394 "executionStageName": "A String", # The name of the execution stage. 1395 "executionStageState": "A String", # Executions stage states allow the same set of values as JobState. 1396 }, 1397 ], 1398 "startTime": "A String", # The timestamp when the job was started (transitioned to JOB_STATE_PENDING). Flexible resource scheduling jobs are started with some delay after job creation, so start_time is unset before start and is updated when the job is started by the Cloud Dataflow service. For other jobs, start_time always equals to create_time and is immutable and set by the Cloud Dataflow service. 1399 "steps": [ # Exactly one of step or steps_location should be specified. The top-level steps that constitute the entire job. Only retrieved with JOB_VIEW_ALL. 1400 { # Defines a particular step within a Cloud Dataflow job. A job consists of multiple steps, each of which performs some specific operation as part of the overall job. Data is typically passed from one step to another as part of the job. Here's an example of a sequence of steps which together implement a Map-Reduce job: * Read a collection of data from some source, parsing the collection's elements. * Validate the elements. * Apply a user-defined function to map each element to some value and extract an element-specific key value. * Group elements with the same key into a single element with that key, transforming a multiply-keyed collection into a uniquely-keyed collection. * Write the elements out to some data sink. Note that the Cloud Dataflow service may be used to run many different types of jobs, not just Map-Reduce. 1401 "kind": "A String", # The kind of step in the Cloud Dataflow job. 1402 "name": "A String", # The name that identifies the step. This must be unique for each step with respect to all other steps in the Cloud Dataflow job. 1403 "properties": { # Named properties associated with the step. Each kind of predefined step has its own required set of properties. Must be provided on Create. Only retrieved with JOB_VIEW_ALL. 1404 "a_key": "", # Properties of the object. 1405 }, 1406 }, 1407 ], 1408 "stepsLocation": "A String", # The Cloud Storage location where the steps are stored. 1409 "tempFiles": [ # A set of files the system should be aware of that are used for temporary storage. These temporary files will be removed on job completion. No duplicates are allowed. No file patterns are supported. The supported files are: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object} 1410 "A String", 1411 ], 1412 "transformNameMapping": { # The map of transform name prefixes of the job to be replaced to the corresponding name prefixes of the new job. 1413 "a_key": "A String", 1414 }, 1415 "type": "A String", # The type of Cloud Dataflow job. 1416}</pre> 1417</div> 1418 1419<div class="method"> 1420 <code class="details" id="getMetrics">getMetrics(projectId, jobId, location=None, startTime=None, x__xgafv=None)</code> 1421 <pre>Request the job status. To request the status of a job, we recommend using `projects.locations.jobs.getMetrics` with a [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints). Using `projects.jobs.getMetrics` is not recommended, as you can only request the status of jobs that are running in `us-central1`. 1422 1423Args: 1424 projectId: string, A project id. (required) 1425 jobId: string, The job to get metrics for. (required) 1426 location: string, The [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints) that contains the job specified by job_id. 1427 startTime: string, Return only metric data that has changed since this time. Default is to return all information about all metrics for the job. 1428 x__xgafv: string, V1 error format. 1429 Allowed values 1430 1 - v1 error format 1431 2 - v2 error format 1432 1433Returns: 1434 An object of the form: 1435 1436 { # JobMetrics contains a collection of metrics describing the detailed progress of a Dataflow job. Metrics correspond to user-defined and system-defined metrics in the job. This resource captures only the most recent values of each metric; time-series data can be queried for them (under the same metric names) from Cloud Monitoring. 1437 "metricTime": "A String", # Timestamp as of which metric values are current. 1438 "metrics": [ # All metrics for this job. 1439 { # Describes the state of a metric. 1440 "cumulative": True or False, # True if this metric is reported as the total cumulative aggregate value accumulated since the worker started working on this WorkItem. By default this is false, indicating that this metric is reported as a delta that is not associated with any WorkItem. 1441 "distribution": "", # A struct value describing properties of a distribution of numeric values. 1442 "gauge": "", # A struct value describing properties of a Gauge. Metrics of gauge type show the value of a metric across time, and is aggregated based on the newest value. 1443 "internal": "", # Worker-computed aggregate value for internal use by the Dataflow service. 1444 "kind": "A String", # Metric aggregation kind. The possible metric aggregation kinds are "Sum", "Max", "Min", "Mean", "Set", "And", "Or", and "Distribution". The specified aggregation kind is case-insensitive. If omitted, this is not an aggregated value but instead a single metric sample value. 1445 "meanCount": "", # Worker-computed aggregate value for the "Mean" aggregation kind. This holds the count of the aggregated values and is used in combination with mean_sum above to obtain the actual mean aggregate value. The only possible value type is Long. 1446 "meanSum": "", # Worker-computed aggregate value for the "Mean" aggregation kind. This holds the sum of the aggregated values and is used in combination with mean_count below to obtain the actual mean aggregate value. The only possible value types are Long and Double. 1447 "name": { # Identifies a metric, by describing the source which generated the metric. # Name of the metric. 1448 "context": { # Zero or more labeled fields which identify the part of the job this metric is associated with, such as the name of a step or collection. For example, built-in counters associated with steps will have context['step'] = . Counters associated with PCollections in the SDK will have context['pcollection'] = . 1449 "a_key": "A String", 1450 }, 1451 "name": "A String", # Worker-defined metric name. 1452 "origin": "A String", # Origin (namespace) of metric name. May be blank for user-define metrics; will be "dataflow" for metrics defined by the Dataflow service or SDK. 1453 }, 1454 "scalar": "", # Worker-computed aggregate value for aggregation kinds "Sum", "Max", "Min", "And", and "Or". The possible value types are Long, Double, and Boolean. 1455 "set": "", # Worker-computed aggregate value for the "Set" aggregation kind. The only possible value type is a list of Values whose type can be Long, Double, or String, according to the metric's type. All Values in the list must be of the same type. 1456 "updateTime": "A String", # Timestamp associated with the metric value. Optional when workers are reporting work progress; it will be filled in responses from the metrics API. 1457 }, 1458 ], 1459}</pre> 1460</div> 1461 1462<div class="method"> 1463 <code class="details" id="list">list(projectId, filter=None, location=None, pageSize=None, pageToken=None, view=None, x__xgafv=None)</code> 1464 <pre>List the jobs of a project. To list the jobs of a project in a region, we recommend using `projects.locations.jobs.list` with a [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints). To list the all jobs across all regions, use `projects.jobs.aggregated`. Using `projects.jobs.list` is not recommended, as you can only get the list of jobs that are running in `us-central1`. 1465 1466Args: 1467 projectId: string, The project which owns the jobs. (required) 1468 filter: string, The kind of filter to use. 1469 Allowed values 1470 UNKNOWN - The filter isn't specified, or is unknown. This returns all jobs ordered on descending `JobUuid`. 1471 ALL - Returns all running jobs first ordered on creation timestamp, then returns all terminated jobs ordered on the termination timestamp. 1472 TERMINATED - Filters the jobs that have a terminated state, ordered on the termination timestamp. Example terminated states: `JOB_STATE_STOPPED`, `JOB_STATE_UPDATED`, `JOB_STATE_DRAINED`, etc. 1473 ACTIVE - Filters the jobs that are running ordered on the creation timestamp. 1474 location: string, The [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints) that contains this job. 1475 pageSize: integer, If there are many jobs, limit response to at most this many. The actual number of jobs returned will be the lesser of max_responses and an unspecified server-defined limit. 1476 pageToken: string, Set this to the 'next_page_token' field of a previous response to request additional results in a long list. 1477 view: string, Deprecated. ListJobs always returns summaries now. Use GetJob for other JobViews. 1478 Allowed values 1479 JOB_VIEW_UNKNOWN - The job view to return isn't specified, or is unknown. Responses will contain at least the `JOB_VIEW_SUMMARY` information, and may contain additional information. 1480 JOB_VIEW_SUMMARY - Request summary information only: Project ID, Job ID, job name, job type, job status, start/end time, and Cloud SDK version details. 1481 JOB_VIEW_ALL - Request all information available for this job. 1482 JOB_VIEW_DESCRIPTION - Request summary info and limited job description data for steps, labels and environment. 1483 x__xgafv: string, V1 error format. 1484 Allowed values 1485 1 - v1 error format 1486 2 - v2 error format 1487 1488Returns: 1489 An object of the form: 1490 1491 { # Response to a request to list Cloud Dataflow jobs in a project. This might be a partial response, depending on the page size in the ListJobsRequest. However, if the project does not have any jobs, an instance of ListJobsResponse is not returned and the requests's response body is empty {}. 1492 "failedLocation": [ # Zero or more messages describing the [regional endpoints] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints) that failed to respond. 1493 { # Indicates which [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints) failed to respond to a request for data. 1494 "name": "A String", # The name of the [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints) that failed to respond. 1495 }, 1496 ], 1497 "jobs": [ # A subset of the requested job information. 1498 { # Defines a job to be run by the Cloud Dataflow service. nextID: 26 1499 "clientRequestId": "A String", # The client's unique identifier of the job, re-used across retried attempts. If this field is set, the service will ensure its uniqueness. The request to create a job will fail if the service has knowledge of a previously submitted job with the same client's ID and job name. The caller may use this field to ensure idempotence of job creation across retried attempts to create a job. By default, the field is empty and, in that case, the service ignores it. 1500 "createTime": "A String", # The timestamp when the job was initially created. Immutable and set by the Cloud Dataflow service. 1501 "createdFromSnapshotId": "A String", # If this is specified, the job's initial state is populated from the given snapshot. 1502 "currentState": "A String", # The current state of the job. Jobs are created in the `JOB_STATE_STOPPED` state unless otherwise specified. A job in the `JOB_STATE_RUNNING` state may asynchronously enter a terminal state. After a job has reached a terminal state, no further state updates may be made. This field may be mutated by the Cloud Dataflow service; callers cannot mutate it. 1503 "currentStateTime": "A String", # The timestamp associated with the current state. 1504 "environment": { # Describes the environment in which a Dataflow Job runs. # The environment for the job. 1505 "clusterManagerApiService": "A String", # The type of cluster manager API to use. If unknown or unspecified, the service will attempt to choose a reasonable default. This should be in the form of the API service name, e.g. "compute.googleapis.com". 1506 "dataset": "A String", # The dataset for the current project where various workflow related tables are stored. The supported resource type is: Google BigQuery: bigquery.googleapis.com/{dataset} 1507 "debugOptions": { # Describes any options that have an effect on the debugging of pipelines. # Any debugging options to be supplied to the job. 1508 "enableHotKeyLogging": True or False, # When true, enables the logging of the literal hot key to the user's Cloud Logging. 1509 }, 1510 "experiments": [ # The list of experiments to enable. This field should be used for SDK related experiments and not for service related experiments. The proper field for service related experiments is service_options. 1511 "A String", 1512 ], 1513 "flexResourceSchedulingGoal": "A String", # Which Flexible Resource Scheduling mode to run in. 1514 "internalExperiments": { # Experimental settings. 1515 "a_key": "", # Properties of the object. Contains field @type with type URL. 1516 }, 1517 "sdkPipelineOptions": { # The Cloud Dataflow SDK pipeline options specified by the user. These options are passed through the service and are used to recreate the SDK pipeline options on the worker in a language agnostic and platform independent way. 1518 "a_key": "", # Properties of the object. 1519 }, 1520 "serviceAccountEmail": "A String", # Identity to run virtual machines as. Defaults to the default account. 1521 "serviceKmsKeyName": "A String", # If set, contains the Cloud KMS key identifier used to encrypt data at rest, AKA a Customer Managed Encryption Key (CMEK). Format: projects/PROJECT_ID/locations/LOCATION/keyRings/KEY_RING/cryptoKeys/KEY 1522 "serviceOptions": [ # The list of service options to enable. This field should be used for service related experiments only. These experiments, when graduating to GA, should be replaced by dedicated fields or become default (i.e. always on). 1523 "A String", 1524 ], 1525 "shuffleMode": "A String", # Output only. The shuffle mode used for the job. 1526 "tempStoragePrefix": "A String", # The prefix of the resources the system should use for temporary storage. The system will append the suffix "/temp-{JOBNAME} to this resource prefix, where {JOBNAME} is the value of the job_name field. The resulting bucket and object prefix is used as the prefix of the resources used to store temporary data needed during the job execution. NOTE: This will override the value in taskrunner_settings. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object} 1527 "userAgent": { # A description of the process that generated the request. 1528 "a_key": "", # Properties of the object. 1529 }, 1530 "version": { # A structure describing which components and their versions of the service are required in order to run the job. 1531 "a_key": "", # Properties of the object. 1532 }, 1533 "workerPools": [ # The worker pools. At least one "harness" worker pool must be specified in order for the job to have workers. 1534 { # Describes one particular pool of Cloud Dataflow workers to be instantiated by the Cloud Dataflow service in order to perform the computations required by a job. Note that a workflow job may use multiple pools, in order to match the various computational requirements of the various stages of the job. 1535 "autoscalingSettings": { # Settings for WorkerPool autoscaling. # Settings for autoscaling of this WorkerPool. 1536 "algorithm": "A String", # The algorithm to use for autoscaling. 1537 "maxNumWorkers": 42, # The maximum number of workers to cap scaling at. 1538 }, 1539 "dataDisks": [ # Data disks that are used by a VM in this workflow. 1540 { # Describes the data disk used by a workflow job. 1541 "diskType": "A String", # Disk storage type, as defined by Google Compute Engine. This must be a disk type appropriate to the project and zone in which the workers will run. If unknown or unspecified, the service will attempt to choose a reasonable default. For example, the standard persistent disk type is a resource name typically ending in "pd-standard". If SSD persistent disks are available, the resource name typically ends with "pd-ssd". The actual valid values are defined the Google Compute Engine API, not by the Cloud Dataflow API; consult the Google Compute Engine documentation for more information about determining the set of available disk types for a particular project and zone. Google Compute Engine Disk types are local to a particular project in a particular zone, and so the resource name will typically look something like this: compute.googleapis.com/projects/project-id/zones/zone/diskTypes/pd-standard 1542 "mountPoint": "A String", # Directory in a VM where disk is mounted. 1543 "sizeGb": 42, # Size of disk in GB. If zero or unspecified, the service will attempt to choose a reasonable default. 1544 }, 1545 ], 1546 "defaultPackageSet": "A String", # The default package set to install. This allows the service to select a default set of packages which are useful to worker harnesses written in a particular language. 1547 "diskSizeGb": 42, # Size of root disk for VMs, in GB. If zero or unspecified, the service will attempt to choose a reasonable default. 1548 "diskSourceImage": "A String", # Fully qualified source image for disks. 1549 "diskType": "A String", # Type of root disk for VMs. If empty or unspecified, the service will attempt to choose a reasonable default. 1550 "ipConfiguration": "A String", # Configuration for VM IPs. 1551 "kind": "A String", # The kind of the worker pool; currently only `harness` and `shuffle` are supported. 1552 "machineType": "A String", # Machine type (e.g. "n1-standard-1"). If empty or unspecified, the service will attempt to choose a reasonable default. 1553 "metadata": { # Metadata to set on the Google Compute Engine VMs. 1554 "a_key": "A String", 1555 }, 1556 "network": "A String", # Network to which VMs will be assigned. If empty or unspecified, the service will use the network "default". 1557 "numThreadsPerWorker": 42, # The number of threads per worker harness. If empty or unspecified, the service will choose a number of threads (according to the number of cores on the selected machine type for batch, or 1 by convention for streaming). 1558 "numWorkers": 42, # Number of Google Compute Engine workers in this pool needed to execute the job. If zero or unspecified, the service will attempt to choose a reasonable default. 1559 "onHostMaintenance": "A String", # The action to take on host maintenance, as defined by the Google Compute Engine API. 1560 "packages": [ # Packages to be installed on workers. 1561 { # The packages that must be installed in order for a worker to run the steps of the Cloud Dataflow job that will be assigned to its worker pool. This is the mechanism by which the Cloud Dataflow SDK causes code to be loaded onto the workers. For example, the Cloud Dataflow Java SDK might use this to install jars containing the user's code and all of the various dependencies (libraries, data files, etc.) required in order for that code to run. 1562 "location": "A String", # The resource to read the package from. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket} bucket.storage.googleapis.com/ 1563 "name": "A String", # The name of the package. 1564 }, 1565 ], 1566 "poolArgs": { # Extra arguments for this worker pool. 1567 "a_key": "", # Properties of the object. Contains field @type with type URL. 1568 }, 1569 "sdkHarnessContainerImages": [ # Set of SDK harness containers needed to execute this pipeline. This will only be set in the Fn API path. For non-cross-language pipelines this should have only one entry. Cross-language pipelines will have two or more entries. 1570 { # Defines a SDK harness container for executing Dataflow pipelines. 1571 "containerImage": "A String", # A docker container image that resides in Google Container Registry. 1572 "environmentId": "A String", # Environment ID for the Beam runner API proto Environment that corresponds to the current SDK Harness. 1573 "useSingleCorePerContainer": True or False, # If true, recommends the Dataflow service to use only one core per SDK container instance with this image. If false (or unset) recommends using more than one core per SDK container instance with this image for efficiency. Note that Dataflow service may choose to override this property if needed. 1574 }, 1575 ], 1576 "subnetwork": "A String", # Subnetwork to which VMs will be assigned, if desired. Expected to be of the form "regions/REGION/subnetworks/SUBNETWORK". 1577 "taskrunnerSettings": { # Taskrunner configuration settings. # Settings passed through to Google Compute Engine workers when using the standard Dataflow task runner. Users should ignore this field. 1578 "alsologtostderr": True or False, # Whether to also send taskrunner log info to stderr. 1579 "baseTaskDir": "A String", # The location on the worker for task-specific subdirectories. 1580 "baseUrl": "A String", # The base URL for the taskrunner to use when accessing Google Cloud APIs. When workers access Google Cloud APIs, they logically do so via relative URLs. If this field is specified, it supplies the base URL to use for resolving these relative URLs. The normative algorithm used is defined by RFC 1808, "Relative Uniform Resource Locators". If not specified, the default value is "http://www.googleapis.com/" 1581 "commandlinesFileName": "A String", # The file to store preprocessing commands in. 1582 "continueOnException": True or False, # Whether to continue taskrunner if an exception is hit. 1583 "dataflowApiVersion": "A String", # The API version of endpoint, e.g. "v1b3" 1584 "harnessCommand": "A String", # The command to launch the worker harness. 1585 "languageHint": "A String", # The suggested backend language. 1586 "logDir": "A String", # The directory on the VM to store logs. 1587 "logToSerialconsole": True or False, # Whether to send taskrunner log info to Google Compute Engine VM serial console. 1588 "logUploadLocation": "A String", # Indicates where to put logs. If this is not specified, the logs will not be uploaded. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object} 1589 "oauthScopes": [ # The OAuth2 scopes to be requested by the taskrunner in order to access the Cloud Dataflow API. 1590 "A String", 1591 ], 1592 "parallelWorkerSettings": { # Provides data to pass through to the worker harness. # The settings to pass to the parallel worker harness. 1593 "baseUrl": "A String", # The base URL for accessing Google Cloud APIs. When workers access Google Cloud APIs, they logically do so via relative URLs. If this field is specified, it supplies the base URL to use for resolving these relative URLs. The normative algorithm used is defined by RFC 1808, "Relative Uniform Resource Locators". If not specified, the default value is "http://www.googleapis.com/" 1594 "reportingEnabled": True or False, # Whether to send work progress updates to the service. 1595 "servicePath": "A String", # The Cloud Dataflow service path relative to the root URL, for example, "dataflow/v1b3/projects". 1596 "shuffleServicePath": "A String", # The Shuffle service path relative to the root URL, for example, "shuffle/v1beta1". 1597 "tempStoragePrefix": "A String", # The prefix of the resources the system should use for temporary storage. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object} 1598 "workerId": "A String", # The ID of the worker running this pipeline. 1599 }, 1600 "streamingWorkerMainClass": "A String", # The streaming worker main class name. 1601 "taskGroup": "A String", # The UNIX group ID on the worker VM to use for tasks launched by taskrunner; e.g. "wheel". 1602 "taskUser": "A String", # The UNIX user ID on the worker VM to use for tasks launched by taskrunner; e.g. "root". 1603 "tempStoragePrefix": "A String", # The prefix of the resources the taskrunner should use for temporary storage. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object} 1604 "vmId": "A String", # The ID string of the VM. 1605 "workflowFileName": "A String", # The file to store the workflow in. 1606 }, 1607 "teardownPolicy": "A String", # Sets the policy for determining when to turndown worker pool. Allowed values are: `TEARDOWN_ALWAYS`, `TEARDOWN_ON_SUCCESS`, and `TEARDOWN_NEVER`. `TEARDOWN_ALWAYS` means workers are always torn down regardless of whether the job succeeds. `TEARDOWN_ON_SUCCESS` means workers are torn down if the job succeeds. `TEARDOWN_NEVER` means the workers are never torn down. If the workers are not torn down by the service, they will continue to run and use Google Compute Engine VM resources in the user's project until they are explicitly terminated by the user. Because of this, Google recommends using the `TEARDOWN_ALWAYS` policy except for small, manually supervised test jobs. If unknown or unspecified, the service will attempt to choose a reasonable default. 1608 "workerHarnessContainerImage": "A String", # Required. Docker container image that executes the Cloud Dataflow worker harness, residing in Google Container Registry. Deprecated for the Fn API path. Use sdk_harness_container_images instead. 1609 "zone": "A String", # Zone to run the worker pools in. If empty or unspecified, the service will attempt to choose a reasonable default. 1610 }, 1611 ], 1612 "workerRegion": "A String", # The Compute Engine region (https://cloud.google.com/compute/docs/regions-zones/regions-zones) in which worker processing should occur, e.g. "us-west1". Mutually exclusive with worker_zone. If neither worker_region nor worker_zone is specified, default to the control plane's region. 1613 "workerZone": "A String", # The Compute Engine zone (https://cloud.google.com/compute/docs/regions-zones/regions-zones) in which worker processing should occur, e.g. "us-west1-a". Mutually exclusive with worker_region. If neither worker_region nor worker_zone is specified, a zone in the control plane's region is chosen based on available capacity. 1614 }, 1615 "executionInfo": { # Additional information about how a Cloud Dataflow job will be executed that isn't contained in the submitted job. # Deprecated. 1616 "stages": { # A mapping from each stage to the information about that stage. 1617 "a_key": { # Contains information about how a particular google.dataflow.v1beta3.Step will be executed. 1618 "stepName": [ # The steps associated with the execution stage. Note that stages may have several steps, and that a given step might be run by more than one stage. 1619 "A String", 1620 ], 1621 }, 1622 }, 1623 }, 1624 "id": "A String", # The unique ID of this job. This field is set by the Cloud Dataflow service when the Job is created, and is immutable for the life of the job. 1625 "jobMetadata": { # Metadata available primarily for filtering jobs. Will be included in the ListJob response and Job SUMMARY view. # This field is populated by the Dataflow service to support filtering jobs by the metadata values provided here. Populated for ListJobs and all GetJob views SUMMARY and higher. 1626 "bigTableDetails": [ # Identification of a Cloud Bigtable source used in the Dataflow job. 1627 { # Metadata for a Cloud Bigtable connector used by the job. 1628 "instanceId": "A String", # InstanceId accessed in the connection. 1629 "projectId": "A String", # ProjectId accessed in the connection. 1630 "tableId": "A String", # TableId accessed in the connection. 1631 }, 1632 ], 1633 "bigqueryDetails": [ # Identification of a BigQuery source used in the Dataflow job. 1634 { # Metadata for a BigQuery connector used by the job. 1635 "dataset": "A String", # Dataset accessed in the connection. 1636 "projectId": "A String", # Project accessed in the connection. 1637 "query": "A String", # Query used to access data in the connection. 1638 "table": "A String", # Table accessed in the connection. 1639 }, 1640 ], 1641 "datastoreDetails": [ # Identification of a Datastore source used in the Dataflow job. 1642 { # Metadata for a Datastore connector used by the job. 1643 "namespace": "A String", # Namespace used in the connection. 1644 "projectId": "A String", # ProjectId accessed in the connection. 1645 }, 1646 ], 1647 "fileDetails": [ # Identification of a File source used in the Dataflow job. 1648 { # Metadata for a File connector used by the job. 1649 "filePattern": "A String", # File Pattern used to access files by the connector. 1650 }, 1651 ], 1652 "pubsubDetails": [ # Identification of a Pub/Sub source used in the Dataflow job. 1653 { # Metadata for a Pub/Sub connector used by the job. 1654 "subscription": "A String", # Subscription used in the connection. 1655 "topic": "A String", # Topic accessed in the connection. 1656 }, 1657 ], 1658 "sdkVersion": { # The version of the SDK used to run the job. # The SDK version used to run the job. 1659 "sdkSupportStatus": "A String", # The support status for this SDK version. 1660 "version": "A String", # The version of the SDK used to run the job. 1661 "versionDisplayName": "A String", # A readable string describing the version of the SDK. 1662 }, 1663 "spannerDetails": [ # Identification of a Spanner source used in the Dataflow job. 1664 { # Metadata for a Spanner connector used by the job. 1665 "databaseId": "A String", # DatabaseId accessed in the connection. 1666 "instanceId": "A String", # InstanceId accessed in the connection. 1667 "projectId": "A String", # ProjectId accessed in the connection. 1668 }, 1669 ], 1670 }, 1671 "labels": { # User-defined labels for this job. The labels map can contain no more than 64 entries. Entries of the labels map are UTF8 strings that comply with the following restrictions: * Keys must conform to regexp: \p{Ll}\p{Lo}{0,62} * Values must conform to regexp: [\p{Ll}\p{Lo}\p{N}_-]{0,63} * Both keys and values are additionally constrained to be <= 128 bytes in size. 1672 "a_key": "A String", 1673 }, 1674 "location": "A String", # The [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints) that contains this job. 1675 "name": "A String", # The user-specified Cloud Dataflow job name. Only one Job with a given name may exist in a project at any given time. If a caller attempts to create a Job with the same name as an already-existing Job, the attempt returns the existing Job. The name must match the regular expression `[a-z]([-a-z0-9]{0,38}[a-z0-9])?` 1676 "pipelineDescription": { # A descriptive representation of submitted pipeline as well as the executed form. This data is provided by the Dataflow service for ease of visualizing the pipeline and interpreting Dataflow provided metrics. # Preliminary field: The format of this data may change at any time. A description of the user pipeline and stages through which it is executed. Created by Cloud Dataflow service. Only retrieved with JOB_VIEW_DESCRIPTION or JOB_VIEW_ALL. 1677 "displayData": [ # Pipeline level display data. 1678 { # Data provided with a pipeline or transform to provide descriptive info. 1679 "boolValue": True or False, # Contains value if the data is of a boolean type. 1680 "durationValue": "A String", # Contains value if the data is of duration type. 1681 "floatValue": 3.14, # Contains value if the data is of float type. 1682 "int64Value": "A String", # Contains value if the data is of int64 type. 1683 "javaClassValue": "A String", # Contains value if the data is of java class type. 1684 "key": "A String", # The key identifying the display data. This is intended to be used as a label for the display data when viewed in a dax monitoring system. 1685 "label": "A String", # An optional label to display in a dax UI for the element. 1686 "namespace": "A String", # The namespace for the key. This is usually a class name or programming language namespace (i.e. python module) which defines the display data. This allows a dax monitoring system to specially handle the data and perform custom rendering. 1687 "shortStrValue": "A String", # A possible additional shorter value to display. For example a java_class_name_value of com.mypackage.MyDoFn will be stored with MyDoFn as the short_str_value and com.mypackage.MyDoFn as the java_class_name value. short_str_value can be displayed and java_class_name_value will be displayed as a tooltip. 1688 "strValue": "A String", # Contains value if the data is of string type. 1689 "timestampValue": "A String", # Contains value if the data is of timestamp type. 1690 "url": "A String", # An optional full URL. 1691 }, 1692 ], 1693 "executionPipelineStage": [ # Description of each stage of execution of the pipeline. 1694 { # Description of the composing transforms, names/ids, and input/outputs of a stage of execution. Some composing transforms and sources may have been generated by the Dataflow service during execution planning. 1695 "componentSource": [ # Collections produced and consumed by component transforms of this stage. 1696 { # Description of an interstitial value between transforms in an execution stage. 1697 "name": "A String", # Dataflow service generated name for this source. 1698 "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated. 1699 "userName": "A String", # Human-readable name for this transform; may be user or system generated. 1700 }, 1701 ], 1702 "componentTransform": [ # Transforms that comprise this execution stage. 1703 { # Description of a transform executed as part of an execution stage. 1704 "name": "A String", # Dataflow service generated name for this source. 1705 "originalTransform": "A String", # User name for the original user transform with which this transform is most closely associated. 1706 "userName": "A String", # Human-readable name for this transform; may be user or system generated. 1707 }, 1708 ], 1709 "id": "A String", # Dataflow service generated id for this stage. 1710 "inputSource": [ # Input sources for this stage. 1711 { # Description of an input or output of an execution stage. 1712 "name": "A String", # Dataflow service generated name for this source. 1713 "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated. 1714 "sizeBytes": "A String", # Size of the source, if measurable. 1715 "userName": "A String", # Human-readable name for this source; may be user or system generated. 1716 }, 1717 ], 1718 "kind": "A String", # Type of transform this stage is executing. 1719 "name": "A String", # Dataflow service generated name for this stage. 1720 "outputSource": [ # Output sources for this stage. 1721 { # Description of an input or output of an execution stage. 1722 "name": "A String", # Dataflow service generated name for this source. 1723 "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated. 1724 "sizeBytes": "A String", # Size of the source, if measurable. 1725 "userName": "A String", # Human-readable name for this source; may be user or system generated. 1726 }, 1727 ], 1728 "prerequisiteStage": [ # Other stages that must complete before this stage can run. 1729 "A String", 1730 ], 1731 }, 1732 ], 1733 "originalPipelineTransform": [ # Description of each transform in the pipeline and collections between them. 1734 { # Description of the type, names/ids, and input/outputs for a transform. 1735 "displayData": [ # Transform-specific display data. 1736 { # Data provided with a pipeline or transform to provide descriptive info. 1737 "boolValue": True or False, # Contains value if the data is of a boolean type. 1738 "durationValue": "A String", # Contains value if the data is of duration type. 1739 "floatValue": 3.14, # Contains value if the data is of float type. 1740 "int64Value": "A String", # Contains value if the data is of int64 type. 1741 "javaClassValue": "A String", # Contains value if the data is of java class type. 1742 "key": "A String", # The key identifying the display data. This is intended to be used as a label for the display data when viewed in a dax monitoring system. 1743 "label": "A String", # An optional label to display in a dax UI for the element. 1744 "namespace": "A String", # The namespace for the key. This is usually a class name or programming language namespace (i.e. python module) which defines the display data. This allows a dax monitoring system to specially handle the data and perform custom rendering. 1745 "shortStrValue": "A String", # A possible additional shorter value to display. For example a java_class_name_value of com.mypackage.MyDoFn will be stored with MyDoFn as the short_str_value and com.mypackage.MyDoFn as the java_class_name value. short_str_value can be displayed and java_class_name_value will be displayed as a tooltip. 1746 "strValue": "A String", # Contains value if the data is of string type. 1747 "timestampValue": "A String", # Contains value if the data is of timestamp type. 1748 "url": "A String", # An optional full URL. 1749 }, 1750 ], 1751 "id": "A String", # SDK generated id of this transform instance. 1752 "inputCollectionName": [ # User names for all collection inputs to this transform. 1753 "A String", 1754 ], 1755 "kind": "A String", # Type of transform. 1756 "name": "A String", # User provided name for this transform instance. 1757 "outputCollectionName": [ # User names for all collection outputs to this transform. 1758 "A String", 1759 ], 1760 }, 1761 ], 1762 }, 1763 "projectId": "A String", # The ID of the Cloud Platform project that the job belongs to. 1764 "replaceJobId": "A String", # If this job is an update of an existing job, this field is the job ID of the job it replaced. When sending a `CreateJobRequest`, you can update a job by specifying it here. The job named here is stopped, and its intermediate state is transferred to this job. 1765 "replacedByJobId": "A String", # If another job is an update of this job (and thus, this job is in `JOB_STATE_UPDATED`), this field contains the ID of that job. 1766 "requestedState": "A String", # The job's requested state. `UpdateJob` may be used to switch between the `JOB_STATE_STOPPED` and `JOB_STATE_RUNNING` states, by setting requested_state. `UpdateJob` may also be used to directly set a job's requested state to `JOB_STATE_CANCELLED` or `JOB_STATE_DONE`, irrevocably terminating the job if it has not already reached a terminal state. 1767 "satisfiesPzs": True or False, # Reserved for future use. This field is set only in responses from the server; it is ignored if it is set in any requests. 1768 "stageStates": [ # This field may be mutated by the Cloud Dataflow service; callers cannot mutate it. 1769 { # A message describing the state of a particular execution stage. 1770 "currentStateTime": "A String", # The time at which the stage transitioned to this state. 1771 "executionStageName": "A String", # The name of the execution stage. 1772 "executionStageState": "A String", # Executions stage states allow the same set of values as JobState. 1773 }, 1774 ], 1775 "startTime": "A String", # The timestamp when the job was started (transitioned to JOB_STATE_PENDING). Flexible resource scheduling jobs are started with some delay after job creation, so start_time is unset before start and is updated when the job is started by the Cloud Dataflow service. For other jobs, start_time always equals to create_time and is immutable and set by the Cloud Dataflow service. 1776 "steps": [ # Exactly one of step or steps_location should be specified. The top-level steps that constitute the entire job. Only retrieved with JOB_VIEW_ALL. 1777 { # Defines a particular step within a Cloud Dataflow job. A job consists of multiple steps, each of which performs some specific operation as part of the overall job. Data is typically passed from one step to another as part of the job. Here's an example of a sequence of steps which together implement a Map-Reduce job: * Read a collection of data from some source, parsing the collection's elements. * Validate the elements. * Apply a user-defined function to map each element to some value and extract an element-specific key value. * Group elements with the same key into a single element with that key, transforming a multiply-keyed collection into a uniquely-keyed collection. * Write the elements out to some data sink. Note that the Cloud Dataflow service may be used to run many different types of jobs, not just Map-Reduce. 1778 "kind": "A String", # The kind of step in the Cloud Dataflow job. 1779 "name": "A String", # The name that identifies the step. This must be unique for each step with respect to all other steps in the Cloud Dataflow job. 1780 "properties": { # Named properties associated with the step. Each kind of predefined step has its own required set of properties. Must be provided on Create. Only retrieved with JOB_VIEW_ALL. 1781 "a_key": "", # Properties of the object. 1782 }, 1783 }, 1784 ], 1785 "stepsLocation": "A String", # The Cloud Storage location where the steps are stored. 1786 "tempFiles": [ # A set of files the system should be aware of that are used for temporary storage. These temporary files will be removed on job completion. No duplicates are allowed. No file patterns are supported. The supported files are: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object} 1787 "A String", 1788 ], 1789 "transformNameMapping": { # The map of transform name prefixes of the job to be replaced to the corresponding name prefixes of the new job. 1790 "a_key": "A String", 1791 }, 1792 "type": "A String", # The type of Cloud Dataflow job. 1793 }, 1794 ], 1795 "nextPageToken": "A String", # Set if there may be more results than fit in this response. 1796}</pre> 1797</div> 1798 1799<div class="method"> 1800 <code class="details" id="list_next">list_next(previous_request, previous_response)</code> 1801 <pre>Retrieves the next page of results. 1802 1803Args: 1804 previous_request: The request for the previous page. (required) 1805 previous_response: The response from the request for the previous page. (required) 1806 1807Returns: 1808 A request object that you can call 'execute()' on to request the next 1809 page. Returns None if there are no more items in the collection. 1810 </pre> 1811</div> 1812 1813<div class="method"> 1814 <code class="details" id="snapshot">snapshot(projectId, jobId, body=None, x__xgafv=None)</code> 1815 <pre>Snapshot the state of a streaming job. 1816 1817Args: 1818 projectId: string, The project which owns the job to be snapshotted. (required) 1819 jobId: string, The job to be snapshotted. (required) 1820 body: object, The request body. 1821 The object takes the form of: 1822 1823{ # Request to create a snapshot of a job. 1824 "description": "A String", # User specified description of the snapshot. Maybe empty. 1825 "location": "A String", # The location that contains this job. 1826 "snapshotSources": True or False, # If true, perform snapshots for sources which support this. 1827 "ttl": "A String", # TTL for the snapshot. 1828} 1829 1830 x__xgafv: string, V1 error format. 1831 Allowed values 1832 1 - v1 error format 1833 2 - v2 error format 1834 1835Returns: 1836 An object of the form: 1837 1838 { # Represents a snapshot of a job. 1839 "creationTime": "A String", # The time this snapshot was created. 1840 "description": "A String", # User specified description of the snapshot. Maybe empty. 1841 "diskSizeBytes": "A String", # The disk byte size of the snapshot. Only available for snapshots in READY state. 1842 "id": "A String", # The unique ID of this snapshot. 1843 "projectId": "A String", # The project this snapshot belongs to. 1844 "pubsubMetadata": [ # Pub/Sub snapshot metadata. 1845 { # Represents a Pubsub snapshot. 1846 "expireTime": "A String", # The expire time of the Pubsub snapshot. 1847 "snapshotName": "A String", # The name of the Pubsub snapshot. 1848 "topicName": "A String", # The name of the Pubsub topic. 1849 }, 1850 ], 1851 "region": "A String", # Cloud region where this snapshot lives in, e.g., "us-central1". 1852 "sourceJobId": "A String", # The job this snapshot was created from. 1853 "state": "A String", # State of the snapshot. 1854 "ttl": "A String", # The time after which this snapshot will be automatically deleted. 1855}</pre> 1856</div> 1857 1858<div class="method"> 1859 <code class="details" id="update">update(projectId, jobId, body=None, location=None, x__xgafv=None)</code> 1860 <pre>Updates the state of an existing Cloud Dataflow job. To update the state of an existing job, we recommend using `projects.locations.jobs.update` with a [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints). Using `projects.jobs.update` is not recommended, as you can only update the state of jobs that are running in `us-central1`. 1861 1862Args: 1863 projectId: string, The ID of the Cloud Platform project that the job belongs to. (required) 1864 jobId: string, The job ID. (required) 1865 body: object, The request body. 1866 The object takes the form of: 1867 1868{ # Defines a job to be run by the Cloud Dataflow service. nextID: 26 1869 "clientRequestId": "A String", # The client's unique identifier of the job, re-used across retried attempts. If this field is set, the service will ensure its uniqueness. The request to create a job will fail if the service has knowledge of a previously submitted job with the same client's ID and job name. The caller may use this field to ensure idempotence of job creation across retried attempts to create a job. By default, the field is empty and, in that case, the service ignores it. 1870 "createTime": "A String", # The timestamp when the job was initially created. Immutable and set by the Cloud Dataflow service. 1871 "createdFromSnapshotId": "A String", # If this is specified, the job's initial state is populated from the given snapshot. 1872 "currentState": "A String", # The current state of the job. Jobs are created in the `JOB_STATE_STOPPED` state unless otherwise specified. A job in the `JOB_STATE_RUNNING` state may asynchronously enter a terminal state. After a job has reached a terminal state, no further state updates may be made. This field may be mutated by the Cloud Dataflow service; callers cannot mutate it. 1873 "currentStateTime": "A String", # The timestamp associated with the current state. 1874 "environment": { # Describes the environment in which a Dataflow Job runs. # The environment for the job. 1875 "clusterManagerApiService": "A String", # The type of cluster manager API to use. If unknown or unspecified, the service will attempt to choose a reasonable default. This should be in the form of the API service name, e.g. "compute.googleapis.com". 1876 "dataset": "A String", # The dataset for the current project where various workflow related tables are stored. The supported resource type is: Google BigQuery: bigquery.googleapis.com/{dataset} 1877 "debugOptions": { # Describes any options that have an effect on the debugging of pipelines. # Any debugging options to be supplied to the job. 1878 "enableHotKeyLogging": True or False, # When true, enables the logging of the literal hot key to the user's Cloud Logging. 1879 }, 1880 "experiments": [ # The list of experiments to enable. This field should be used for SDK related experiments and not for service related experiments. The proper field for service related experiments is service_options. 1881 "A String", 1882 ], 1883 "flexResourceSchedulingGoal": "A String", # Which Flexible Resource Scheduling mode to run in. 1884 "internalExperiments": { # Experimental settings. 1885 "a_key": "", # Properties of the object. Contains field @type with type URL. 1886 }, 1887 "sdkPipelineOptions": { # The Cloud Dataflow SDK pipeline options specified by the user. These options are passed through the service and are used to recreate the SDK pipeline options on the worker in a language agnostic and platform independent way. 1888 "a_key": "", # Properties of the object. 1889 }, 1890 "serviceAccountEmail": "A String", # Identity to run virtual machines as. Defaults to the default account. 1891 "serviceKmsKeyName": "A String", # If set, contains the Cloud KMS key identifier used to encrypt data at rest, AKA a Customer Managed Encryption Key (CMEK). Format: projects/PROJECT_ID/locations/LOCATION/keyRings/KEY_RING/cryptoKeys/KEY 1892 "serviceOptions": [ # The list of service options to enable. This field should be used for service related experiments only. These experiments, when graduating to GA, should be replaced by dedicated fields or become default (i.e. always on). 1893 "A String", 1894 ], 1895 "shuffleMode": "A String", # Output only. The shuffle mode used for the job. 1896 "tempStoragePrefix": "A String", # The prefix of the resources the system should use for temporary storage. The system will append the suffix "/temp-{JOBNAME} to this resource prefix, where {JOBNAME} is the value of the job_name field. The resulting bucket and object prefix is used as the prefix of the resources used to store temporary data needed during the job execution. NOTE: This will override the value in taskrunner_settings. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object} 1897 "userAgent": { # A description of the process that generated the request. 1898 "a_key": "", # Properties of the object. 1899 }, 1900 "version": { # A structure describing which components and their versions of the service are required in order to run the job. 1901 "a_key": "", # Properties of the object. 1902 }, 1903 "workerPools": [ # The worker pools. At least one "harness" worker pool must be specified in order for the job to have workers. 1904 { # Describes one particular pool of Cloud Dataflow workers to be instantiated by the Cloud Dataflow service in order to perform the computations required by a job. Note that a workflow job may use multiple pools, in order to match the various computational requirements of the various stages of the job. 1905 "autoscalingSettings": { # Settings for WorkerPool autoscaling. # Settings for autoscaling of this WorkerPool. 1906 "algorithm": "A String", # The algorithm to use for autoscaling. 1907 "maxNumWorkers": 42, # The maximum number of workers to cap scaling at. 1908 }, 1909 "dataDisks": [ # Data disks that are used by a VM in this workflow. 1910 { # Describes the data disk used by a workflow job. 1911 "diskType": "A String", # Disk storage type, as defined by Google Compute Engine. This must be a disk type appropriate to the project and zone in which the workers will run. If unknown or unspecified, the service will attempt to choose a reasonable default. For example, the standard persistent disk type is a resource name typically ending in "pd-standard". If SSD persistent disks are available, the resource name typically ends with "pd-ssd". The actual valid values are defined the Google Compute Engine API, not by the Cloud Dataflow API; consult the Google Compute Engine documentation for more information about determining the set of available disk types for a particular project and zone. Google Compute Engine Disk types are local to a particular project in a particular zone, and so the resource name will typically look something like this: compute.googleapis.com/projects/project-id/zones/zone/diskTypes/pd-standard 1912 "mountPoint": "A String", # Directory in a VM where disk is mounted. 1913 "sizeGb": 42, # Size of disk in GB. If zero or unspecified, the service will attempt to choose a reasonable default. 1914 }, 1915 ], 1916 "defaultPackageSet": "A String", # The default package set to install. This allows the service to select a default set of packages which are useful to worker harnesses written in a particular language. 1917 "diskSizeGb": 42, # Size of root disk for VMs, in GB. If zero or unspecified, the service will attempt to choose a reasonable default. 1918 "diskSourceImage": "A String", # Fully qualified source image for disks. 1919 "diskType": "A String", # Type of root disk for VMs. If empty or unspecified, the service will attempt to choose a reasonable default. 1920 "ipConfiguration": "A String", # Configuration for VM IPs. 1921 "kind": "A String", # The kind of the worker pool; currently only `harness` and `shuffle` are supported. 1922 "machineType": "A String", # Machine type (e.g. "n1-standard-1"). If empty or unspecified, the service will attempt to choose a reasonable default. 1923 "metadata": { # Metadata to set on the Google Compute Engine VMs. 1924 "a_key": "A String", 1925 }, 1926 "network": "A String", # Network to which VMs will be assigned. If empty or unspecified, the service will use the network "default". 1927 "numThreadsPerWorker": 42, # The number of threads per worker harness. If empty or unspecified, the service will choose a number of threads (according to the number of cores on the selected machine type for batch, or 1 by convention for streaming). 1928 "numWorkers": 42, # Number of Google Compute Engine workers in this pool needed to execute the job. If zero or unspecified, the service will attempt to choose a reasonable default. 1929 "onHostMaintenance": "A String", # The action to take on host maintenance, as defined by the Google Compute Engine API. 1930 "packages": [ # Packages to be installed on workers. 1931 { # The packages that must be installed in order for a worker to run the steps of the Cloud Dataflow job that will be assigned to its worker pool. This is the mechanism by which the Cloud Dataflow SDK causes code to be loaded onto the workers. For example, the Cloud Dataflow Java SDK might use this to install jars containing the user's code and all of the various dependencies (libraries, data files, etc.) required in order for that code to run. 1932 "location": "A String", # The resource to read the package from. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket} bucket.storage.googleapis.com/ 1933 "name": "A String", # The name of the package. 1934 }, 1935 ], 1936 "poolArgs": { # Extra arguments for this worker pool. 1937 "a_key": "", # Properties of the object. Contains field @type with type URL. 1938 }, 1939 "sdkHarnessContainerImages": [ # Set of SDK harness containers needed to execute this pipeline. This will only be set in the Fn API path. For non-cross-language pipelines this should have only one entry. Cross-language pipelines will have two or more entries. 1940 { # Defines a SDK harness container for executing Dataflow pipelines. 1941 "containerImage": "A String", # A docker container image that resides in Google Container Registry. 1942 "environmentId": "A String", # Environment ID for the Beam runner API proto Environment that corresponds to the current SDK Harness. 1943 "useSingleCorePerContainer": True or False, # If true, recommends the Dataflow service to use only one core per SDK container instance with this image. If false (or unset) recommends using more than one core per SDK container instance with this image for efficiency. Note that Dataflow service may choose to override this property if needed. 1944 }, 1945 ], 1946 "subnetwork": "A String", # Subnetwork to which VMs will be assigned, if desired. Expected to be of the form "regions/REGION/subnetworks/SUBNETWORK". 1947 "taskrunnerSettings": { # Taskrunner configuration settings. # Settings passed through to Google Compute Engine workers when using the standard Dataflow task runner. Users should ignore this field. 1948 "alsologtostderr": True or False, # Whether to also send taskrunner log info to stderr. 1949 "baseTaskDir": "A String", # The location on the worker for task-specific subdirectories. 1950 "baseUrl": "A String", # The base URL for the taskrunner to use when accessing Google Cloud APIs. When workers access Google Cloud APIs, they logically do so via relative URLs. If this field is specified, it supplies the base URL to use for resolving these relative URLs. The normative algorithm used is defined by RFC 1808, "Relative Uniform Resource Locators". If not specified, the default value is "http://www.googleapis.com/" 1951 "commandlinesFileName": "A String", # The file to store preprocessing commands in. 1952 "continueOnException": True or False, # Whether to continue taskrunner if an exception is hit. 1953 "dataflowApiVersion": "A String", # The API version of endpoint, e.g. "v1b3" 1954 "harnessCommand": "A String", # The command to launch the worker harness. 1955 "languageHint": "A String", # The suggested backend language. 1956 "logDir": "A String", # The directory on the VM to store logs. 1957 "logToSerialconsole": True or False, # Whether to send taskrunner log info to Google Compute Engine VM serial console. 1958 "logUploadLocation": "A String", # Indicates where to put logs. If this is not specified, the logs will not be uploaded. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object} 1959 "oauthScopes": [ # The OAuth2 scopes to be requested by the taskrunner in order to access the Cloud Dataflow API. 1960 "A String", 1961 ], 1962 "parallelWorkerSettings": { # Provides data to pass through to the worker harness. # The settings to pass to the parallel worker harness. 1963 "baseUrl": "A String", # The base URL for accessing Google Cloud APIs. When workers access Google Cloud APIs, they logically do so via relative URLs. If this field is specified, it supplies the base URL to use for resolving these relative URLs. The normative algorithm used is defined by RFC 1808, "Relative Uniform Resource Locators". If not specified, the default value is "http://www.googleapis.com/" 1964 "reportingEnabled": True or False, # Whether to send work progress updates to the service. 1965 "servicePath": "A String", # The Cloud Dataflow service path relative to the root URL, for example, "dataflow/v1b3/projects". 1966 "shuffleServicePath": "A String", # The Shuffle service path relative to the root URL, for example, "shuffle/v1beta1". 1967 "tempStoragePrefix": "A String", # The prefix of the resources the system should use for temporary storage. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object} 1968 "workerId": "A String", # The ID of the worker running this pipeline. 1969 }, 1970 "streamingWorkerMainClass": "A String", # The streaming worker main class name. 1971 "taskGroup": "A String", # The UNIX group ID on the worker VM to use for tasks launched by taskrunner; e.g. "wheel". 1972 "taskUser": "A String", # The UNIX user ID on the worker VM to use for tasks launched by taskrunner; e.g. "root". 1973 "tempStoragePrefix": "A String", # The prefix of the resources the taskrunner should use for temporary storage. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object} 1974 "vmId": "A String", # The ID string of the VM. 1975 "workflowFileName": "A String", # The file to store the workflow in. 1976 }, 1977 "teardownPolicy": "A String", # Sets the policy for determining when to turndown worker pool. Allowed values are: `TEARDOWN_ALWAYS`, `TEARDOWN_ON_SUCCESS`, and `TEARDOWN_NEVER`. `TEARDOWN_ALWAYS` means workers are always torn down regardless of whether the job succeeds. `TEARDOWN_ON_SUCCESS` means workers are torn down if the job succeeds. `TEARDOWN_NEVER` means the workers are never torn down. If the workers are not torn down by the service, they will continue to run and use Google Compute Engine VM resources in the user's project until they are explicitly terminated by the user. Because of this, Google recommends using the `TEARDOWN_ALWAYS` policy except for small, manually supervised test jobs. If unknown or unspecified, the service will attempt to choose a reasonable default. 1978 "workerHarnessContainerImage": "A String", # Required. Docker container image that executes the Cloud Dataflow worker harness, residing in Google Container Registry. Deprecated for the Fn API path. Use sdk_harness_container_images instead. 1979 "zone": "A String", # Zone to run the worker pools in. If empty or unspecified, the service will attempt to choose a reasonable default. 1980 }, 1981 ], 1982 "workerRegion": "A String", # The Compute Engine region (https://cloud.google.com/compute/docs/regions-zones/regions-zones) in which worker processing should occur, e.g. "us-west1". Mutually exclusive with worker_zone. If neither worker_region nor worker_zone is specified, default to the control plane's region. 1983 "workerZone": "A String", # The Compute Engine zone (https://cloud.google.com/compute/docs/regions-zones/regions-zones) in which worker processing should occur, e.g. "us-west1-a". Mutually exclusive with worker_region. If neither worker_region nor worker_zone is specified, a zone in the control plane's region is chosen based on available capacity. 1984 }, 1985 "executionInfo": { # Additional information about how a Cloud Dataflow job will be executed that isn't contained in the submitted job. # Deprecated. 1986 "stages": { # A mapping from each stage to the information about that stage. 1987 "a_key": { # Contains information about how a particular google.dataflow.v1beta3.Step will be executed. 1988 "stepName": [ # The steps associated with the execution stage. Note that stages may have several steps, and that a given step might be run by more than one stage. 1989 "A String", 1990 ], 1991 }, 1992 }, 1993 }, 1994 "id": "A String", # The unique ID of this job. This field is set by the Cloud Dataflow service when the Job is created, and is immutable for the life of the job. 1995 "jobMetadata": { # Metadata available primarily for filtering jobs. Will be included in the ListJob response and Job SUMMARY view. # This field is populated by the Dataflow service to support filtering jobs by the metadata values provided here. Populated for ListJobs and all GetJob views SUMMARY and higher. 1996 "bigTableDetails": [ # Identification of a Cloud Bigtable source used in the Dataflow job. 1997 { # Metadata for a Cloud Bigtable connector used by the job. 1998 "instanceId": "A String", # InstanceId accessed in the connection. 1999 "projectId": "A String", # ProjectId accessed in the connection. 2000 "tableId": "A String", # TableId accessed in the connection. 2001 }, 2002 ], 2003 "bigqueryDetails": [ # Identification of a BigQuery source used in the Dataflow job. 2004 { # Metadata for a BigQuery connector used by the job. 2005 "dataset": "A String", # Dataset accessed in the connection. 2006 "projectId": "A String", # Project accessed in the connection. 2007 "query": "A String", # Query used to access data in the connection. 2008 "table": "A String", # Table accessed in the connection. 2009 }, 2010 ], 2011 "datastoreDetails": [ # Identification of a Datastore source used in the Dataflow job. 2012 { # Metadata for a Datastore connector used by the job. 2013 "namespace": "A String", # Namespace used in the connection. 2014 "projectId": "A String", # ProjectId accessed in the connection. 2015 }, 2016 ], 2017 "fileDetails": [ # Identification of a File source used in the Dataflow job. 2018 { # Metadata for a File connector used by the job. 2019 "filePattern": "A String", # File Pattern used to access files by the connector. 2020 }, 2021 ], 2022 "pubsubDetails": [ # Identification of a Pub/Sub source used in the Dataflow job. 2023 { # Metadata for a Pub/Sub connector used by the job. 2024 "subscription": "A String", # Subscription used in the connection. 2025 "topic": "A String", # Topic accessed in the connection. 2026 }, 2027 ], 2028 "sdkVersion": { # The version of the SDK used to run the job. # The SDK version used to run the job. 2029 "sdkSupportStatus": "A String", # The support status for this SDK version. 2030 "version": "A String", # The version of the SDK used to run the job. 2031 "versionDisplayName": "A String", # A readable string describing the version of the SDK. 2032 }, 2033 "spannerDetails": [ # Identification of a Spanner source used in the Dataflow job. 2034 { # Metadata for a Spanner connector used by the job. 2035 "databaseId": "A String", # DatabaseId accessed in the connection. 2036 "instanceId": "A String", # InstanceId accessed in the connection. 2037 "projectId": "A String", # ProjectId accessed in the connection. 2038 }, 2039 ], 2040 }, 2041 "labels": { # User-defined labels for this job. The labels map can contain no more than 64 entries. Entries of the labels map are UTF8 strings that comply with the following restrictions: * Keys must conform to regexp: \p{Ll}\p{Lo}{0,62} * Values must conform to regexp: [\p{Ll}\p{Lo}\p{N}_-]{0,63} * Both keys and values are additionally constrained to be <= 128 bytes in size. 2042 "a_key": "A String", 2043 }, 2044 "location": "A String", # The [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints) that contains this job. 2045 "name": "A String", # The user-specified Cloud Dataflow job name. Only one Job with a given name may exist in a project at any given time. If a caller attempts to create a Job with the same name as an already-existing Job, the attempt returns the existing Job. The name must match the regular expression `[a-z]([-a-z0-9]{0,38}[a-z0-9])?` 2046 "pipelineDescription": { # A descriptive representation of submitted pipeline as well as the executed form. This data is provided by the Dataflow service for ease of visualizing the pipeline and interpreting Dataflow provided metrics. # Preliminary field: The format of this data may change at any time. A description of the user pipeline and stages through which it is executed. Created by Cloud Dataflow service. Only retrieved with JOB_VIEW_DESCRIPTION or JOB_VIEW_ALL. 2047 "displayData": [ # Pipeline level display data. 2048 { # Data provided with a pipeline or transform to provide descriptive info. 2049 "boolValue": True or False, # Contains value if the data is of a boolean type. 2050 "durationValue": "A String", # Contains value if the data is of duration type. 2051 "floatValue": 3.14, # Contains value if the data is of float type. 2052 "int64Value": "A String", # Contains value if the data is of int64 type. 2053 "javaClassValue": "A String", # Contains value if the data is of java class type. 2054 "key": "A String", # The key identifying the display data. This is intended to be used as a label for the display data when viewed in a dax monitoring system. 2055 "label": "A String", # An optional label to display in a dax UI for the element. 2056 "namespace": "A String", # The namespace for the key. This is usually a class name or programming language namespace (i.e. python module) which defines the display data. This allows a dax monitoring system to specially handle the data and perform custom rendering. 2057 "shortStrValue": "A String", # A possible additional shorter value to display. For example a java_class_name_value of com.mypackage.MyDoFn will be stored with MyDoFn as the short_str_value and com.mypackage.MyDoFn as the java_class_name value. short_str_value can be displayed and java_class_name_value will be displayed as a tooltip. 2058 "strValue": "A String", # Contains value if the data is of string type. 2059 "timestampValue": "A String", # Contains value if the data is of timestamp type. 2060 "url": "A String", # An optional full URL. 2061 }, 2062 ], 2063 "executionPipelineStage": [ # Description of each stage of execution of the pipeline. 2064 { # Description of the composing transforms, names/ids, and input/outputs of a stage of execution. Some composing transforms and sources may have been generated by the Dataflow service during execution planning. 2065 "componentSource": [ # Collections produced and consumed by component transforms of this stage. 2066 { # Description of an interstitial value between transforms in an execution stage. 2067 "name": "A String", # Dataflow service generated name for this source. 2068 "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated. 2069 "userName": "A String", # Human-readable name for this transform; may be user or system generated. 2070 }, 2071 ], 2072 "componentTransform": [ # Transforms that comprise this execution stage. 2073 { # Description of a transform executed as part of an execution stage. 2074 "name": "A String", # Dataflow service generated name for this source. 2075 "originalTransform": "A String", # User name for the original user transform with which this transform is most closely associated. 2076 "userName": "A String", # Human-readable name for this transform; may be user or system generated. 2077 }, 2078 ], 2079 "id": "A String", # Dataflow service generated id for this stage. 2080 "inputSource": [ # Input sources for this stage. 2081 { # Description of an input or output of an execution stage. 2082 "name": "A String", # Dataflow service generated name for this source. 2083 "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated. 2084 "sizeBytes": "A String", # Size of the source, if measurable. 2085 "userName": "A String", # Human-readable name for this source; may be user or system generated. 2086 }, 2087 ], 2088 "kind": "A String", # Type of transform this stage is executing. 2089 "name": "A String", # Dataflow service generated name for this stage. 2090 "outputSource": [ # Output sources for this stage. 2091 { # Description of an input or output of an execution stage. 2092 "name": "A String", # Dataflow service generated name for this source. 2093 "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated. 2094 "sizeBytes": "A String", # Size of the source, if measurable. 2095 "userName": "A String", # Human-readable name for this source; may be user or system generated. 2096 }, 2097 ], 2098 "prerequisiteStage": [ # Other stages that must complete before this stage can run. 2099 "A String", 2100 ], 2101 }, 2102 ], 2103 "originalPipelineTransform": [ # Description of each transform in the pipeline and collections between them. 2104 { # Description of the type, names/ids, and input/outputs for a transform. 2105 "displayData": [ # Transform-specific display data. 2106 { # Data provided with a pipeline or transform to provide descriptive info. 2107 "boolValue": True or False, # Contains value if the data is of a boolean type. 2108 "durationValue": "A String", # Contains value if the data is of duration type. 2109 "floatValue": 3.14, # Contains value if the data is of float type. 2110 "int64Value": "A String", # Contains value if the data is of int64 type. 2111 "javaClassValue": "A String", # Contains value if the data is of java class type. 2112 "key": "A String", # The key identifying the display data. This is intended to be used as a label for the display data when viewed in a dax monitoring system. 2113 "label": "A String", # An optional label to display in a dax UI for the element. 2114 "namespace": "A String", # The namespace for the key. This is usually a class name or programming language namespace (i.e. python module) which defines the display data. This allows a dax monitoring system to specially handle the data and perform custom rendering. 2115 "shortStrValue": "A String", # A possible additional shorter value to display. For example a java_class_name_value of com.mypackage.MyDoFn will be stored with MyDoFn as the short_str_value and com.mypackage.MyDoFn as the java_class_name value. short_str_value can be displayed and java_class_name_value will be displayed as a tooltip. 2116 "strValue": "A String", # Contains value if the data is of string type. 2117 "timestampValue": "A String", # Contains value if the data is of timestamp type. 2118 "url": "A String", # An optional full URL. 2119 }, 2120 ], 2121 "id": "A String", # SDK generated id of this transform instance. 2122 "inputCollectionName": [ # User names for all collection inputs to this transform. 2123 "A String", 2124 ], 2125 "kind": "A String", # Type of transform. 2126 "name": "A String", # User provided name for this transform instance. 2127 "outputCollectionName": [ # User names for all collection outputs to this transform. 2128 "A String", 2129 ], 2130 }, 2131 ], 2132 }, 2133 "projectId": "A String", # The ID of the Cloud Platform project that the job belongs to. 2134 "replaceJobId": "A String", # If this job is an update of an existing job, this field is the job ID of the job it replaced. When sending a `CreateJobRequest`, you can update a job by specifying it here. The job named here is stopped, and its intermediate state is transferred to this job. 2135 "replacedByJobId": "A String", # If another job is an update of this job (and thus, this job is in `JOB_STATE_UPDATED`), this field contains the ID of that job. 2136 "requestedState": "A String", # The job's requested state. `UpdateJob` may be used to switch between the `JOB_STATE_STOPPED` and `JOB_STATE_RUNNING` states, by setting requested_state. `UpdateJob` may also be used to directly set a job's requested state to `JOB_STATE_CANCELLED` or `JOB_STATE_DONE`, irrevocably terminating the job if it has not already reached a terminal state. 2137 "satisfiesPzs": True or False, # Reserved for future use. This field is set only in responses from the server; it is ignored if it is set in any requests. 2138 "stageStates": [ # This field may be mutated by the Cloud Dataflow service; callers cannot mutate it. 2139 { # A message describing the state of a particular execution stage. 2140 "currentStateTime": "A String", # The time at which the stage transitioned to this state. 2141 "executionStageName": "A String", # The name of the execution stage. 2142 "executionStageState": "A String", # Executions stage states allow the same set of values as JobState. 2143 }, 2144 ], 2145 "startTime": "A String", # The timestamp when the job was started (transitioned to JOB_STATE_PENDING). Flexible resource scheduling jobs are started with some delay after job creation, so start_time is unset before start and is updated when the job is started by the Cloud Dataflow service. For other jobs, start_time always equals to create_time and is immutable and set by the Cloud Dataflow service. 2146 "steps": [ # Exactly one of step or steps_location should be specified. The top-level steps that constitute the entire job. Only retrieved with JOB_VIEW_ALL. 2147 { # Defines a particular step within a Cloud Dataflow job. A job consists of multiple steps, each of which performs some specific operation as part of the overall job. Data is typically passed from one step to another as part of the job. Here's an example of a sequence of steps which together implement a Map-Reduce job: * Read a collection of data from some source, parsing the collection's elements. * Validate the elements. * Apply a user-defined function to map each element to some value and extract an element-specific key value. * Group elements with the same key into a single element with that key, transforming a multiply-keyed collection into a uniquely-keyed collection. * Write the elements out to some data sink. Note that the Cloud Dataflow service may be used to run many different types of jobs, not just Map-Reduce. 2148 "kind": "A String", # The kind of step in the Cloud Dataflow job. 2149 "name": "A String", # The name that identifies the step. This must be unique for each step with respect to all other steps in the Cloud Dataflow job. 2150 "properties": { # Named properties associated with the step. Each kind of predefined step has its own required set of properties. Must be provided on Create. Only retrieved with JOB_VIEW_ALL. 2151 "a_key": "", # Properties of the object. 2152 }, 2153 }, 2154 ], 2155 "stepsLocation": "A String", # The Cloud Storage location where the steps are stored. 2156 "tempFiles": [ # A set of files the system should be aware of that are used for temporary storage. These temporary files will be removed on job completion. No duplicates are allowed. No file patterns are supported. The supported files are: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object} 2157 "A String", 2158 ], 2159 "transformNameMapping": { # The map of transform name prefixes of the job to be replaced to the corresponding name prefixes of the new job. 2160 "a_key": "A String", 2161 }, 2162 "type": "A String", # The type of Cloud Dataflow job. 2163} 2164 2165 location: string, The [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints) that contains this job. 2166 x__xgafv: string, V1 error format. 2167 Allowed values 2168 1 - v1 error format 2169 2 - v2 error format 2170 2171Returns: 2172 An object of the form: 2173 2174 { # Defines a job to be run by the Cloud Dataflow service. nextID: 26 2175 "clientRequestId": "A String", # The client's unique identifier of the job, re-used across retried attempts. If this field is set, the service will ensure its uniqueness. The request to create a job will fail if the service has knowledge of a previously submitted job with the same client's ID and job name. The caller may use this field to ensure idempotence of job creation across retried attempts to create a job. By default, the field is empty and, in that case, the service ignores it. 2176 "createTime": "A String", # The timestamp when the job was initially created. Immutable and set by the Cloud Dataflow service. 2177 "createdFromSnapshotId": "A String", # If this is specified, the job's initial state is populated from the given snapshot. 2178 "currentState": "A String", # The current state of the job. Jobs are created in the `JOB_STATE_STOPPED` state unless otherwise specified. A job in the `JOB_STATE_RUNNING` state may asynchronously enter a terminal state. After a job has reached a terminal state, no further state updates may be made. This field may be mutated by the Cloud Dataflow service; callers cannot mutate it. 2179 "currentStateTime": "A String", # The timestamp associated with the current state. 2180 "environment": { # Describes the environment in which a Dataflow Job runs. # The environment for the job. 2181 "clusterManagerApiService": "A String", # The type of cluster manager API to use. If unknown or unspecified, the service will attempt to choose a reasonable default. This should be in the form of the API service name, e.g. "compute.googleapis.com". 2182 "dataset": "A String", # The dataset for the current project where various workflow related tables are stored. The supported resource type is: Google BigQuery: bigquery.googleapis.com/{dataset} 2183 "debugOptions": { # Describes any options that have an effect on the debugging of pipelines. # Any debugging options to be supplied to the job. 2184 "enableHotKeyLogging": True or False, # When true, enables the logging of the literal hot key to the user's Cloud Logging. 2185 }, 2186 "experiments": [ # The list of experiments to enable. This field should be used for SDK related experiments and not for service related experiments. The proper field for service related experiments is service_options. 2187 "A String", 2188 ], 2189 "flexResourceSchedulingGoal": "A String", # Which Flexible Resource Scheduling mode to run in. 2190 "internalExperiments": { # Experimental settings. 2191 "a_key": "", # Properties of the object. Contains field @type with type URL. 2192 }, 2193 "sdkPipelineOptions": { # The Cloud Dataflow SDK pipeline options specified by the user. These options are passed through the service and are used to recreate the SDK pipeline options on the worker in a language agnostic and platform independent way. 2194 "a_key": "", # Properties of the object. 2195 }, 2196 "serviceAccountEmail": "A String", # Identity to run virtual machines as. Defaults to the default account. 2197 "serviceKmsKeyName": "A String", # If set, contains the Cloud KMS key identifier used to encrypt data at rest, AKA a Customer Managed Encryption Key (CMEK). Format: projects/PROJECT_ID/locations/LOCATION/keyRings/KEY_RING/cryptoKeys/KEY 2198 "serviceOptions": [ # The list of service options to enable. This field should be used for service related experiments only. These experiments, when graduating to GA, should be replaced by dedicated fields or become default (i.e. always on). 2199 "A String", 2200 ], 2201 "shuffleMode": "A String", # Output only. The shuffle mode used for the job. 2202 "tempStoragePrefix": "A String", # The prefix of the resources the system should use for temporary storage. The system will append the suffix "/temp-{JOBNAME} to this resource prefix, where {JOBNAME} is the value of the job_name field. The resulting bucket and object prefix is used as the prefix of the resources used to store temporary data needed during the job execution. NOTE: This will override the value in taskrunner_settings. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object} 2203 "userAgent": { # A description of the process that generated the request. 2204 "a_key": "", # Properties of the object. 2205 }, 2206 "version": { # A structure describing which components and their versions of the service are required in order to run the job. 2207 "a_key": "", # Properties of the object. 2208 }, 2209 "workerPools": [ # The worker pools. At least one "harness" worker pool must be specified in order for the job to have workers. 2210 { # Describes one particular pool of Cloud Dataflow workers to be instantiated by the Cloud Dataflow service in order to perform the computations required by a job. Note that a workflow job may use multiple pools, in order to match the various computational requirements of the various stages of the job. 2211 "autoscalingSettings": { # Settings for WorkerPool autoscaling. # Settings for autoscaling of this WorkerPool. 2212 "algorithm": "A String", # The algorithm to use for autoscaling. 2213 "maxNumWorkers": 42, # The maximum number of workers to cap scaling at. 2214 }, 2215 "dataDisks": [ # Data disks that are used by a VM in this workflow. 2216 { # Describes the data disk used by a workflow job. 2217 "diskType": "A String", # Disk storage type, as defined by Google Compute Engine. This must be a disk type appropriate to the project and zone in which the workers will run. If unknown or unspecified, the service will attempt to choose a reasonable default. For example, the standard persistent disk type is a resource name typically ending in "pd-standard". If SSD persistent disks are available, the resource name typically ends with "pd-ssd". The actual valid values are defined the Google Compute Engine API, not by the Cloud Dataflow API; consult the Google Compute Engine documentation for more information about determining the set of available disk types for a particular project and zone. Google Compute Engine Disk types are local to a particular project in a particular zone, and so the resource name will typically look something like this: compute.googleapis.com/projects/project-id/zones/zone/diskTypes/pd-standard 2218 "mountPoint": "A String", # Directory in a VM where disk is mounted. 2219 "sizeGb": 42, # Size of disk in GB. If zero or unspecified, the service will attempt to choose a reasonable default. 2220 }, 2221 ], 2222 "defaultPackageSet": "A String", # The default package set to install. This allows the service to select a default set of packages which are useful to worker harnesses written in a particular language. 2223 "diskSizeGb": 42, # Size of root disk for VMs, in GB. If zero or unspecified, the service will attempt to choose a reasonable default. 2224 "diskSourceImage": "A String", # Fully qualified source image for disks. 2225 "diskType": "A String", # Type of root disk for VMs. If empty or unspecified, the service will attempt to choose a reasonable default. 2226 "ipConfiguration": "A String", # Configuration for VM IPs. 2227 "kind": "A String", # The kind of the worker pool; currently only `harness` and `shuffle` are supported. 2228 "machineType": "A String", # Machine type (e.g. "n1-standard-1"). If empty or unspecified, the service will attempt to choose a reasonable default. 2229 "metadata": { # Metadata to set on the Google Compute Engine VMs. 2230 "a_key": "A String", 2231 }, 2232 "network": "A String", # Network to which VMs will be assigned. If empty or unspecified, the service will use the network "default". 2233 "numThreadsPerWorker": 42, # The number of threads per worker harness. If empty or unspecified, the service will choose a number of threads (according to the number of cores on the selected machine type for batch, or 1 by convention for streaming). 2234 "numWorkers": 42, # Number of Google Compute Engine workers in this pool needed to execute the job. If zero or unspecified, the service will attempt to choose a reasonable default. 2235 "onHostMaintenance": "A String", # The action to take on host maintenance, as defined by the Google Compute Engine API. 2236 "packages": [ # Packages to be installed on workers. 2237 { # The packages that must be installed in order for a worker to run the steps of the Cloud Dataflow job that will be assigned to its worker pool. This is the mechanism by which the Cloud Dataflow SDK causes code to be loaded onto the workers. For example, the Cloud Dataflow Java SDK might use this to install jars containing the user's code and all of the various dependencies (libraries, data files, etc.) required in order for that code to run. 2238 "location": "A String", # The resource to read the package from. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket} bucket.storage.googleapis.com/ 2239 "name": "A String", # The name of the package. 2240 }, 2241 ], 2242 "poolArgs": { # Extra arguments for this worker pool. 2243 "a_key": "", # Properties of the object. Contains field @type with type URL. 2244 }, 2245 "sdkHarnessContainerImages": [ # Set of SDK harness containers needed to execute this pipeline. This will only be set in the Fn API path. For non-cross-language pipelines this should have only one entry. Cross-language pipelines will have two or more entries. 2246 { # Defines a SDK harness container for executing Dataflow pipelines. 2247 "containerImage": "A String", # A docker container image that resides in Google Container Registry. 2248 "environmentId": "A String", # Environment ID for the Beam runner API proto Environment that corresponds to the current SDK Harness. 2249 "useSingleCorePerContainer": True or False, # If true, recommends the Dataflow service to use only one core per SDK container instance with this image. If false (or unset) recommends using more than one core per SDK container instance with this image for efficiency. Note that Dataflow service may choose to override this property if needed. 2250 }, 2251 ], 2252 "subnetwork": "A String", # Subnetwork to which VMs will be assigned, if desired. Expected to be of the form "regions/REGION/subnetworks/SUBNETWORK". 2253 "taskrunnerSettings": { # Taskrunner configuration settings. # Settings passed through to Google Compute Engine workers when using the standard Dataflow task runner. Users should ignore this field. 2254 "alsologtostderr": True or False, # Whether to also send taskrunner log info to stderr. 2255 "baseTaskDir": "A String", # The location on the worker for task-specific subdirectories. 2256 "baseUrl": "A String", # The base URL for the taskrunner to use when accessing Google Cloud APIs. When workers access Google Cloud APIs, they logically do so via relative URLs. If this field is specified, it supplies the base URL to use for resolving these relative URLs. The normative algorithm used is defined by RFC 1808, "Relative Uniform Resource Locators". If not specified, the default value is "http://www.googleapis.com/" 2257 "commandlinesFileName": "A String", # The file to store preprocessing commands in. 2258 "continueOnException": True or False, # Whether to continue taskrunner if an exception is hit. 2259 "dataflowApiVersion": "A String", # The API version of endpoint, e.g. "v1b3" 2260 "harnessCommand": "A String", # The command to launch the worker harness. 2261 "languageHint": "A String", # The suggested backend language. 2262 "logDir": "A String", # The directory on the VM to store logs. 2263 "logToSerialconsole": True or False, # Whether to send taskrunner log info to Google Compute Engine VM serial console. 2264 "logUploadLocation": "A String", # Indicates where to put logs. If this is not specified, the logs will not be uploaded. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object} 2265 "oauthScopes": [ # The OAuth2 scopes to be requested by the taskrunner in order to access the Cloud Dataflow API. 2266 "A String", 2267 ], 2268 "parallelWorkerSettings": { # Provides data to pass through to the worker harness. # The settings to pass to the parallel worker harness. 2269 "baseUrl": "A String", # The base URL for accessing Google Cloud APIs. When workers access Google Cloud APIs, they logically do so via relative URLs. If this field is specified, it supplies the base URL to use for resolving these relative URLs. The normative algorithm used is defined by RFC 1808, "Relative Uniform Resource Locators". If not specified, the default value is "http://www.googleapis.com/" 2270 "reportingEnabled": True or False, # Whether to send work progress updates to the service. 2271 "servicePath": "A String", # The Cloud Dataflow service path relative to the root URL, for example, "dataflow/v1b3/projects". 2272 "shuffleServicePath": "A String", # The Shuffle service path relative to the root URL, for example, "shuffle/v1beta1". 2273 "tempStoragePrefix": "A String", # The prefix of the resources the system should use for temporary storage. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object} 2274 "workerId": "A String", # The ID of the worker running this pipeline. 2275 }, 2276 "streamingWorkerMainClass": "A String", # The streaming worker main class name. 2277 "taskGroup": "A String", # The UNIX group ID on the worker VM to use for tasks launched by taskrunner; e.g. "wheel". 2278 "taskUser": "A String", # The UNIX user ID on the worker VM to use for tasks launched by taskrunner; e.g. "root". 2279 "tempStoragePrefix": "A String", # The prefix of the resources the taskrunner should use for temporary storage. The supported resource type is: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object} 2280 "vmId": "A String", # The ID string of the VM. 2281 "workflowFileName": "A String", # The file to store the workflow in. 2282 }, 2283 "teardownPolicy": "A String", # Sets the policy for determining when to turndown worker pool. Allowed values are: `TEARDOWN_ALWAYS`, `TEARDOWN_ON_SUCCESS`, and `TEARDOWN_NEVER`. `TEARDOWN_ALWAYS` means workers are always torn down regardless of whether the job succeeds. `TEARDOWN_ON_SUCCESS` means workers are torn down if the job succeeds. `TEARDOWN_NEVER` means the workers are never torn down. If the workers are not torn down by the service, they will continue to run and use Google Compute Engine VM resources in the user's project until they are explicitly terminated by the user. Because of this, Google recommends using the `TEARDOWN_ALWAYS` policy except for small, manually supervised test jobs. If unknown or unspecified, the service will attempt to choose a reasonable default. 2284 "workerHarnessContainerImage": "A String", # Required. Docker container image that executes the Cloud Dataflow worker harness, residing in Google Container Registry. Deprecated for the Fn API path. Use sdk_harness_container_images instead. 2285 "zone": "A String", # Zone to run the worker pools in. If empty or unspecified, the service will attempt to choose a reasonable default. 2286 }, 2287 ], 2288 "workerRegion": "A String", # The Compute Engine region (https://cloud.google.com/compute/docs/regions-zones/regions-zones) in which worker processing should occur, e.g. "us-west1". Mutually exclusive with worker_zone. If neither worker_region nor worker_zone is specified, default to the control plane's region. 2289 "workerZone": "A String", # The Compute Engine zone (https://cloud.google.com/compute/docs/regions-zones/regions-zones) in which worker processing should occur, e.g. "us-west1-a". Mutually exclusive with worker_region. If neither worker_region nor worker_zone is specified, a zone in the control plane's region is chosen based on available capacity. 2290 }, 2291 "executionInfo": { # Additional information about how a Cloud Dataflow job will be executed that isn't contained in the submitted job. # Deprecated. 2292 "stages": { # A mapping from each stage to the information about that stage. 2293 "a_key": { # Contains information about how a particular google.dataflow.v1beta3.Step will be executed. 2294 "stepName": [ # The steps associated with the execution stage. Note that stages may have several steps, and that a given step might be run by more than one stage. 2295 "A String", 2296 ], 2297 }, 2298 }, 2299 }, 2300 "id": "A String", # The unique ID of this job. This field is set by the Cloud Dataflow service when the Job is created, and is immutable for the life of the job. 2301 "jobMetadata": { # Metadata available primarily for filtering jobs. Will be included in the ListJob response and Job SUMMARY view. # This field is populated by the Dataflow service to support filtering jobs by the metadata values provided here. Populated for ListJobs and all GetJob views SUMMARY and higher. 2302 "bigTableDetails": [ # Identification of a Cloud Bigtable source used in the Dataflow job. 2303 { # Metadata for a Cloud Bigtable connector used by the job. 2304 "instanceId": "A String", # InstanceId accessed in the connection. 2305 "projectId": "A String", # ProjectId accessed in the connection. 2306 "tableId": "A String", # TableId accessed in the connection. 2307 }, 2308 ], 2309 "bigqueryDetails": [ # Identification of a BigQuery source used in the Dataflow job. 2310 { # Metadata for a BigQuery connector used by the job. 2311 "dataset": "A String", # Dataset accessed in the connection. 2312 "projectId": "A String", # Project accessed in the connection. 2313 "query": "A String", # Query used to access data in the connection. 2314 "table": "A String", # Table accessed in the connection. 2315 }, 2316 ], 2317 "datastoreDetails": [ # Identification of a Datastore source used in the Dataflow job. 2318 { # Metadata for a Datastore connector used by the job. 2319 "namespace": "A String", # Namespace used in the connection. 2320 "projectId": "A String", # ProjectId accessed in the connection. 2321 }, 2322 ], 2323 "fileDetails": [ # Identification of a File source used in the Dataflow job. 2324 { # Metadata for a File connector used by the job. 2325 "filePattern": "A String", # File Pattern used to access files by the connector. 2326 }, 2327 ], 2328 "pubsubDetails": [ # Identification of a Pub/Sub source used in the Dataflow job. 2329 { # Metadata for a Pub/Sub connector used by the job. 2330 "subscription": "A String", # Subscription used in the connection. 2331 "topic": "A String", # Topic accessed in the connection. 2332 }, 2333 ], 2334 "sdkVersion": { # The version of the SDK used to run the job. # The SDK version used to run the job. 2335 "sdkSupportStatus": "A String", # The support status for this SDK version. 2336 "version": "A String", # The version of the SDK used to run the job. 2337 "versionDisplayName": "A String", # A readable string describing the version of the SDK. 2338 }, 2339 "spannerDetails": [ # Identification of a Spanner source used in the Dataflow job. 2340 { # Metadata for a Spanner connector used by the job. 2341 "databaseId": "A String", # DatabaseId accessed in the connection. 2342 "instanceId": "A String", # InstanceId accessed in the connection. 2343 "projectId": "A String", # ProjectId accessed in the connection. 2344 }, 2345 ], 2346 }, 2347 "labels": { # User-defined labels for this job. The labels map can contain no more than 64 entries. Entries of the labels map are UTF8 strings that comply with the following restrictions: * Keys must conform to regexp: \p{Ll}\p{Lo}{0,62} * Values must conform to regexp: [\p{Ll}\p{Lo}\p{N}_-]{0,63} * Both keys and values are additionally constrained to be <= 128 bytes in size. 2348 "a_key": "A String", 2349 }, 2350 "location": "A String", # The [regional endpoint] (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints) that contains this job. 2351 "name": "A String", # The user-specified Cloud Dataflow job name. Only one Job with a given name may exist in a project at any given time. If a caller attempts to create a Job with the same name as an already-existing Job, the attempt returns the existing Job. The name must match the regular expression `[a-z]([-a-z0-9]{0,38}[a-z0-9])?` 2352 "pipelineDescription": { # A descriptive representation of submitted pipeline as well as the executed form. This data is provided by the Dataflow service for ease of visualizing the pipeline and interpreting Dataflow provided metrics. # Preliminary field: The format of this data may change at any time. A description of the user pipeline and stages through which it is executed. Created by Cloud Dataflow service. Only retrieved with JOB_VIEW_DESCRIPTION or JOB_VIEW_ALL. 2353 "displayData": [ # Pipeline level display data. 2354 { # Data provided with a pipeline or transform to provide descriptive info. 2355 "boolValue": True or False, # Contains value if the data is of a boolean type. 2356 "durationValue": "A String", # Contains value if the data is of duration type. 2357 "floatValue": 3.14, # Contains value if the data is of float type. 2358 "int64Value": "A String", # Contains value if the data is of int64 type. 2359 "javaClassValue": "A String", # Contains value if the data is of java class type. 2360 "key": "A String", # The key identifying the display data. This is intended to be used as a label for the display data when viewed in a dax monitoring system. 2361 "label": "A String", # An optional label to display in a dax UI for the element. 2362 "namespace": "A String", # The namespace for the key. This is usually a class name or programming language namespace (i.e. python module) which defines the display data. This allows a dax monitoring system to specially handle the data and perform custom rendering. 2363 "shortStrValue": "A String", # A possible additional shorter value to display. For example a java_class_name_value of com.mypackage.MyDoFn will be stored with MyDoFn as the short_str_value and com.mypackage.MyDoFn as the java_class_name value. short_str_value can be displayed and java_class_name_value will be displayed as a tooltip. 2364 "strValue": "A String", # Contains value if the data is of string type. 2365 "timestampValue": "A String", # Contains value if the data is of timestamp type. 2366 "url": "A String", # An optional full URL. 2367 }, 2368 ], 2369 "executionPipelineStage": [ # Description of each stage of execution of the pipeline. 2370 { # Description of the composing transforms, names/ids, and input/outputs of a stage of execution. Some composing transforms and sources may have been generated by the Dataflow service during execution planning. 2371 "componentSource": [ # Collections produced and consumed by component transforms of this stage. 2372 { # Description of an interstitial value between transforms in an execution stage. 2373 "name": "A String", # Dataflow service generated name for this source. 2374 "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated. 2375 "userName": "A String", # Human-readable name for this transform; may be user or system generated. 2376 }, 2377 ], 2378 "componentTransform": [ # Transforms that comprise this execution stage. 2379 { # Description of a transform executed as part of an execution stage. 2380 "name": "A String", # Dataflow service generated name for this source. 2381 "originalTransform": "A String", # User name for the original user transform with which this transform is most closely associated. 2382 "userName": "A String", # Human-readable name for this transform; may be user or system generated. 2383 }, 2384 ], 2385 "id": "A String", # Dataflow service generated id for this stage. 2386 "inputSource": [ # Input sources for this stage. 2387 { # Description of an input or output of an execution stage. 2388 "name": "A String", # Dataflow service generated name for this source. 2389 "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated. 2390 "sizeBytes": "A String", # Size of the source, if measurable. 2391 "userName": "A String", # Human-readable name for this source; may be user or system generated. 2392 }, 2393 ], 2394 "kind": "A String", # Type of transform this stage is executing. 2395 "name": "A String", # Dataflow service generated name for this stage. 2396 "outputSource": [ # Output sources for this stage. 2397 { # Description of an input or output of an execution stage. 2398 "name": "A String", # Dataflow service generated name for this source. 2399 "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this source is most closely associated. 2400 "sizeBytes": "A String", # Size of the source, if measurable. 2401 "userName": "A String", # Human-readable name for this source; may be user or system generated. 2402 }, 2403 ], 2404 "prerequisiteStage": [ # Other stages that must complete before this stage can run. 2405 "A String", 2406 ], 2407 }, 2408 ], 2409 "originalPipelineTransform": [ # Description of each transform in the pipeline and collections between them. 2410 { # Description of the type, names/ids, and input/outputs for a transform. 2411 "displayData": [ # Transform-specific display data. 2412 { # Data provided with a pipeline or transform to provide descriptive info. 2413 "boolValue": True or False, # Contains value if the data is of a boolean type. 2414 "durationValue": "A String", # Contains value if the data is of duration type. 2415 "floatValue": 3.14, # Contains value if the data is of float type. 2416 "int64Value": "A String", # Contains value if the data is of int64 type. 2417 "javaClassValue": "A String", # Contains value if the data is of java class type. 2418 "key": "A String", # The key identifying the display data. This is intended to be used as a label for the display data when viewed in a dax monitoring system. 2419 "label": "A String", # An optional label to display in a dax UI for the element. 2420 "namespace": "A String", # The namespace for the key. This is usually a class name or programming language namespace (i.e. python module) which defines the display data. This allows a dax monitoring system to specially handle the data and perform custom rendering. 2421 "shortStrValue": "A String", # A possible additional shorter value to display. For example a java_class_name_value of com.mypackage.MyDoFn will be stored with MyDoFn as the short_str_value and com.mypackage.MyDoFn as the java_class_name value. short_str_value can be displayed and java_class_name_value will be displayed as a tooltip. 2422 "strValue": "A String", # Contains value if the data is of string type. 2423 "timestampValue": "A String", # Contains value if the data is of timestamp type. 2424 "url": "A String", # An optional full URL. 2425 }, 2426 ], 2427 "id": "A String", # SDK generated id of this transform instance. 2428 "inputCollectionName": [ # User names for all collection inputs to this transform. 2429 "A String", 2430 ], 2431 "kind": "A String", # Type of transform. 2432 "name": "A String", # User provided name for this transform instance. 2433 "outputCollectionName": [ # User names for all collection outputs to this transform. 2434 "A String", 2435 ], 2436 }, 2437 ], 2438 }, 2439 "projectId": "A String", # The ID of the Cloud Platform project that the job belongs to. 2440 "replaceJobId": "A String", # If this job is an update of an existing job, this field is the job ID of the job it replaced. When sending a `CreateJobRequest`, you can update a job by specifying it here. The job named here is stopped, and its intermediate state is transferred to this job. 2441 "replacedByJobId": "A String", # If another job is an update of this job (and thus, this job is in `JOB_STATE_UPDATED`), this field contains the ID of that job. 2442 "requestedState": "A String", # The job's requested state. `UpdateJob` may be used to switch between the `JOB_STATE_STOPPED` and `JOB_STATE_RUNNING` states, by setting requested_state. `UpdateJob` may also be used to directly set a job's requested state to `JOB_STATE_CANCELLED` or `JOB_STATE_DONE`, irrevocably terminating the job if it has not already reached a terminal state. 2443 "satisfiesPzs": True or False, # Reserved for future use. This field is set only in responses from the server; it is ignored if it is set in any requests. 2444 "stageStates": [ # This field may be mutated by the Cloud Dataflow service; callers cannot mutate it. 2445 { # A message describing the state of a particular execution stage. 2446 "currentStateTime": "A String", # The time at which the stage transitioned to this state. 2447 "executionStageName": "A String", # The name of the execution stage. 2448 "executionStageState": "A String", # Executions stage states allow the same set of values as JobState. 2449 }, 2450 ], 2451 "startTime": "A String", # The timestamp when the job was started (transitioned to JOB_STATE_PENDING). Flexible resource scheduling jobs are started with some delay after job creation, so start_time is unset before start and is updated when the job is started by the Cloud Dataflow service. For other jobs, start_time always equals to create_time and is immutable and set by the Cloud Dataflow service. 2452 "steps": [ # Exactly one of step or steps_location should be specified. The top-level steps that constitute the entire job. Only retrieved with JOB_VIEW_ALL. 2453 { # Defines a particular step within a Cloud Dataflow job. A job consists of multiple steps, each of which performs some specific operation as part of the overall job. Data is typically passed from one step to another as part of the job. Here's an example of a sequence of steps which together implement a Map-Reduce job: * Read a collection of data from some source, parsing the collection's elements. * Validate the elements. * Apply a user-defined function to map each element to some value and extract an element-specific key value. * Group elements with the same key into a single element with that key, transforming a multiply-keyed collection into a uniquely-keyed collection. * Write the elements out to some data sink. Note that the Cloud Dataflow service may be used to run many different types of jobs, not just Map-Reduce. 2454 "kind": "A String", # The kind of step in the Cloud Dataflow job. 2455 "name": "A String", # The name that identifies the step. This must be unique for each step with respect to all other steps in the Cloud Dataflow job. 2456 "properties": { # Named properties associated with the step. Each kind of predefined step has its own required set of properties. Must be provided on Create. Only retrieved with JOB_VIEW_ALL. 2457 "a_key": "", # Properties of the object. 2458 }, 2459 }, 2460 ], 2461 "stepsLocation": "A String", # The Cloud Storage location where the steps are stored. 2462 "tempFiles": [ # A set of files the system should be aware of that are used for temporary storage. These temporary files will be removed on job completion. No duplicates are allowed. No file patterns are supported. The supported files are: Google Cloud Storage: storage.googleapis.com/{bucket}/{object} bucket.storage.googleapis.com/{object} 2463 "A String", 2464 ], 2465 "transformNameMapping": { # The map of transform name prefixes of the job to be replaced to the corresponding name prefixes of the new job. 2466 "a_key": "A String", 2467 }, 2468 "type": "A String", # The type of Cloud Dataflow job. 2469}</pre> 2470</div> 2471 2472</body></html>