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<h1><a href="dataflow_v1b3.html">Dataflow API</a> . <a href="dataflow_v1b3.projects.html">projects</a> . <a href="dataflow_v1b3.projects.templates.html">templates</a></h1>
<h2>Instance Methods</h2>
<p class="toc_element">
  <code><a href="#create">create(projectId, body, x__xgafv=None)</a></code></p>
<p class="firstline">Creates a Cloud Dataflow job from a template.</p>
<p class="toc_element">
  <code><a href="#get">get(projectId, gcsPath=None, location=None, x__xgafv=None, view=None)</a></code></p>
<p class="firstline">Get the template associated with a template.</p>
<p class="toc_element">
  <code><a href="#launch">launch(projectId, body, dynamicTemplate_gcsPath=None, x__xgafv=None, dynamicTemplate_stagingLocation=None, location=None, gcsPath=None, validateOnly=None)</a></code></p>
<p class="firstline">Launch a template.</p>
<h3>Method Details</h3>
<div class="method">
    <code class="details" id="create">create(projectId, body, x__xgafv=None)</code>
  <pre>Creates a Cloud Dataflow job from a template.

Args:
  projectId: string, Required. The ID of the Cloud Platform project that the job belongs to. (required)
  body: object, The request body. (required)
    The object takes the form of:

{ # A request to create a Cloud Dataflow job from a template.
    "environment": { # The environment values to set at runtime. # The runtime environment for the job.
      "machineType": "A String", # The machine type to use for the job. Defaults to the value from the
          # template if not specified.
      "network": "A String", # Network to which VMs will be assigned.  If empty or unspecified,
          # the service will use the network "default".
      "zone": "A String", # The Compute Engine [availability
          # zone](https://cloud.google.com/compute/docs/regions-zones/regions-zones)
          # for launching worker instances to run your pipeline.
      "additionalUserLabels": { # Additional user labels to be specified for the job.
          # Keys and values should follow the restrictions specified in the [labeling
          # restrictions](https://cloud.google.com/compute/docs/labeling-resources#restrictions)
          # page.
        "a_key": "A String",
      },
      "additionalExperiments": [ # Additional experiment flags for the job.
        "A String",
      ],
      "bypassTempDirValidation": True or False, # Whether to bypass the safety checks for the job's temporary directory.
          # Use with caution.
      "tempLocation": "A String", # The Cloud Storage path to use for temporary files.
          # Must be a valid Cloud Storage URL, beginning with `gs://`.
      "serviceAccountEmail": "A String", # The email address of the service account to run the job as.
      "numWorkers": 42, # The initial number of Google Compute Engine instnaces for the job.
      "maxWorkers": 42, # The maximum number of Google Compute Engine instances to be made
          # available to your pipeline during execution, from 1 to 1000.
      "subnetwork": "A String", # Subnetwork to which VMs will be assigned, if desired.  Expected to be of
          # the form "regions/REGION/subnetworks/SUBNETWORK".
    },
    "gcsPath": "A String", # Required. A Cloud Storage path to the template from which to
        # create the job.
        # Must be a valid Cloud Storage URL, beginning with `gs://`.
    "location": "A String", # The [regional endpoint]
        # (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints) to
        # which to direct the request.
    "parameters": { # The runtime parameters to pass to the job.
      "a_key": "A String",
    },
    "jobName": "A String", # Required. The job name to use for the created job.
  }

  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format

Returns:
  An object of the form:

    { # Defines a job to be run by the Cloud Dataflow service.
    "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.
      "a_key": "A String",
    },
    "jobMetadata": { # Metadata available primarily for filtering jobs. Will be included in the # 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.
        # ListJob response and Job SUMMARY view.
      "sdkVersion": { # The version of the SDK used to run the job. # The SDK version used to run the job.
        "versionDisplayName": "A String", # A readable string describing the version of the SDK.
        "version": "A String", # The version of the SDK used to run the job.
        "sdkSupportStatus": "A String", # The support status for this SDK version.
      },
      "pubsubDetails": [ # Identification of a PubSub source used in the Dataflow job.
        { # Metadata for a PubSub connector used by the job.
          "topic": "A String", # Topic accessed in the connection.
          "subscription": "A String", # Subscription used in the connection.
        },
      ],
      "datastoreDetails": [ # Identification of a Datastore source used in the Dataflow job.
        { # Metadata for a Datastore connector used by the job.
          "projectId": "A String", # ProjectId accessed in the connection.
          "namespace": "A String", # Namespace used in the connection.
        },
      ],
      "fileDetails": [ # Identification of a File source used in the Dataflow job.
        { # Metadata for a File connector used by the job.
          "filePattern": "A String", # File Pattern used to access files by the connector.
        },
      ],
      "spannerDetails": [ # Identification of a Spanner source used in the Dataflow job.
        { # Metadata for a Spanner connector used by the job.
          "instanceId": "A String", # InstanceId accessed in the connection.
          "projectId": "A String", # ProjectId accessed in the connection.
          "databaseId": "A String", # DatabaseId accessed in the connection.
        },
      ],
      "bigTableDetails": [ # Identification of a BigTable source used in the Dataflow job.
        { # Metadata for a BigTable connector used by the job.
          "instanceId": "A String", # InstanceId accessed in the connection.
          "projectId": "A String", # ProjectId accessed in the connection.
          "tableId": "A String", # TableId accessed in the connection.
        },
      ],
      "bigqueryDetails": [ # Identification of a BigQuery source used in the Dataflow job.
        { # Metadata for a BigQuery connector used by the job.
          "projectId": "A String", # Project accessed in the connection.
          "dataset": "A String", # Dataset accessed in the connection.
          "table": "A String", # Table accessed in the connection.
          "query": "A String", # Query used to access data in the connection.
        },
      ],
    },
    "pipelineDescription": { # A descriptive representation of submitted pipeline as well as the executed # 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.
        # form.  This data is provided by the Dataflow service for ease of visualizing
        # the pipeline and interpreting Dataflow provided metrics.
      "originalPipelineTransform": [ # Description of each transform in the pipeline and collections between them.
        { # Description of the type, names/ids, and input/outputs for a transform.
          "kind": "A String", # Type of transform.
          "name": "A String", # User provided name for this transform instance.
          "inputCollectionName": [ # User names for all collection inputs to this transform.
            "A String",
          ],
          "displayData": [ # Transform-specific display data.
            { # Data provided with a pipeline or transform to provide descriptive info.
              "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.
              "durationValue": "A String", # Contains value if the data is of duration type.
              "url": "A String", # An optional full URL.
              "floatValue": 3.14, # Contains value if the data is of float type.
              "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.
              "javaClassValue": "A String", # Contains value if the data is of java class type.
              "label": "A String", # An optional label to display in a dax UI for the element.
              "boolValue": True or False, # Contains value if the data is of a boolean type.
              "strValue": "A String", # Contains value if the data is of string type.
              "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.
              "int64Value": "A String", # Contains value if the data is of int64 type.
              "timestampValue": "A String", # Contains value if the data is of timestamp type.
            },
          ],
          "outputCollectionName": [ # User  names for all collection outputs to this transform.
            "A String",
          ],
          "id": "A String", # SDK generated id of this transform instance.
        },
      ],
      "executionPipelineStage": [ # Description of each stage of execution of the pipeline.
        { # 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.
          "componentSource": [ # Collections produced and consumed by component transforms of this stage.
            { # Description of an interstitial value between transforms in an execution
                # stage.
              "userName": "A String", # Human-readable name for this transform; may be user or system generated.
              "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this
                  # source is most closely associated.
              "name": "A String", # Dataflow service generated name for this source.
            },
          ],
          "kind": "A String", # Type of tranform this stage is executing.
          "name": "A String", # Dataflow service generated name for this stage.
          "outputSource": [ # Output sources for this stage.
            { # Description of an input or output of an execution stage.
              "userName": "A String", # Human-readable name for this source; may be user or system generated.
              "sizeBytes": "A String", # Size of the source, if measurable.
              "name": "A String", # Dataflow service generated name for this source.
              "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this
                  # source is most closely associated.
            },
          ],
          "inputSource": [ # Input sources for this stage.
            { # Description of an input or output of an execution stage.
              "userName": "A String", # Human-readable name for this source; may be user or system generated.
              "sizeBytes": "A String", # Size of the source, if measurable.
              "name": "A String", # Dataflow service generated name for this source.
              "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this
                  # source is most closely associated.
            },
          ],
          "componentTransform": [ # Transforms that comprise this execution stage.
            { # Description of a transform executed as part of an execution stage.
              "userName": "A String", # Human-readable name for this transform; may be user or system generated.
              "originalTransform": "A String", # User name for the original user transform with which this transform is
                  # most closely associated.
              "name": "A String", # Dataflow service generated name for this source.
            },
          ],
          "id": "A String", # Dataflow service generated id for this stage.
        },
      ],
      "displayData": [ # Pipeline level display data.
        { # Data provided with a pipeline or transform to provide descriptive info.
          "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.
          "durationValue": "A String", # Contains value if the data is of duration type.
          "url": "A String", # An optional full URL.
          "floatValue": 3.14, # Contains value if the data is of float type.
          "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.
          "javaClassValue": "A String", # Contains value if the data is of java class type.
          "label": "A String", # An optional label to display in a dax UI for the element.
          "boolValue": True or False, # Contains value if the data is of a boolean type.
          "strValue": "A String", # Contains value if the data is of string type.
          "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.
          "int64Value": "A String", # Contains value if the data is of int64 type.
          "timestampValue": "A String", # Contains value if the data is of timestamp type.
        },
      ],
    },
    "stageStates": [ # This field may be mutated by the Cloud Dataflow service;
        # callers cannot mutate it.
      { # A message describing the state of a particular execution stage.
        "executionStageName": "A String", # The name of the execution stage.
        "executionStageState": "A String", # Executions stage states allow the same set of values as JobState.
        "currentStateTime": "A String", # The time at which the stage transitioned to this state.
      },
    ],
    "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.
    "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.
    "projectId": "A String", # The ID of the Cloud Platform project that the job belongs to.
    "transformNameMapping": { # The map of transform name prefixes of the job to be replaced to the
        # corresponding name prefixes of the new job.
      "a_key": "A String",
    },
    "environment": { # Describes the environment in which a Dataflow Job runs. # The environment for the job.
      "version": { # A structure describing which components and their versions of the service
          # are required in order to run the job.
        "a_key": "", # Properties of the object.
      },
      "flexResourceSchedulingGoal": "A String", # Which Flexible Resource Scheduling mode to run in.
      "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
      "internalExperiments": { # Experimental settings.
        "a_key": "", # Properties of the object. Contains field @type with type URL.
      },
      "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}
      "experiments": [ # The list of experiments to enable.
        "A String",
      ],
      "serviceAccountEmail": "A String", # Identity to run virtual machines as. Defaults to the default account.
      "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.
        "a_key": "", # Properties of the object.
      },
      "userAgent": { # A description of the process that generated the request.
        "a_key": "", # Properties of the object.
      },
      "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".
      "workerPools": [ # The worker pools. At least one "harness" worker pool must be
          # specified in order for the job to have workers.
        { # 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.
          "diskSourceImage": "A String", # Fully qualified source image for disks.
          "taskrunnerSettings": { # Taskrunner configuration settings. # Settings passed through to Google Compute Engine workers when
              # using the standard Dataflow task runner.  Users should ignore
              # this field.
            "workflowFileName": "A String", # The file to store the workflow in.
            "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}
            "commandlinesFileName": "A String", # The file to store preprocessing commands in.
            "parallelWorkerSettings": { # Provides data to pass through to the worker harness. # The settings to pass to the parallel worker harness.
              "reportingEnabled": True or False, # Whether to send work progress updates to the service.
              "shuffleServicePath": "A String", # The Shuffle service path relative to the root URL, for example,
                  # "shuffle/v1beta1".
              "workerId": "A String", # The ID of the worker running this pipeline.
              "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/"
              "servicePath": "A String", # The Cloud Dataflow service path relative to the root URL, for example,
                  # "dataflow/v1b3/projects".
              "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}
            },
            "vmId": "A String", # The ID string of the VM.
            "baseTaskDir": "A String", # The location on the worker for task-specific subdirectories.
            "continueOnException": True or False, # Whether to continue taskrunner if an exception is hit.
            "oauthScopes": [ # The OAuth2 scopes to be requested by the taskrunner in order to
                # access the Cloud Dataflow API.
              "A String",
            ],
            "taskUser": "A String", # The UNIX user ID on the worker VM to use for tasks launched by
                # taskrunner; e.g. "root".
            "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/"
            "taskGroup": "A String", # The UNIX group ID on the worker VM to use for tasks launched by
                # taskrunner; e.g. "wheel".
            "languageHint": "A String", # The suggested backend language.
            "logToSerialconsole": True or False, # Whether to send taskrunner log info to Google Compute Engine VM serial
                # console.
            "streamingWorkerMainClass": "A String", # The streaming worker main class name.
            "logDir": "A String", # The directory on the VM to store logs.
            "dataflowApiVersion": "A String", # The API version of endpoint, e.g. "v1b3"
            "harnessCommand": "A String", # The command to launch the worker harness.
            "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}
            "alsologtostderr": True or False, # Whether to also send taskrunner log info to stderr.
          },
          "kind": "A String", # The kind of the worker pool; currently only `harness` and `shuffle`
              # are supported.
          "packages": [ # Packages to be installed on workers.
            { # 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.
              "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/
              "name": "A String", # The name of the package.
            },
          ],
          "machineType": "A String", # Machine type (e.g. "n1-standard-1").  If empty or unspecified, the
              # service will attempt to choose a reasonable default.
          "network": "A String", # Network to which VMs will be assigned.  If empty or unspecified,
              # the service will use the network "default".
          "zone": "A String", # Zone to run the worker pools in.  If empty or unspecified, the service
              # will attempt to choose a reasonable default.
          "diskSizeGb": 42, # Size of root disk for VMs, in GB.  If zero or unspecified, the service will
              # attempt to choose a reasonable default.
          "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.
          "onHostMaintenance": "A String", # The action to take on host maintenance, as defined by the Google
              # Compute Engine API.
          "ipConfiguration": "A String", # Configuration for VM IPs.
          "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).
          "poolArgs": { # Extra arguments for this worker pool.
            "a_key": "", # Properties of the object. Contains field @type with type URL.
          },
          "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.
          "workerHarnessContainerImage": "A String", # Required. Docker container image that executes the Cloud Dataflow worker
              # harness, residing in Google Container Registry.
          "subnetwork": "A String", # Subnetwork to which VMs will be assigned, if desired.  Expected to be of
              # the form "regions/REGION/subnetworks/SUBNETWORK".
          "dataDisks": [ # Data disks that are used by a VM in this workflow.
            { # Describes the data disk used by a workflow job.
              "mountPoint": "A String", # Directory in a VM where disk is mounted.
              "sizeGb": 42, # Size of disk in GB.  If zero or unspecified, the service will
                  # attempt to choose a reasonable default.
              "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
            },
          ],
          "autoscalingSettings": { # Settings for WorkerPool autoscaling. # Settings for autoscaling of this WorkerPool.
            "maxNumWorkers": 42, # The maximum number of workers to cap scaling at.
            "algorithm": "A String", # The algorithm to use for autoscaling.
          },
          "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.
          "diskType": "A String", # Type of root disk for VMs.  If empty or unspecified, the service will
              # attempt to choose a reasonable default.
          "metadata": { # Metadata to set on the Google Compute Engine VMs.
            "a_key": "A String",
          },
        },
      ],
      "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}
    },
    "location": "A String", # The [regional endpoint]
        # (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints) that
        # contains this job.
    "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}
      "A String",
    ],
    "type": "A String", # The type of Cloud Dataflow job.
    "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.
    "createdFromSnapshotId": "A String", # If this is specified, the job's initial state is populated from the given
        # snapshot.
    "stepsLocation": "A String", # The GCS location where the steps are stored.
    "currentStateTime": "A String", # The timestamp associated with the current state.
    "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.
    "createTime": "A String", # The timestamp when the job was initially created. Immutable and set by the
        # Cloud Dataflow service.
    "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.
    "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])?`
    "steps": [ # Exactly one of step or steps_location should be specified.
        #
        # The top-level steps that constitute the entire job.
      { # 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.
        "kind": "A String", # The kind of step in the Cloud Dataflow job.
        "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.
          "a_key": "", # Properties of the object.
        },
        "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.
      },
    ],
    "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.
    "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.
    "executionInfo": { # Additional information about how a Cloud Dataflow job will be executed that # Deprecated.
        # isn't contained in the submitted job.
      "stages": { # A mapping from each stage to the information about that stage.
        "a_key": { # Contains information about how a particular
            # google.dataflow.v1beta3.Step will be executed.
          "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.
            "A String",
          ],
        },
      },
    },
  }</pre>
</div>

<div class="method">
    <code class="details" id="get">get(projectId, gcsPath=None, location=None, x__xgafv=None, view=None)</code>
  <pre>Get the template associated with a template.

Args:
  projectId: string, Required. The ID of the Cloud Platform project that the job belongs to. (required)
  gcsPath: string, Required. A Cloud Storage path to the template from which to
create the job.
Must be valid Cloud Storage URL, beginning with 'gs://'.
  location: string, The [regional endpoint]
(https://cloud.google.com/dataflow/docs/concepts/regional-endpoints) to
which to direct the request.
  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format
  view: string, The view to retrieve. Defaults to METADATA_ONLY.

Returns:
  An object of the form:

    { # The response to a GetTemplate request.
    "status": { # The `Status` type defines a logical error model that is suitable for # The status of the get template request. Any problems with the
        # request will be indicated in the error_details.
        # different programming environments, including REST APIs and RPC APIs. It is
        # used by [gRPC](https://github.com/grpc). The error model is designed to be:
        #
        # - Simple to use and understand for most users
        # - Flexible enough to meet unexpected needs
        #
        # # Overview
        #
        # The `Status` message contains three pieces of data: error code, error
        # message, and error details. The error code should be an enum value of
        # google.rpc.Code, but it may accept additional error codes if needed.  The
        # error message should be a developer-facing English message that helps
        # developers *understand* and *resolve* the error. If a localized user-facing
        # error message is needed, put the localized message in the error details or
        # localize it in the client. The optional error details may contain arbitrary
        # information about the error. There is a predefined set of error detail types
        # in the package `google.rpc` that can be used for common error conditions.
        #
        # # Language mapping
        #
        # The `Status` message is the logical representation of the error model, but it
        # is not necessarily the actual wire format. When the `Status` message is
        # exposed in different client libraries and different wire protocols, it can be
        # mapped differently. For example, it will likely be mapped to some exceptions
        # in Java, but more likely mapped to some error codes in C.
        #
        # # Other uses
        #
        # The error model and the `Status` message can be used in a variety of
        # environments, either with or without APIs, to provide a
        # consistent developer experience across different environments.
        #
        # Example uses of this error model include:
        #
        # - Partial errors. If a service needs to return partial errors to the client,
        #     it may embed the `Status` in the normal response to indicate the partial
        #     errors.
        #
        # - Workflow errors. A typical workflow has multiple steps. Each step may
        #     have a `Status` message for error reporting.
        #
        # - Batch operations. If a client uses batch request and batch response, the
        #     `Status` message should be used directly inside batch response, one for
        #     each error sub-response.
        #
        # - Asynchronous operations. If an API call embeds asynchronous operation
        #     results in its response, the status of those operations should be
        #     represented directly using the `Status` message.
        #
        # - Logging. If some API errors are stored in logs, the message `Status` could
        #     be used directly after any stripping needed for security/privacy reasons.
      "message": "A String", # A developer-facing error message, which should be in English. Any
          # user-facing error message should be localized and sent in the
          # google.rpc.Status.details field, or localized by the client.
      "code": 42, # The status code, which should be an enum value of google.rpc.Code.
      "details": [ # A list of messages that carry the error details.  There is a common set of
          # message types for APIs to use.
        {
          "a_key": "", # Properties of the object. Contains field @type with type URL.
        },
      ],
    },
    "metadata": { # Metadata describing a template. # The template metadata describing the template name, available
        # parameters, etc.
      "name": "A String", # Required. The name of the template.
      "parameters": [ # The parameters for the template.
        { # Metadata for a specific parameter.
          "regexes": [ # Optional. Regexes that the parameter must match.
            "A String",
          ],
          "helpText": "A String", # Required. The help text to display for the parameter.
          "name": "A String", # Required. The name of the parameter.
          "isOptional": True or False, # Optional. Whether the parameter is optional. Defaults to false.
          "label": "A String", # Required. The label to display for the parameter.
        },
      ],
      "description": "A String", # Optional. A description of the template.
    },
  }</pre>
</div>

<div class="method">
    <code class="details" id="launch">launch(projectId, body, dynamicTemplate_gcsPath=None, x__xgafv=None, dynamicTemplate_stagingLocation=None, location=None, gcsPath=None, validateOnly=None)</code>
  <pre>Launch a template.

Args:
  projectId: string, Required. The ID of the Cloud Platform project that the job belongs to. (required)
  body: object, The request body. (required)
    The object takes the form of:

{ # Parameters to provide to the template being launched.
    "environment": { # The environment values to set at runtime. # The runtime environment for the job.
      "machineType": "A String", # The machine type to use for the job. Defaults to the value from the
          # template if not specified.
      "network": "A String", # Network to which VMs will be assigned.  If empty or unspecified,
          # the service will use the network "default".
      "zone": "A String", # The Compute Engine [availability
          # zone](https://cloud.google.com/compute/docs/regions-zones/regions-zones)
          # for launching worker instances to run your pipeline.
      "additionalUserLabels": { # Additional user labels to be specified for the job.
          # Keys and values should follow the restrictions specified in the [labeling
          # restrictions](https://cloud.google.com/compute/docs/labeling-resources#restrictions)
          # page.
        "a_key": "A String",
      },
      "additionalExperiments": [ # Additional experiment flags for the job.
        "A String",
      ],
      "bypassTempDirValidation": True or False, # Whether to bypass the safety checks for the job's temporary directory.
          # Use with caution.
      "tempLocation": "A String", # The Cloud Storage path to use for temporary files.
          # Must be a valid Cloud Storage URL, beginning with `gs://`.
      "serviceAccountEmail": "A String", # The email address of the service account to run the job as.
      "numWorkers": 42, # The initial number of Google Compute Engine instnaces for the job.
      "maxWorkers": 42, # The maximum number of Google Compute Engine instances to be made
          # available to your pipeline during execution, from 1 to 1000.
      "subnetwork": "A String", # Subnetwork to which VMs will be assigned, if desired.  Expected to be of
          # the form "regions/REGION/subnetworks/SUBNETWORK".
    },
    "parameters": { # The runtime parameters to pass to the job.
      "a_key": "A String",
    },
    "jobName": "A String", # Required. The job name to use for the created job.
  }

  dynamicTemplate_gcsPath: string, Path to dynamic template spec file on GCS.
The file must be a Json serialized DynamicTemplateFieSpec object.
  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format
  dynamicTemplate_stagingLocation: string, Cloud Storage path for staging dependencies.
Must be a valid Cloud Storage URL, beginning with `gs://`.
  location: string, The [regional endpoint]
(https://cloud.google.com/dataflow/docs/concepts/regional-endpoints) to
which to direct the request.
  gcsPath: string, A Cloud Storage path to the template from which to create
the job.
Must be valid Cloud Storage URL, beginning with 'gs://'.
  validateOnly: boolean, If true, the request is validated but not actually executed.
Defaults to false.

Returns:
  An object of the form:

    { # Response to the request to launch a template.
    "job": { # Defines a job to be run by the Cloud Dataflow service. # The job that was launched, if the request was not a dry run and
        # the job was successfully launched.
      "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.
        "a_key": "A String",
      },
      "jobMetadata": { # Metadata available primarily for filtering jobs. Will be included in the # 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.
          # ListJob response and Job SUMMARY view.
        "sdkVersion": { # The version of the SDK used to run the job. # The SDK version used to run the job.
          "versionDisplayName": "A String", # A readable string describing the version of the SDK.
          "version": "A String", # The version of the SDK used to run the job.
          "sdkSupportStatus": "A String", # The support status for this SDK version.
        },
        "pubsubDetails": [ # Identification of a PubSub source used in the Dataflow job.
          { # Metadata for a PubSub connector used by the job.
            "topic": "A String", # Topic accessed in the connection.
            "subscription": "A String", # Subscription used in the connection.
          },
        ],
        "datastoreDetails": [ # Identification of a Datastore source used in the Dataflow job.
          { # Metadata for a Datastore connector used by the job.
            "projectId": "A String", # ProjectId accessed in the connection.
            "namespace": "A String", # Namespace used in the connection.
          },
        ],
        "fileDetails": [ # Identification of a File source used in the Dataflow job.
          { # Metadata for a File connector used by the job.
            "filePattern": "A String", # File Pattern used to access files by the connector.
          },
        ],
        "spannerDetails": [ # Identification of a Spanner source used in the Dataflow job.
          { # Metadata for a Spanner connector used by the job.
            "instanceId": "A String", # InstanceId accessed in the connection.
            "projectId": "A String", # ProjectId accessed in the connection.
            "databaseId": "A String", # DatabaseId accessed in the connection.
          },
        ],
        "bigTableDetails": [ # Identification of a BigTable source used in the Dataflow job.
          { # Metadata for a BigTable connector used by the job.
            "instanceId": "A String", # InstanceId accessed in the connection.
            "projectId": "A String", # ProjectId accessed in the connection.
            "tableId": "A String", # TableId accessed in the connection.
          },
        ],
        "bigqueryDetails": [ # Identification of a BigQuery source used in the Dataflow job.
          { # Metadata for a BigQuery connector used by the job.
            "projectId": "A String", # Project accessed in the connection.
            "dataset": "A String", # Dataset accessed in the connection.
            "table": "A String", # Table accessed in the connection.
            "query": "A String", # Query used to access data in the connection.
          },
        ],
      },
      "pipelineDescription": { # A descriptive representation of submitted pipeline as well as the executed # 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.
          # form.  This data is provided by the Dataflow service for ease of visualizing
          # the pipeline and interpreting Dataflow provided metrics.
        "originalPipelineTransform": [ # Description of each transform in the pipeline and collections between them.
          { # Description of the type, names/ids, and input/outputs for a transform.
            "kind": "A String", # Type of transform.
            "name": "A String", # User provided name for this transform instance.
            "inputCollectionName": [ # User names for all collection inputs to this transform.
              "A String",
            ],
            "displayData": [ # Transform-specific display data.
              { # Data provided with a pipeline or transform to provide descriptive info.
                "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.
                "durationValue": "A String", # Contains value if the data is of duration type.
                "url": "A String", # An optional full URL.
                "floatValue": 3.14, # Contains value if the data is of float type.
                "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.
                "javaClassValue": "A String", # Contains value if the data is of java class type.
                "label": "A String", # An optional label to display in a dax UI for the element.
                "boolValue": True or False, # Contains value if the data is of a boolean type.
                "strValue": "A String", # Contains value if the data is of string type.
                "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.
                "int64Value": "A String", # Contains value if the data is of int64 type.
                "timestampValue": "A String", # Contains value if the data is of timestamp type.
              },
            ],
            "outputCollectionName": [ # User  names for all collection outputs to this transform.
              "A String",
            ],
            "id": "A String", # SDK generated id of this transform instance.
          },
        ],
        "executionPipelineStage": [ # Description of each stage of execution of the pipeline.
          { # 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.
            "componentSource": [ # Collections produced and consumed by component transforms of this stage.
              { # Description of an interstitial value between transforms in an execution
                  # stage.
                "userName": "A String", # Human-readable name for this transform; may be user or system generated.
                "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this
                    # source is most closely associated.
                "name": "A String", # Dataflow service generated name for this source.
              },
            ],
            "kind": "A String", # Type of tranform this stage is executing.
            "name": "A String", # Dataflow service generated name for this stage.
            "outputSource": [ # Output sources for this stage.
              { # Description of an input or output of an execution stage.
                "userName": "A String", # Human-readable name for this source; may be user or system generated.
                "sizeBytes": "A String", # Size of the source, if measurable.
                "name": "A String", # Dataflow service generated name for this source.
                "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this
                    # source is most closely associated.
              },
            ],
            "inputSource": [ # Input sources for this stage.
              { # Description of an input or output of an execution stage.
                "userName": "A String", # Human-readable name for this source; may be user or system generated.
                "sizeBytes": "A String", # Size of the source, if measurable.
                "name": "A String", # Dataflow service generated name for this source.
                "originalTransformOrCollection": "A String", # User name for the original user transform or collection with which this
                    # source is most closely associated.
              },
            ],
            "componentTransform": [ # Transforms that comprise this execution stage.
              { # Description of a transform executed as part of an execution stage.
                "userName": "A String", # Human-readable name for this transform; may be user or system generated.
                "originalTransform": "A String", # User name for the original user transform with which this transform is
                    # most closely associated.
                "name": "A String", # Dataflow service generated name for this source.
              },
            ],
            "id": "A String", # Dataflow service generated id for this stage.
          },
        ],
        "displayData": [ # Pipeline level display data.
          { # Data provided with a pipeline or transform to provide descriptive info.
            "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.
            "durationValue": "A String", # Contains value if the data is of duration type.
            "url": "A String", # An optional full URL.
            "floatValue": 3.14, # Contains value if the data is of float type.
            "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.
            "javaClassValue": "A String", # Contains value if the data is of java class type.
            "label": "A String", # An optional label to display in a dax UI for the element.
            "boolValue": True or False, # Contains value if the data is of a boolean type.
            "strValue": "A String", # Contains value if the data is of string type.
            "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.
            "int64Value": "A String", # Contains value if the data is of int64 type.
            "timestampValue": "A String", # Contains value if the data is of timestamp type.
          },
        ],
      },
      "stageStates": [ # This field may be mutated by the Cloud Dataflow service;
          # callers cannot mutate it.
        { # A message describing the state of a particular execution stage.
          "executionStageName": "A String", # The name of the execution stage.
          "executionStageState": "A String", # Executions stage states allow the same set of values as JobState.
          "currentStateTime": "A String", # The time at which the stage transitioned to this state.
        },
      ],
      "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.
      "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.
      "projectId": "A String", # The ID of the Cloud Platform project that the job belongs to.
      "transformNameMapping": { # The map of transform name prefixes of the job to be replaced to the
          # corresponding name prefixes of the new job.
        "a_key": "A String",
      },
      "environment": { # Describes the environment in which a Dataflow Job runs. # The environment for the job.
        "version": { # A structure describing which components and their versions of the service
            # are required in order to run the job.
          "a_key": "", # Properties of the object.
        },
        "flexResourceSchedulingGoal": "A String", # Which Flexible Resource Scheduling mode to run in.
        "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
        "internalExperiments": { # Experimental settings.
          "a_key": "", # Properties of the object. Contains field @type with type URL.
        },
        "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}
        "experiments": [ # The list of experiments to enable.
          "A String",
        ],
        "serviceAccountEmail": "A String", # Identity to run virtual machines as. Defaults to the default account.
        "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.
          "a_key": "", # Properties of the object.
        },
        "userAgent": { # A description of the process that generated the request.
          "a_key": "", # Properties of the object.
        },
        "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".
        "workerPools": [ # The worker pools. At least one "harness" worker pool must be
            # specified in order for the job to have workers.
          { # 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.
            "diskSourceImage": "A String", # Fully qualified source image for disks.
            "taskrunnerSettings": { # Taskrunner configuration settings. # Settings passed through to Google Compute Engine workers when
                # using the standard Dataflow task runner.  Users should ignore
                # this field.
              "workflowFileName": "A String", # The file to store the workflow in.
              "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}
              "commandlinesFileName": "A String", # The file to store preprocessing commands in.
              "parallelWorkerSettings": { # Provides data to pass through to the worker harness. # The settings to pass to the parallel worker harness.
                "reportingEnabled": True or False, # Whether to send work progress updates to the service.
                "shuffleServicePath": "A String", # The Shuffle service path relative to the root URL, for example,
                    # "shuffle/v1beta1".
                "workerId": "A String", # The ID of the worker running this pipeline.
                "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/"
                "servicePath": "A String", # The Cloud Dataflow service path relative to the root URL, for example,
                    # "dataflow/v1b3/projects".
                "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}
              },
              "vmId": "A String", # The ID string of the VM.
              "baseTaskDir": "A String", # The location on the worker for task-specific subdirectories.
              "continueOnException": True or False, # Whether to continue taskrunner if an exception is hit.
              "oauthScopes": [ # The OAuth2 scopes to be requested by the taskrunner in order to
                  # access the Cloud Dataflow API.
                "A String",
              ],
              "taskUser": "A String", # The UNIX user ID on the worker VM to use for tasks launched by
                  # taskrunner; e.g. "root".
              "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/"
              "taskGroup": "A String", # The UNIX group ID on the worker VM to use for tasks launched by
                  # taskrunner; e.g. "wheel".
              "languageHint": "A String", # The suggested backend language.
              "logToSerialconsole": True or False, # Whether to send taskrunner log info to Google Compute Engine VM serial
                  # console.
              "streamingWorkerMainClass": "A String", # The streaming worker main class name.
              "logDir": "A String", # The directory on the VM to store logs.
              "dataflowApiVersion": "A String", # The API version of endpoint, e.g. "v1b3"
              "harnessCommand": "A String", # The command to launch the worker harness.
              "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}
              "alsologtostderr": True or False, # Whether to also send taskrunner log info to stderr.
            },
            "kind": "A String", # The kind of the worker pool; currently only `harness` and `shuffle`
                # are supported.
            "packages": [ # Packages to be installed on workers.
              { # 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.
                "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/
                "name": "A String", # The name of the package.
              },
            ],
            "machineType": "A String", # Machine type (e.g. "n1-standard-1").  If empty or unspecified, the
                # service will attempt to choose a reasonable default.
            "network": "A String", # Network to which VMs will be assigned.  If empty or unspecified,
                # the service will use the network "default".
            "zone": "A String", # Zone to run the worker pools in.  If empty or unspecified, the service
                # will attempt to choose a reasonable default.
            "diskSizeGb": 42, # Size of root disk for VMs, in GB.  If zero or unspecified, the service will
                # attempt to choose a reasonable default.
            "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.
            "onHostMaintenance": "A String", # The action to take on host maintenance, as defined by the Google
                # Compute Engine API.
            "ipConfiguration": "A String", # Configuration for VM IPs.
            "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).
            "poolArgs": { # Extra arguments for this worker pool.
              "a_key": "", # Properties of the object. Contains field @type with type URL.
            },
            "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.
            "workerHarnessContainerImage": "A String", # Required. Docker container image that executes the Cloud Dataflow worker
                # harness, residing in Google Container Registry.
            "subnetwork": "A String", # Subnetwork to which VMs will be assigned, if desired.  Expected to be of
                # the form "regions/REGION/subnetworks/SUBNETWORK".
            "dataDisks": [ # Data disks that are used by a VM in this workflow.
              { # Describes the data disk used by a workflow job.
                "mountPoint": "A String", # Directory in a VM where disk is mounted.
                "sizeGb": 42, # Size of disk in GB.  If zero or unspecified, the service will
                    # attempt to choose a reasonable default.
                "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
              },
            ],
            "autoscalingSettings": { # Settings for WorkerPool autoscaling. # Settings for autoscaling of this WorkerPool.
              "maxNumWorkers": 42, # The maximum number of workers to cap scaling at.
              "algorithm": "A String", # The algorithm to use for autoscaling.
            },
            "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.
            "diskType": "A String", # Type of root disk for VMs.  If empty or unspecified, the service will
                # attempt to choose a reasonable default.
            "metadata": { # Metadata to set on the Google Compute Engine VMs.
              "a_key": "A String",
            },
          },
        ],
        "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}
      },
      "location": "A String", # The [regional endpoint]
          # (https://cloud.google.com/dataflow/docs/concepts/regional-endpoints) that
          # contains this job.
      "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}
        "A String",
      ],
      "type": "A String", # The type of Cloud Dataflow job.
      "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.
      "createdFromSnapshotId": "A String", # If this is specified, the job's initial state is populated from the given
          # snapshot.
      "stepsLocation": "A String", # The GCS location where the steps are stored.
      "currentStateTime": "A String", # The timestamp associated with the current state.
      "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.
      "createTime": "A String", # The timestamp when the job was initially created. Immutable and set by the
          # Cloud Dataflow service.
      "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.
      "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])?`
      "steps": [ # Exactly one of step or steps_location should be specified.
          #
          # The top-level steps that constitute the entire job.
        { # 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.
          "kind": "A String", # The kind of step in the Cloud Dataflow job.
          "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.
            "a_key": "", # Properties of the object.
          },
          "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.
        },
      ],
      "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.
      "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.
      "executionInfo": { # Additional information about how a Cloud Dataflow job will be executed that # Deprecated.
          # isn't contained in the submitted job.
        "stages": { # A mapping from each stage to the information about that stage.
          "a_key": { # Contains information about how a particular
              # google.dataflow.v1beta3.Step will be executed.
            "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.
              "A String",
            ],
          },
        },
      },
    },
  }</pre>
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