create(projectId, body, x__xgafv=None)
Creates a Cloud Dataflow job from a template.
get(projectId, gcsPath=None, location=None, x__xgafv=None, view=None)
Get the template associated with a template.
Launch a template.
create(projectId, body, x__xgafv=None)
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",
],
},
},
},
}
get(projectId, gcsPath=None, location=None, x__xgafv=None, view=None)
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.
},
}
launch(projectId, body, dynamicTemplate_gcsPath=None, x__xgafv=None, dynamicTemplate_stagingLocation=None, location=None, gcsPath=None, validateOnly=None)
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",
],
},
},
},
},
}