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Copy file name to clipboardExpand all lines: docs/dyn/aiplatform_v1.projects.locations.featureOnlineStores.featureViews.featureViewSyncs.html
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"endTime": "A String", # Optional. Exclusive end of the interval. If specified, a Timestamp matching this interval will have to be before the end.
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"startTime": "A String", # Optional. Inclusive start of the interval. If specified, a Timestamp matching this interval will have to be the same or after the start.
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},
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"syncSummary": { # Summary from the Sync job. For continuous syncs, the summary is updated periodically. For batch syncs, it gets updated on completion of the sync. # Output only. Summary of the sync job.
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"rowSynced": "A String", # Output only. Total number of rows synced.
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"totalSlot": "A String", # Output only. BigQuery slot milliseconds consumed for the sync job.
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},
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}</pre>
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</div>
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"endTime": "A String", # Optional. Exclusive end of the interval. If specified, a Timestamp matching this interval will have to be before the end.
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"startTime": "A String", # Optional. Inclusive start of the interval. If specified, a Timestamp matching this interval will have to be the same or after the start.
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},
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"syncSummary": { # Summary from the Sync job. For continuous syncs, the summary is updated periodically. For batch syncs, it gets updated on completion of the sync. # Output only. Summary of the sync job.
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"rowSynced": "A String", # Output only. Total number of rows synced.
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"totalSlot": "A String", # Output only. BigQuery slot milliseconds consumed for the sync job.
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},
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},
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],
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"nextPageToken": "A String", # A token, which can be sent as ListFeatureViewSyncsRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages.
Copy file name to clipboardExpand all lines: docs/dyn/aiplatform_v1.projects.locations.featureOnlineStores.featureViews.html
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],
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],
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"projectNumber": "A String", # Optional. The project number of the parent project of the Feature Groups.
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},
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"labels": { # Optional. The labels with user-defined metadata to organize your FeatureViews. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one FeatureOnlineStore(System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
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"a_key": "A String",
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"projectNumber": "A String", # Optional. The project number of the parent project of the Feature Groups.
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},
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"labels": { # Optional. The labels with user-defined metadata to organize your FeatureViews. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one FeatureOnlineStore(System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
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"a_key": "A String",
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"projectNumber": "A String", # Optional. The project number of the parent project of the Feature Groups.
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},
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"labels": { # Optional. The labels with user-defined metadata to organize your FeatureViews. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one FeatureOnlineStore(System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
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"a_key": "A String",
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],
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"projectNumber": "A String", # Optional. The project number of the parent project of the Feature Groups.
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},
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"labels": { # Optional. The labels with user-defined metadata to organize your FeatureViews. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one FeatureOnlineStore(System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
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"a_key": "A String",
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"updateTime": "A String", # Output only. Timestamp when this FeatureView was last updated.
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}
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updateMask: string, Field mask is used to specify the fields to be overwritten in the FeatureView resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field will be overwritten if it is in the mask. If the user does not provide a mask then only the non-empty fields present in the request will be overwritten. Set the update_mask to `*` to override all fields. Updatable fields: * `labels`
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updateMask: string, Field mask is used to specify the fields to be overwritten in the FeatureView resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field will be overwritten if it is in the mask. If the user does not provide a mask then only the non-empty fields present in the request will be overwritten. Set the update_mask to `*` to override all fields. Updatable fields: * `labels` * `serviceAgentType`
<pre>Creates a PipelineJob. A PipelineJob will run immediately when created.
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Args:
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"A String",
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],
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"runtimeConfig": { # The runtime config of a PipelineJob. # Runtime config of the pipeline.
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"defaultRuntime": { # The default runtime for the PipelineJob. # Optional. The default runtime for the PipelineJob. If not provided, Vertex Custom Job is used as the runtime. For Vertex Custom Job, please refer to https://cloud.google.com/vertex-ai/docs/training/overview
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"persistentResourceRuntimeDetail": { # Persistent resource based runtime detail. For more information, refer to https://cloud.google.com/vertex-ai/docs/training/persistent-resource-overview # Persistent resource based runtime detail.
"failurePolicy": "A String", # Represents the failure policy of a pipeline. Currently, the default of a pipeline is that the pipeline will continue to run until no more tasks can be executed, also known as PIPELINE_FAILURE_POLICY_FAIL_SLOW. However, if a pipeline is set to PIPELINE_FAILURE_POLICY_FAIL_FAST, it will stop scheduling any new tasks when a task has failed. Any scheduled tasks will continue to completion.
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"gcsOutputDirectory": "A String", # Required. A path in a Cloud Storage bucket, which will be treated as the root output directory of the pipeline. It is used by the system to generate the paths of output artifacts. The artifact paths are generated with a sub-path pattern `{job_id}/{task_id}/{output_key}` under the specified output directory. The service account specified in this pipeline must have the `storage.objects.get` and `storage.objects.create` permissions for this bucket.
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"inputArtifacts": { # The runtime artifacts of the PipelineJob. The key will be the input artifact name and the value would be one of the InputArtifact.
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}
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pipelineJobId: string, The ID to use for the PipelineJob, which will become the final component of the PipelineJob name. If not provided, an ID will be automatically generated. This value should be less than 128 characters, and valid characters are `/a-z-/`.
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preflightValidations: boolean, Optional. Whether to do component level validations before job creation. Currently we only support Google First Party Component/Pipelines.
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x__xgafv: string, V1 error format.
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Allowed values
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1 - v1 error format
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"A String",
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],
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"runtimeConfig": { # The runtime config of a PipelineJob. # Runtime config of the pipeline.
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"defaultRuntime": { # The default runtime for the PipelineJob. # Optional. The default runtime for the PipelineJob. If not provided, Vertex Custom Job is used as the runtime. For Vertex Custom Job, please refer to https://cloud.google.com/vertex-ai/docs/training/overview
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"persistentResourceRuntimeDetail": { # Persistent resource based runtime detail. For more information, refer to https://cloud.google.com/vertex-ai/docs/training/persistent-resource-overview # Persistent resource based runtime detail.
"failurePolicy": "A String", # Represents the failure policy of a pipeline. Currently, the default of a pipeline is that the pipeline will continue to run until no more tasks can be executed, also known as PIPELINE_FAILURE_POLICY_FAIL_SLOW. However, if a pipeline is set to PIPELINE_FAILURE_POLICY_FAIL_FAST, it will stop scheduling any new tasks when a task has failed. Any scheduled tasks will continue to completion.
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"gcsOutputDirectory": "A String", # Required. A path in a Cloud Storage bucket, which will be treated as the root output directory of the pipeline. It is used by the system to generate the paths of output artifacts. The artifact paths are generated with a sub-path pattern `{job_id}/{task_id}/{output_key}` under the specified output directory. The service account specified in this pipeline must have the `storage.objects.get` and `storage.objects.create` permissions for this bucket.
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"inputArtifacts": { # The runtime artifacts of the PipelineJob. The key will be the input artifact name and the value would be one of the InputArtifact.
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"A String",
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"runtimeConfig": { # The runtime config of a PipelineJob. # Runtime config of the pipeline.
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"defaultRuntime": { # The default runtime for the PipelineJob. # Optional. The default runtime for the PipelineJob. If not provided, Vertex Custom Job is used as the runtime. For Vertex Custom Job, please refer to https://cloud.google.com/vertex-ai/docs/training/overview
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"persistentResourceRuntimeDetail": { # Persistent resource based runtime detail. For more information, refer to https://cloud.google.com/vertex-ai/docs/training/persistent-resource-overview # Persistent resource based runtime detail.
"failurePolicy": "A String", # Represents the failure policy of a pipeline. Currently, the default of a pipeline is that the pipeline will continue to run until no more tasks can be executed, also known as PIPELINE_FAILURE_POLICY_FAIL_SLOW. However, if a pipeline is set to PIPELINE_FAILURE_POLICY_FAIL_FAST, it will stop scheduling any new tasks when a task has failed. Any scheduled tasks will continue to completion.
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"gcsOutputDirectory": "A String", # Required. A path in a Cloud Storage bucket, which will be treated as the root output directory of the pipeline. It is used by the system to generate the paths of output artifacts. The artifact paths are generated with a sub-path pattern `{job_id}/{task_id}/{output_key}` under the specified output directory. The service account specified in this pipeline must have the `storage.objects.get` and `storage.objects.create` permissions for this bucket.
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"inputArtifacts": { # The runtime artifacts of the PipelineJob. The key will be the input artifact name and the value would be one of the InputArtifact.
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"A String",
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"runtimeConfig": { # The runtime config of a PipelineJob. # Runtime config of the pipeline.
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"defaultRuntime": { # The default runtime for the PipelineJob. # Optional. The default runtime for the PipelineJob. If not provided, Vertex Custom Job is used as the runtime. For Vertex Custom Job, please refer to https://cloud.google.com/vertex-ai/docs/training/overview
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"persistentResourceRuntimeDetail": { # Persistent resource based runtime detail. For more information, refer to https://cloud.google.com/vertex-ai/docs/training/persistent-resource-overview # Persistent resource based runtime detail.
"failurePolicy": "A String", # Represents the failure policy of a pipeline. Currently, the default of a pipeline is that the pipeline will continue to run until no more tasks can be executed, also known as PIPELINE_FAILURE_POLICY_FAIL_SLOW. However, if a pipeline is set to PIPELINE_FAILURE_POLICY_FAIL_FAST, it will stop scheduling any new tasks when a task has failed. Any scheduled tasks will continue to completion.
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"gcsOutputDirectory": "A String", # Required. A path in a Cloud Storage bucket, which will be treated as the root output directory of the pipeline. It is used by the system to generate the paths of output artifacts. The artifact paths are generated with a sub-path pattern `{job_id}/{task_id}/{output_key}` under the specified output directory. The service account specified in this pipeline must have the `storage.objects.get` and `storage.objects.create` permissions for this bucket.
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"inputArtifacts": { # The runtime artifacts of the PipelineJob. The key will be the input artifact name and the value would be one of the InputArtifact.
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