Bigtable to Cloud Storage SequenceFile template

The Bigtable to Cloud Storage SequenceFile template is a pipeline that reads data from a Bigtable table and writes the data to a Cloud Storage bucket in SequenceFile format. You can use the template to copy data from Bigtable to Cloud Storage.

Pipeline requirements

  • The Bigtable table must exist.
  • The output Cloud Storage bucket must exist before running the pipeline.

Template parameters

Required parameters

  • bigtableProject: The ID of the Google Cloud project that contains the Bigtable instance that you want to read data from.
  • bigtableInstanceId: The ID of the Bigtable instance that contains the table.
  • bigtableTableId: The ID of the Bigtable table to export.
  • destinationPath: The Cloud Storage path where data is written. For example, gs://your-bucket/your-path/.
  • filenamePrefix: The prefix of the SequenceFile filename. For example, output-.

Optional parameters

  • bigtableAppProfileId: The ID of the Bigtable application profile to use for the export. If you don't specify an app profile, Bigtable uses the instance's default app profile: https://cloud.google.com/bigtable/docs/app-profiles#default-app-profile.
  • bigtableStartRow: The row where to start the export from, defaults to the first row.
  • bigtableStopRow: The row where to stop the export, defaults to the last row.
  • bigtableMaxVersions: Maximum number of cell versions. Defaults to: 2147483647.
  • bigtableFilter: Filter string. See: http://hbase.apache.org/book.html#thrift. Defaults to empty.

Run the template

Console

  1. Go to the Dataflow Create job from template page.
    2. Go to Create job from template
  2. In the Job name field, enter a unique job name.
  3. Optional: For Regional endpoint, select a value from the drop-down menu. The default region is us-central1.

    For a list of regions where you can run a Dataflow job, see Dataflow locations.

  4. From the Dataflow template drop-down menu, select the Cloud Bigtable to SequenceFile Files on Cloud Storage template .
  5. In the provided parameter fields, enter your parameter values.
  6. Click Run job.

gcloud

In your shell or terminal, run the template:

gcloud dataflow jobs run JOB_NAME \
    --gcs-location gs://dataflow-templates-REGION_NAME/VERSION/Cloud_Bigtable_to_GCS_SequenceFile \
    --region REGION_NAME \
    --parameters \
bigtableProject=BIGTABLE_PROJECT_ID,\
bigtableInstanceId=INSTANCE_ID,\
bigtableTableId=TABLE_ID,\
bigtableAppProfileId=APPLICATION_PROFILE_ID,\
destinationPath=DESTINATION_PATH,\
filenamePrefix=FILENAME_PREFIX

Replace the following:

  • JOB_NAME: a unique job name of your choice
  • VERSION: the version of the template that you want to use

    You can use the following values:

  • REGION_NAME: the region where you want to deploy your Dataflow job—for example, us-central1
  • BIGTABLE_PROJECT_ID: the ID of the Google Cloud project of the Bigtable instance that you want to read data from
  • INSTANCE_ID: the ID of the Bigtable instance that contains the table
  • TABLE_ID: the ID of the Bigtable table to export
  • APPLICATION_PROFILE_ID: the ID of the Bigtable application profile to be used for the export
  • DESTINATION_PATH: the Cloud Storage path where data is written, for example, gs://mybucket/somefolder
  • FILENAME_PREFIX: the prefix of the SequenceFile filename, for example, output-

API

To run the template using the REST API, send an HTTP POST request. For more information on the API and its authorization scopes, see projects.templates.launch.

POST https://dataflow.googleapis.com/v1b3/projects/PROJECT_ID/locations/LOCATION/templates:launch?gcsPath=gs://dataflow-templates-LOCATION/VERSION/Cloud_Bigtable_to_GCS_SequenceFile
{
   "jobName": "JOB_NAME",
   "parameters": {
       "bigtableProject": "BIGTABLE_PROJECT_ID",
       "bigtableInstanceId": "INSTANCE_ID",
       "bigtableTableId": "TABLE_ID",
       "bigtableAppProfileId": "APPLICATION_PROFILE_ID",
       "destinationPath": "DESTINATION_PATH",
       "filenamePrefix": "FILENAME_PREFIX",
   },
   "environment": { "zone": "us-central1-f" }
}

Replace the following:

  • PROJECT_ID: the Google Cloud project ID where you want to run the Dataflow job
  • JOB_NAME: a unique job name of your choice
  • VERSION: the version of the template that you want to use

    You can use the following values:

  • LOCATION: the region where you want to deploy your Dataflow job—for example, us-central1
  • BIGTABLE_PROJECT_ID: the ID of the Google Cloud project of the Bigtable instance that you want to read data from
  • INSTANCE_ID: the ID of the Bigtable instance that contains the table
  • TABLE_ID: the ID of the Bigtable table to export
  • APPLICATION_PROFILE_ID: the ID of the Bigtable application profile to be used for the export
  • DESTINATION_PATH: the Cloud Storage path where data is written, for example, gs://mybucket/somefolder
  • FILENAME_PREFIX: the prefix of the SequenceFile filename, for example, output-

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