Cloud Storage SequenceFile to Bigtable template

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

Pipeline requirements

  • The Bigtable table must exist.
  • The input SequenceFiles must exist in a Cloud Storage bucket before running the pipeline.
  • The input SequenceFiles must have been exported from Bigtable or HBase.

Template parameters

Required parameters

  • bigtableProject : The ID of the Google Cloud project that contains the Bigtable instance that you want to write data to.
  • bigtableInstanceId : The ID of the Bigtable instance that contains the table.
  • bigtableTableId : The ID of the Bigtable table to import.
  • sourcePattern : The Cloud Storage path pattern to the location of the data. (Example: gs://your-bucket/your-path/prefix*).

Optional parameters

  • bigtableAppProfileId : The ID of the Bigtable application profile to use for the import. If you don't specify an application profile, Bigtable uses the instance's default application profile (https://cloud.google.com/bigtable/docs/app-profiles#default-app-profile).
  • mutationThrottleLatencyMs : Optional Set mutation latency throttling (enables the feature). Value in milliseconds. Defaults to: 0.

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 SequenceFile Files on Cloud Storage to Cloud Bigtable 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/GCS_SequenceFile_to_Cloud_Bigtable \
    --region REGION_NAME \
    --parameters \
bigtableProject=BIGTABLE_PROJECT_ID,\
bigtableInstanceId=INSTANCE_ID,\
bigtableTableId=TABLE_ID,\
bigtableAppProfileId=APPLICATION_PROFILE_ID,\
sourcePattern=SOURCE_PATTERN

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
  • SOURCE_PATTERN: the Cloud Storage path pattern where data is located, for example, gs://mybucket/somefolder/prefix*

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/GCS_SequenceFile_to_Cloud_Bigtable
{
   "jobName": "JOB_NAME",
   "parameters": {
       "bigtableProject": "BIGTABLE_PROJECT_ID",
       "bigtableInstanceId": "INSTANCE_ID",
       "bigtableTableId": "TABLE_ID",
       "bigtableAppProfileId": "APPLICATION_PROFILE_ID",
       "sourcePattern": "SOURCE_PATTERN",
   },
   "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
  • SOURCE_PATTERN: the Cloud Storage path pattern where data is located, for example, gs://mybucket/somefolder/prefix*

What's next