Pub/Sub Topic to BigQuery template

The Pub/Sub Topic to BigQuery template is a streaming pipeline that reads JSON-formatted messages from a Pub/Sub topic and writes them to a BigQuery table. You can use the template as a quick solution to move Pub/Sub data to BigQuery. The template reads JSON-formatted messages from Pub/Sub and converts them to BigQuery elements.

Pipeline requirements

  • The data field of Pub/Sub messages must use the JSON format, described in this JSON guide. For example, messages with values in the data field formatted as {"k1":"v1", "k2":"v2"} can be inserted into a BigQuery table with two columns, named k1 and k2, with a string data type.
  • The output table must exist prior to running the pipeline. The table schema must match the input JSON objects.

Template parameters

Parameter Description
inputTopic The Pub/Sub input topic to read from, in the format of projects/<project>/topics/<topic>.
outputTableSpec The BigQuery output table location, in the format of <my-project>:<my-dataset>.<my-table>
outputDeadletterTable The BigQuery table for messages that failed to reach the output table. It should be in <my-project>:<my-dataset>.<my-table> format. If it doesn't exist, it is created during pipeline execution. If not specified, <outputTableSpec>_error_records is used instead.
javascriptTextTransformGcsPath (Optional) The Cloud Storage URI of the .js file that defines the JavaScript user-defined function (UDF) you want to use. For example, gs://my-bucket/my-udfs/my_file.js.
javascriptTextTransformFunctionName (Optional) The name of the JavaScript user-defined function (UDF) that you want to use. For example, if your JavaScript function code is myTransform(inJson) { /*...do stuff...*/ }, then the function name is myTransform. For sample JavaScript UDFs, see UDF Examples.

User-defined function

Optionally, you can extend this template by writing a user-defined function (UDF) in JavaScript. The template calls the UDF for each input element. Element payloads are serialized as JSON strings.

To use a UDF, upload the JavaScript file to Cloud Storage and set the following template parameters:

ParameterDescription
javascriptTextTransformGcsPath The Cloud Storage location of the JavaScript file.
javascriptTextTransformFunctionName The name of the JavaScript function.

For more information, see Create user-defined functions for Dataflow templates.

Function specification

The UDF has the following specification:

  • Input: the Pub/Sub message data field, serialized as a JSON string.
  • Output: a JSON string that matches the schema of the BigQuery destination table.

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 regional endpoint 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 Pub/Sub Topic to BigQuery 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/PubSub_to_BigQuery \
    --region REGION_NAME \
    --staging-location STAGING_LOCATION \
    --parameters \
inputTopic=projects/PROJECT_ID/topics/TOPIC_NAME,\
outputTableSpec=PROJECT_ID:DATASET.TABLE_NAME,\
outputDeadletterTable=PROJECT_ID:DATASET.TABLE_NAME

Replace the following:

  • JOB_NAME: a unique job name of your choice
  • REGION_NAME: the regional endpoint where you want to deploy your Dataflow job—for example, us-central1
  • VERSION: the version of the template that you want to use

    You can use the following values:

  • STAGING_LOCATION: the location for staging local files (for example, gs://your-bucket/staging)
  • TOPIC_NAME: your Pub/Sub topic name
  • DATASET: your BigQuery dataset
  • TABLE_NAME: your BigQuery table name

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/PubSub_to_BigQuery
{
   "jobName": "JOB_NAME",
   "environment": {
       "ipConfiguration": "WORKER_IP_UNSPECIFIED",
       "additionalExperiments": []
    },
   "parameters": {
       "inputTopic": "projects/PROJECT_ID/topics/TOPIC_NAME",
       "outputTableSpec": "PROJECT_ID:DATASET.TABLE_NAME"
   }
}

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
  • LOCATION: the regional endpoint where you want to deploy your Dataflow job—for example, us-central1
  • VERSION: the version of the template that you want to use

    You can use the following values:

  • STAGING_LOCATION: the location for staging local files (for example, gs://your-bucket/staging)
  • TOPIC_NAME: your Pub/Sub topic name
  • DATASET: your BigQuery dataset
  • TABLE_NAME: your BigQuery table name

What's next