Firestore to Cloud Storage Text template

The Firestore to Cloud Storage Text template is a batch pipeline that reads Firestore entities and writes them to Cloud Storage as text files. You can provide a function to process each entity as a JSON string. If you don't provide such a function, every line in the output file will be a JSON-serialized entity.

Pipeline requirements

Firestore must be set up in the project before running the pipeline.

Template parameters

Required parameters

  • firestoreReadGqlQuery : A GQL (https://cloud.google.com/datastore/docs/reference/gql_reference) query that specifies which entities to grab. For example, SELECT * FROM MyKind.
  • firestoreReadProjectId : The ID of the Google Cloud project that contains the Firestore instance that you want to read data from.
  • textWritePrefix : The Cloud Storage path prefix that specifies where the data is written. (Example: gs://mybucket/somefolder/).

Optional parameters

  • firestoreReadNamespace : The namespace of the requested entities. To use the default namespace, leave this parameter blank.
  • javascriptTextTransformGcsPath : The Cloud Storage URI of the .js file that defines the JavaScript user-defined function (UDF) to use. For example, gs://my-bucket/my-udfs/my_file.js.
  • javascriptTextTransformFunctionName : The name of the JavaScript user-defined function (UDF) 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 (https://github.com/GoogleCloudPlatform/DataflowTemplates#udf-examples).

User-defined function

Optionally, you can extend this template by writing a user-defined function (UDF). The template calls the UDF for each input element. Element payloads are serialized as JSON strings. For more information, see Create user-defined functions for Dataflow templates.

Function specification

The UDF has the following specification:

  • Input: a Firestore entity, serialized as a JSON string.
  • Output: the string value to write to Cloud Storage.

Run the template

Console

  1. Go to the Dataflow Create job from template page.
  2. Go to Create job from template
  3. In the Job name field, enter a unique job name.
  4. 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.

  5. From the Dataflow template drop-down menu, select the Firestore to Text Files on Cloud Storage template.
  6. In the provided parameter fields, enter your parameter values.
  7. 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/Firestore_to_GCS_Text \
    --region REGION_NAME \
    --parameters \
firestoreReadGqlQuery="SELECT * FROM FIRESTORE_KIND",\
firestoreReadProjectId=FIRESTORE_PROJECT_ID,\
firestoreReadNamespace=FIRESTORE_NAMESPACE,\
javascriptTextTransformGcsPath=PATH_TO_JAVASCRIPT_UDF_FILE,\
javascriptTextTransformFunctionName=JAVASCRIPT_FUNCTION,\
textWritePrefix=gs://BUCKET_NAME/output/

Replace the following:

  • JOB_NAME: a unique job name of your choice
  • REGION_NAME: the region 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:

  • BUCKET_NAME: the name of your Cloud Storage bucket
  • FIRESTORE_PROJECT_ID: the Google Cloud project ID where the Firestore instance exists
  • FIRESTORE_KIND: the type of your Firestore entities
  • FIRESTORE_NAMESPACE: the namespace of your Firestore entities
  • JAVASCRIPT_FUNCTION: 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.

  • PATH_TO_JAVASCRIPT_UDF_FILE: 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

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/Firestore_to_GCS_Text
{
   "jobName": "JOB_NAME",
   "parameters": {
       "firestoreReadGqlQuery": "SELECT * FROM FIRESTORE_KIND"
       "firestoreReadProjectId": "FIRESTORE_PROJECT_ID",
       "firestoreReadNamespace": "FIRESTORE_NAMESPACE",
       "javascriptTextTransformGcsPath": "PATH_TO_JAVASCRIPT_UDF_FILE",
       "javascriptTextTransformFunctionName": "JAVASCRIPT_FUNCTION",
       "textWritePrefix": "gs://BUCKET_NAME/output/"
   },
   "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
  • LOCATION: the region 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:

  • BUCKET_NAME: the name of your Cloud Storage bucket
  • FIRESTORE_PROJECT_ID: the Google Cloud project ID where the Firestore instance exists
  • FIRESTORE_KIND: the type of your Firestore entities
  • FIRESTORE_NAMESPACE: the namespace of your Firestore entities
  • JAVASCRIPT_FUNCTION: 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.

  • PATH_TO_JAVASCRIPT_UDF_FILE: 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

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