Cloud Storage Avro to Spanner template

The Cloud Storage Avro files to Spanner template is a batch pipeline that reads Avro files exported from Spanner stored in Cloud Storage and imports them to a Spanner database.

Pipeline requirements

• The target Spanner database must exist and must be empty.
• You must have read permissions for the Cloud Storage bucket and write permissions for the target Spanner database.
• The input Cloud Storage path must exist, and it must include a spanner-export.json file that contains a JSON description of files to import.
• If the source Avro file doesn't contain a primary key, you must create an empty Spanner table with a primary key before you run the template. This step isn't required if the Avro file defines the primary key.

Warning: If the target Spanner database is not empty, new data might overwrite pre-existing data, or the import might fail.

Template parameters

Parameter	Description
instanceId	The instance ID of the Spanner database.
databaseId	The database ID of the Spanner database.
inputDir	The Cloud Storage path where the Avro files are imported from.
spannerProjectId	Optional: The Google Cloud project ID of the Spanner database. If not set, the default Google Cloud project is used.
spannerPriority	Optional: The request priority for Spanner calls. Possible values are HIGH, MEDIUM, LOW. The default value is MEDIUM.
ddlCreationTimeoutInMinutes	Optional: The timeout, in minutes, for DDL statements performed by the template. The default value is 30 minutes.
earlyIndexCreateFlag	Optional: Specifies whether to enable early index creation. If the template runs a large number of DDL statements, it's more efficient to create indexes before loading data. Therefore, the default behavior is to create the indexes first when the number of DDL statements exceeds a threshold. To disable this feature, set earlyIndexCreateFlag to false. Default: true.
waitForChangeStreams	Optional: If true, the pipeline waits for change streams to be created. If false, the job might complete while change streams are still being created in the background. Default: true.
waitForForeignKeys	Optional: If true, the pipeline waits for foreign keys to be created. If false, the job might complete while foreign keys are still being created in the background. Default: false.
waitForIndexes	Optional: If true, the pipeline waits for indexes to be created. If false, the job might complete while indexes are still being created in the background. Default: false.

Run the template

Console

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

   For the job to show up in the Spanner Instances page of the Google Cloud console, the job name must match the following format:

   cloud-spanner-import-SPANNER_INSTANCE_ID-SPANNER_DATABASE_NAME

   Replace the following:

   • SPANNER_INSTANCE_ID: your Spanner instance's ID
   • SPANNER_DATABASE_NAME: your Spanner database's 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 Avro Files on Cloud Storage to Cloud Spanner template.
5. In the provided parameter fields, enter your parameter values.
6. Click Run job.

gcloud

Note: To use the Google Cloud CLI to run classic templates, you must have Google Cloud CLI version 138.0.0 or later.

In your shell or terminal, run the template:

gcloud dataflow jobs run JOB_NAME \
    --gcs-location gs://dataflow-templates-REGION_NAME/VERSION/GCS_Avro_to_Cloud_Spanner \
    --region REGION_NAME \
    --staging-location GCS_STAGING_LOCATION \
    --parameters \
instanceId=INSTANCE_ID,\
databaseId=DATABASE_ID,\
inputDir=GCS_DIRECTORY

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:

  • latest to use the latest version of the template, which is available in the non-dated parent folder in the bucket— gs://dataflow-templates-REGION_NAME/latest/
  • the version name, like 2023-09-12-00_RC00, to use a specific version of the template, which can be found nested in the respective dated parent folder in the bucket— gs://dataflow-templates-REGION_NAME/
  Caution: The latest version of templates might update with breaking changes. Your production environments should use templates kept in the most recent dated parent folder to prevent these breaking changes from affecting your production workflows.
• REGION_NAME: the region where you want to deploy your Dataflow job—for example, us-central1
• INSTANCE_ID: the ID of the Spanner instance that contains the database
• DATABASE_ID: the ID of the Spanner database to import to
• GCS_DIRECTORY: the Cloud Storage path where the Avro files are imported from, for example, gs://mybucket/somefolder

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_Avro_to_Cloud_Spanner
{
   "jobName": "JOB_NAME",
   "parameters": {
       "instanceId": "INSTANCE_ID",
       "databaseId": "DATABASE_ID",
       "inputDir": "gs://GCS_DIRECTORY"
   },
   "environment": {
       "machineType": "n1-standard-2"
   }
}

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:

  • latest to use the latest version of the template, which is available in the non-dated parent folder in the bucket— gs://dataflow-templates-REGION_NAME/latest/
  • the version name, like 2023-09-12-00_RC00, to use a specific version of the template, which can be found nested in the respective dated parent folder in the bucket— gs://dataflow-templates-REGION_NAME/
  Caution: The latest version of templates might update with breaking changes. Your production environments should use templates kept in the most recent dated parent folder to prevent these breaking changes from affecting your production workflows.
• LOCATION: the region where you want to deploy your Dataflow job—for example, us-central1
• INSTANCE_ID: the ID of the Spanner instance that contains the database
• DATABASE_ID: the ID of the Spanner database to import to
• GCS_DIRECTORY: the Cloud Storage path where the Avro files are imported from, for example, gs://mybucket/somefolder

Template source code

Java

/*
 * Copyright (C) 2018 Google LLC
 *
 * Licensed under the Apache License, Version 2.0 (the "License"); you may not
 * use this file except in compliance with the License. You may obtain a copy of
 * the License at
 *
 *   http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
 * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
 * License for the specific language governing permissions and limitations under
 * the License.
 */
package com.google.cloud.teleport.spanner;

import com.google.cloud.spanner.Options.RpcPriority;
import com.google.cloud.spanner.SpannerOptions;
import com.google.cloud.teleport.metadata.Template;
import com.google.cloud.teleport.metadata.TemplateCategory;
import com.google.cloud.teleport.metadata.TemplateCreationParameter;
import com.google.cloud.teleport.metadata.TemplateParameter;
import com.google.cloud.teleport.metadata.TemplateParameter.TemplateEnumOption;
import com.google.cloud.teleport.spanner.ImportPipeline.Options;
import org.apache.beam.runners.dataflow.options.DataflowPipelineOptions;
import org.apache.beam.sdk.Pipeline;
import org.apache.beam.sdk.PipelineResult;
import org.apache.beam.sdk.io.gcp.spanner.SpannerConfig;
import org.apache.beam.sdk.options.Default;
import org.apache.beam.sdk.options.Description;
import org.apache.beam.sdk.options.PipelineOptions;
import org.apache.beam.sdk.options.PipelineOptionsFactory;
import org.apache.beam.sdk.options.ValueProvider;
import org.apache.beam.sdk.options.ValueProvider.NestedValueProvider;
import org.apache.beam.sdk.transforms.SerializableFunction;

/**
 * Avro to Cloud Spanner Import pipeline.
 *
 * <p>Check out <a
 * href="https://github.com/GoogleCloudPlatform/DataflowTemplates/blob/main/v1/README_GCS_Avro_to_Cloud_Spanner.md">README</a>
 * for instructions on how to use or modify this template.
 */
@Template(
    name = "GCS_Avro_to_Cloud_Spanner",
    category = TemplateCategory.BATCH,
    displayName = "Avro Files on Cloud Storage to Cloud Spanner",
    description =
        "The Cloud Storage Avro files to Cloud Spanner template is a batch pipeline that reads Avro files exported from "
            + "Cloud Spanner stored in Cloud Storage and imports them to a Cloud Spanner database.",
    optionsClass = Options.class,
    documentation =
        "https://cloud.google.com/dataflow/docs/guides/templates/provided/avro-to-cloud-spanner",
    contactInformation = "https://cloud.google.com/support",
    requirements = {
      "The target Cloud Spanner database must exist and must be empty.",
      "You must have read permissions for the Cloud Storage bucket and write permissions for the target Cloud Spanner database.",
      "The input Cloud Storage path must exist, and it must include a <a href=\"https://cloud.google.com/spanner/docs/import-non-spanner#create-export-json\">spanner-export.json</a> file that contains a JSON description of files to import."
    })
public class ImportPipeline {

  /** Options for {@link ImportPipeline}. */
  public interface Options extends PipelineOptions {

    @TemplateParameter.Text(
        order = 1,
        regexes = {"^[a-z0-9\\-]+$"},
        description = "Cloud Spanner instance ID",
        helpText = "The instance ID of the Cloud Spanner database that you want to import to.")
    ValueProvider<String> getInstanceId();

    void setInstanceId(ValueProvider<String> value);

    @TemplateParameter.Text(
        order = 2,
        regexes = {"^[a-z_0-9\\-]+$"},
        description = "Cloud Spanner database ID",
        helpText =
            "The database ID of the Cloud Spanner database that you want to import into (must"
                + " already exist).")
    ValueProvider<String> getDatabaseId();

    void setDatabaseId(ValueProvider<String> value);

    @TemplateParameter.GcsReadFolder(
        order = 3,
        description = "Cloud storage input directory",
        helpText = "The Cloud Storage path where the Avro files should be imported from.")
    ValueProvider<String> getInputDir();

    void setInputDir(ValueProvider<String> value);

    @TemplateParameter.Text(
        order = 4,
        optional = true,
        description = "Cloud Spanner Endpoint to call",
        helpText = "The Cloud Spanner endpoint to call in the template. Only used for testing.",
        example = "https://batch-spanner.googleapis.com")
    @Default.String("https://batch-spanner.googleapis.com")
    ValueProvider<String> getSpannerHost();

    void setSpannerHost(ValueProvider<String> value);

    @TemplateParameter.Boolean(
        order = 5,
        optional = true,
        description = "Wait for Indexes",
        helpText =
            "By default the import pipeline is not blocked on index creation, and it "
                + "may complete with indexes still being created in the background. If true, the "
                + "pipeline waits until indexes are created.")
    @Default.Boolean(false)
    ValueProvider<Boolean> getWaitForIndexes();

    void setWaitForIndexes(ValueProvider<Boolean> value);

    @TemplateParameter.Boolean(
        order = 6,
        optional = true,
        description = "Wait for Foreign Keys",
        helpText =
            "By default the import pipeline is not blocked on foreign key creation, and it may"
                + " complete with foreign keys still being created in the background. If true, the"
                + " pipeline waits until foreign keys are created.")
    @Default.Boolean(false)
    ValueProvider<Boolean> getWaitForForeignKeys();

    void setWaitForForeignKeys(ValueProvider<Boolean> value);

    @TemplateParameter.Boolean(
        order = 7,
        optional = true,
        description = "Wait for Change Streams",
        helpText =
            "By default the import pipeline is blocked on change stream creation. If false, it may"
                + " complete with change streams still being created in the background.")
    @Default.Boolean(true)
    ValueProvider<Boolean> getWaitForChangeStreams();

    void setWaitForChangeStreams(ValueProvider<Boolean> value);

    @TemplateParameter.Boolean(
        order = 7,
        optional = true,
        description = "Wait for Sequences",
        helpText =
            "By default the import pipeline is blocked on sequence creation. If false, it may"
                + " complete with sequences still being created in the background.")
    @Default.Boolean(true)
    ValueProvider<Boolean> getWaitForSequences();

    void setWaitForSequences(ValueProvider<Boolean> value);

    @TemplateParameter.Boolean(
        order = 8,
        optional = true,
        description = "Create Indexes early",
        helpText =
            "Flag to turn off early index creation if there are many indexes. Indexes and Foreign"
                + " keys are created after dataload. If there are more than 40 DDL statements to be"
                + " executed after dataload, it is preferable to create the indexes before dataload."
                + " This is the flag to turn the feature off.")
    @Default.Boolean(true)
    ValueProvider<Boolean> getEarlyIndexCreateFlag();

    void setEarlyIndexCreateFlag(ValueProvider<Boolean> value);

    @TemplateCreationParameter(value = "false")
    @Description("If true, wait for job finish")
    @Default.Boolean(true)
    boolean getWaitUntilFinish();

    @TemplateParameter.ProjectId(
        order = 9,
        optional = true,
        description = "Cloud Spanner Project Id",
        helpText = "The project ID of the Cloud Spanner instance.")
    ValueProvider<String> getSpannerProjectId();

    void setSpannerProjectId(ValueProvider<String> value);

    void setWaitUntilFinish(boolean value);

    @TemplateParameter.Text(
        order = 10,
        optional = true,
        regexes = {"[0-9]+"},
        description = "DDL Creation timeout in minutes",
        helpText = "DDL Creation timeout in minutes.")
    @Default.Integer(30)
    ValueProvider<Integer> getDdlCreationTimeoutInMinutes();

    void setDdlCreationTimeoutInMinutes(ValueProvider<Integer> value);

    @TemplateParameter.Enum(
        order = 11,
        enumOptions = {
          @TemplateEnumOption("LOW"),
          @TemplateEnumOption("MEDIUM"),
          @TemplateEnumOption("HIGH")
        },
        optional = true,
        description = "Priority for Spanner RPC invocations",
        helpText =
            "The request priority for Cloud Spanner calls. The value must be one of:"
                + " [HIGH,MEDIUM,LOW].")
    ValueProvider<RpcPriority> getSpannerPriority();

    void setSpannerPriority(ValueProvider<RpcPriority> value);
  }

  public static void main(String[] args) {

    Options options = PipelineOptionsFactory.fromArgs(args).withValidation().as(Options.class);

    Pipeline p = Pipeline.create(options);

    SpannerConfig spannerConfig =
        SpannerConfig.create()
            // Temporary fix explicitly setting SpannerConfig.projectId to the default project
            // if spannerProjectId is not provided as a parameter. Required as of Beam 2.38,
            // which no longer accepts null label values on metrics, and SpannerIO#setup() has
            // a bug resulting in the label value being set to the original parameter value,
            // with no fallback to the default project.
            // TODO: remove NestedValueProvider when this is fixed in Beam.
            .withProjectId(
                NestedValueProvider.of(
                    options.getSpannerProjectId(),
                    (SerializableFunction<String, String>)
                        input -> input != null ? input : SpannerOptions.getDefaultProjectId()))
            .withHost(options.getSpannerHost())
            .withInstanceId(options.getInstanceId())
            .withDatabaseId(options.getDatabaseId())
            .withRpcPriority(options.getSpannerPriority());

    p.apply(
        new ImportTransform(
            spannerConfig,
            options.getInputDir(),
            options.getWaitForIndexes(),
            options.getWaitForForeignKeys(),
            options.getWaitForChangeStreams(),
            options.getWaitForSequences(),
            options.getEarlyIndexCreateFlag(),
            options.getDdlCreationTimeoutInMinutes()));

    PipelineResult result = p.run();

    if (options.getWaitUntilFinish()
        &&
        /* Only if template location is null, there is a dataflow job to wait for. Else it's
         * template generation which doesn't start a dataflow job.
         */
        options.as(DataflowPipelineOptions.class).getTemplateLocation() == null) {
      result.waitUntilFinish();
    }
  }
}

What's next

• Learn about Dataflow templates.
• See the list of Google-provided templates.