Prepare Spanner for RDI

Prepare Google Cloud Spanner databases to work with RDI

Google Cloud Spanner requires specific configuration to enable change data capture (CDC) with RDI. RDI operates in two phases with Spanner: snapshot (initial sync) and streaming. During the snapshot phase, RDI uses the JDBC driver to connect directly to Spanner and read the current state of the database. In the streaming phase, RDI uses Spanner's Change Streams to capture changes related to the monitored schemas and tables.

1. Prepare for snapshot

During the snapshot phase, RDI executes multiple transactions to capture data at an exact point in time that remains consistent across all queries. This is achieved using a Spanner feature called Timestamp bounds with exact staleness.

This feature relies on the version_retention_period, which is set to one hour by default. Depending on the database tier, the volume of data to be ingested into RDI, and the load on the database, this setting may need to be increased. You can update it using this method.

2. Prepare for streaming

To enable streaming, you must create a change stream in Spanner at the database level. Use the option value_capture_type = 'NEW_ROW_AND_OLD_VALUES' to capture both the previous and updated row values.

Be sure to specify only the tables you want to ingest from and, optionally, the specific columns you're interested in. Here's an example using Google SQL syntax:

CREATE CHANGE STREAM change_stream_table1_and_table2
  FOR table1, table2
  OPTIONS (
    value_capture_type = 'NEW_ROW_AND_OLD_VALUES'
  );

Refer to the official documentation for more details, including additional configuration options and dialect-specific syntax.

3. Create a service account

To allow RDI to access the Spanner instance, you'll need to create a service account with the appropriate permissions. This service account will then be provided to RDI as a secret for authentication.

1. Create the service account

   gcloud iam service-accounts create spanner-reader-account \
       --display-name="Spanner Reader Service Account" \
       --description="Service account for reading from Spanner databases" \
       --project=YOUR_PROJECT_ID
   

2. Grant required roles

   Database Reader (read access to Spanner data):

   gcloud projects add-iam-policy-binding YOUR_PROJECT_ID \
       --member="serviceAccount:spanner-reader-account@YOUR_PROJECT_ID.iam.gserviceaccount.com" \
       --role="roles/spanner.databaseReader"
   

   Database User (query execution and metadata access):

   gcloud projects add-iam-policy-binding YOUR_PROJECT_ID \
       --member="serviceAccount:spanner-reader-account@YOUR_PROJECT_ID.iam.gserviceaccount.com" \
       --role="roles/spanner.databaseUser"
   

   Viewer (viewing instance and database configuration):

   gcloud projects add-iam-policy-binding YOUR_PROJECT_ID \
       --member="serviceAccount:spanner-reader-account@YOUR_PROJECT_ID.iam.gserviceaccount.com" \
       --role="roles/spanner.viewer"
   

3. Download the service account key

   Save the credentials locally so they can be used later by RDI:

   gcloud iam service-accounts keys create ~/spanner-reader-account.json \
       --iam-account=spanner-reader-account@YOUR_PROJECT_ID.iam.gserviceaccount.com \
       --project=YOUR_PROJECT_ID
   

4. Set up secrets for Kubernetes deployment

Before deploying the RDI pipeline, you need to configure the necessary secrets for both the source and target databases. Instructions for setting up the target database secrets are available in the RDI deployment guide.

In addition to the target database secrets, you'll also need to create a Spanner-specific secret named source-db-credentials. This secret should contain the service account key file generated during the Spanner setup phase. Use the command below to create it:

kubectl create secret generic source-db-credentials --namespace=rdi \
--from-file=gcp-service-account.json=~/spanner-reader-account.json \
--save-config --dry-run=client -o yaml | kubectl apply -f -

Be sure to adjust the file path (~/spanner-reader-account.json) if your service account key is stored elsewhere.

5. Configure RDI for Spanner

When configuring your RDI pipeline for Spanner, use the following example configuration in your config.yaml file:

sources:
  source:
    type: flink
    connection:
      type: spanner
      project_id: your-project-id
      instance_id: your-spanner-instance
      database_id: your-spanner-database
      change_streams:
        change_stream_all:
          {}
          # retention_hours: 24
    # schemas:
    #  - DEFAULT
    # tables:
    #   products: {}
    #   orders: {}
    #   order_items: {}
    # logging:
    #   level: debug
    # advanced:
    #   source:
    #     spanner.change.stream.retention.hours: 24
    #     spanner.fetch.timeout.milliseconds: 20000
    #     spanner.dialect: POSTGRESQL
    #   flink:
    #     jobmanager.rpc.port: 7123
    #     jobmanager.memory.process.size: 1024m
    #     taskmanager.numberOfTaskSlots: 3
    #     taskmanager.rpc.port: 7122
    #     taskmanager.memory.process.size: 2g
    #     blob.server.port: 7124
    #     rest.port: 8082
    #     parallelism.default: 4
    #     restart-strategy.type: fixed-delay
    #     restart-strategy.fixed-delay.attempts: 3
targets:
  target:
    connection:
      type: redis
      host: ${HOST_IP}
      port: 12000
      user: ${TARGET_DB_USERNAME}
      password: ${TARGET_DB_PASSWORD}
processors:
  target_data_type: hash

Make sure to replace the relevant connection details with your own for both the Spanner and target Redis databases.

6. Additional Kubernetes configuration

In your rdi-values.yaml file for Kubernetes deployment, make sure to configure the dataPlane section like this:

operator:
  dataPlane:
    flinkCollector:
      enabled: true
      jobManager:
        ingress:
          enabled: true
          className: traefik # Replace with your ingress controller
          hosts:
            - hostname # Replace with your desired ingress hostname

7. Configuration is complete

Once you have followed the steps above, your Google Spanner database is ready for RDI to use.