Sync from Cloud SQL

In the Google Cloud console, go to the Agentspace page.

Agentspace

Go to the Data Stores page.

Click New data store.

On the Source page, select Cloud SQL.

Specify the project ID, instance ID, database ID, and table ID of the data that you plan to import.

Click Browse and choose an intermediate Cloud Storage location to export data to, and then click Select. Alternatively, enter the location directly in the gs:// field.

Select whether to turn on serverless export. Serverless export incurs additional cost. For information about serverless export, see Minimize the performance impact of exports in the Cloud SQL documentation.

Click Continue.

Choose a region for your data store.

Enter a name for your data store.

Click Create.

To check the status of your ingestion, go to the Data Stores page and click your data store name to see details about it on its Data page. When the status column on the Activity tab changes from In progress to Import completed, the ingestion is complete.

Depending on the size of your data, ingestion can take several minutes or several hours.

Create a data store.

curl -X POST \
-H "Authorization: Bearer $(gcloud auth print-access-token)" \
-H "Content-Type: application/json" \
-H "X-Goog-User-Project: PROJECT_ID" \
"https://discoveryengine.googleapis.com/v1alpha/projects/PROJECT_ID/locations/global/collections/default_collection/dataStores?dataStoreId=DATA_STORE_ID" \
-d '{
  "displayName": "DISPLAY_NAME",
  "industryVertical": "GENERIC",
  "solutionTypes": ["SOLUTION_TYPE_SEARCH"],
}'

Replace the following:

• PROJECT_ID: the ID of your project.
• DATA_STORE_ID: the ID of the data store. The ID can contain only lowercase letters, digits, underscores, and hyphens.
• DISPLAY_NAME: the display name of the data store. This might be displayed in the Google Cloud console.

Import data from Cloud SQL.

  curl -X POST \
  -H "Authorization: Bearer $(gcloud auth print-access-token)" \
  -H "Content-Type: application/json" \
  "https://discoveryengine.googleapis.com/v1/projects/PROJECT_ID/locations/global/collections/default_collection/dataStores/DATA_STORE_ID/branches/0/documents:import" \
  -d '{
    "cloudSqlSource": {
      "projectId": "SQL_PROJECT_ID",
      "instanceId": "INSTANCE_ID",
      "databaseId": "DATABASE_ID",
      "tableId": "TABLE_ID",
      "gcsStagingDir": "STAGING_DIRECTORY"
    },
    "reconciliationMode": "RECONCILIATION_MODE",
    "autoGenerateIds": "AUTO_GENERATE_IDS",
    "idField": "ID_FIELD",
  }'

Replace the following:

• PROJECT_ID: the ID of your Agentspace project.
• DATA_STORE_ID: the ID of the data store. The ID can contain only lowercase letters, digits, underscores, and hyphens.
• SQL_PROJECT_ID: the ID of your Cloud SQL project.
• INSTANCE_ID: the ID of your Cloud SQL instance.
• DATABASE_ID: the ID of your Cloud SQL database.
• TABLE_ID: the ID of your Cloud SQL table.
• STAGING_DIRECTORY: optional. A Cloud Storage directory—for example, gs://<your-gcs-bucket>/directory/import_errors.
• RECONCILIATION_MODE: optional. Values are FULL and INCREMENTAL. Default is INCREMENTAL. Specifying INCREMENTAL causes an incremental refresh of data from Cloud SQL to your data store. This does an upsert operation, which adds new documents and replaces existing documents with updated documents with the same ID. Specifying FULL causes a full rebase of the documents in your data store. In other words, new and updated documents are added to your data store, and documents that are not in Cloud SQL are removed from your data store. The FULL mode is helpful if you want to automatically delete documents that you no longer need.