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.
Template parameters
Required parameters
- instanceId : The instance ID of the Cloud Spanner database that you want to import to.
- databaseId : The database ID of the Cloud Spanner database that you want to import into (must already exist).
- inputDir : The Cloud Storage path where the Avro files should be imported from.
Optional parameters
- spannerHost : The Cloud Spanner endpoint to call in the template. Only used for testing. (Example: https://batch-spanner.googleapis.com). Defaults to: https://batch-spanner.googleapis.com.
- waitForIndexes : 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.
- waitForForeignKeys : 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.
- waitForChangeStreams : 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.
- waitForSequences : By default the import pipeline is blocked on sequence creation. If false, it may complete with sequences still being created in the background.
- earlyIndexCreateFlag : 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. Defaults to: true.
- spannerProjectId : The project ID of the Cloud Spanner instance.
- ddlCreationTimeoutInMinutes : DDL Creation timeout in minutes. Defaults to: 30.
- spannerPriority : The request priority for Cloud Spanner calls. The value must be one of: [HIGH,MEDIUM,LOW].
Run the template
Console
- Go to the Dataflow Create job from template page. Go to Create job from template
- 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 IDSPANNER_DATABASE_NAME
: your Spanner database's name
- 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.
- From the Dataflow template drop-down menu, select the Avro Files on Cloud Storage to Cloud Spanner template.
- In the provided parameter fields, enter your parameter values.
- 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/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 choiceVERSION
: the version of the template that you want to useYou 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/
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 databaseDATABASE_ID
: the ID of the Spanner database to import toGCS_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 jobJOB_NAME
: a unique job name of your choiceVERSION
: the version of the template that you want to useYou 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/
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 databaseDATABASE_ID
: the ID of the Spanner database to import toGCS_DIRECTORY
: the Cloud Storage path where the Avro files are imported from, for example,gs://mybucket/somefolder
What's next
- Learn about Dataflow templates.
- See the list of Google-provided templates.