The Spanner to Avro Files on Cloud Storage template is a batch pipeline that exports a whole Spanner database to Cloud Storage in Avro format. Exporting a Spanner database creates a folder in the bucket you select. The folder contains:
- A
spanner-export.json
file. - A
TableName-manifest.json
file for each table in the database you exported. - One or more
TableName.avro-#####-of-#####
files.
For example, exporting a database with two tables, Singers
and Albums
,
creates the following file set:
Albums-manifest.json
Albums.avro-00000-of-00002
Albums.avro-00001-of-00002
Singers-manifest.json
Singers.avro-00000-of-00003
Singers.avro-00001-of-00003
Singers.avro-00002-of-00003
spanner-export.json
Pipeline requirements
- The Spanner database must exist.
- The output Cloud Storage bucket must exist.
- In addition to the Identity and Access Management (IAM) roles necessary to run Dataflow jobs, you must also have the appropriate IAM roles for reading your Spanner data and writing to your Cloud Storage bucket.
Template parameters
Required parameters
- instanceId : The instance ID of the Spanner database that you want to export.
- databaseId : The database ID of the Spanner database that you want to export.
- outputDir : The Cloud Storage path to export Avro files to. The export job creates a new directory under this path that contains the exported files. (Example: gs://your-bucket/your-path).
Optional parameters
- avroTempDirectory : The Cloud Storage path where temporary Avro files are written.
- 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.
- snapshotTime : The timestamp that corresponds to the version of the Spanner database that you want to read. The timestamp must be specified by using RFC 3339 UTC
Zulu
format. The timestamp must be in the past, and maximum timestamp staleness applies. (Example: 1990-12-31T23:59:60Z). Defaults to empty. - spannerProjectId : The ID of the Google Cloud project that contains the Spanner database that you want to read data from.
- shouldExportTimestampAsLogicalType : If true, timestamps are exported as a
long
type withtimestamp-micros
logical type. By default, this parameter is set tofalse
and timestamps are exported as ISO-8601 strings at nanosecond precision. - tableNames : A comma-separated list of tables specifying the subset of the Spanner database to export. If you set this parameter, you must either include all of the related tables (parent tables and foreign key referenced tables) or set the
shouldExportRelatedTables
parameter totrue
.If the table is in named schema, please use fully qualified name. For example:sch1.foo
in whichsch1
is the schema name andfoo
is the table name. Defaults to empty. - shouldExportRelatedTables : Whether to include related tables. This parameter is used in conjunction with the
tableNames
parameter. Defaults to: false. - spannerPriority : The request priority for Spanner calls. Possible values are
HIGH
,MEDIUM
, andLOW
. The default value isMEDIUM
. - dataBoostEnabled : Set to
true
to use the compute resources of Spanner Data Boost to run the job with near-zero impact on Spanner OLTP workflows. When set totrue
, you also need thespanner.databases.useDataBoost
IAM permission. For more information, see the Data Boost overview (https://cloud.google.com/spanner/docs/databoost/databoost-overview). Defaults to: false.
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-export-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 Cloud Spanner to Avro Files on Cloud Storage 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/Cloud_Spanner_to_GCS_Avro \ --region REGION_NAME \ --staging-location GCS_STAGING_LOCATION \ --parameters \ instanceId=INSTANCE_ID,\ databaseId=DATABASE_ID,\ outputDir=GCS_DIRECTORY
Replace the following:
JOB_NAME
: a unique job name of your choiceFor the job to show in the Spanner portion of the Google Cloud console, the job name must match the format
cloud-spanner-export-INSTANCE_ID-DATABASE_ID
.VERSION
: 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
GCS_STAGING_LOCATION
: the path for writing temporary files; for example,gs://mybucket/temp
INSTANCE_ID
: your Spanner instance IDDATABASE_ID
: your Spanner database IDGCS_DIRECTORY
: the Cloud Storage path that the Avro files are exported to
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/Cloud_Spanner_to_GCS_Avro { "jobName": "JOB_NAME", "parameters": { "instanceId": "INSTANCE_ID", "databaseId": "DATABASE_ID", "outputDir": "gs://GCS_DIRECTORY" } }
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 choiceFor the job to show in the Spanner portion of the Google Cloud console, the job name must match the format
cloud-spanner-export-INSTANCE_ID-DATABASE_ID
.VERSION
: 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
GCS_STAGING_LOCATION
: the path for writing temporary files; for example,gs://mybucket/temp
INSTANCE_ID
: your Spanner instance IDDATABASE_ID
: your Spanner database IDGCS_DIRECTORY
: the Cloud Storage path that the Avro files are exported to
What's next
- Learn about Dataflow templates.
- See the list of Google-provided templates.