JDBC to Cloud Spanner template

Use the Dataproc Serverless JDBC to Spanner template to extract data from JDBC databases to Spanner.

This template supports the following databases as input:

  • MySQL
  • PostgreSQL
  • Microsoft SQL Server
  • Oracle

Use the template

Run the template using the gcloud CLI or Dataproc API.

gcloud

Before using any of the command data below, make the following replacements:

  • PROJECT_ID : Required. Your Google Cloud project ID listed in the IAM Settings .
  • REGION : Required. Compute Engine region .
  • TEMPLATE_VERSION : Required. Specify latest for the latest template version, or the date of a specific version, for example, 2023-03-17_v0.1.0-beta (visit gs://dataproc-templates-binaries or run gsutil ls gs://dataproc-templates-binaries to list available template versions).
  • SUBNET : Optional. If a subnet is not specified, the subnet in the specified REGION in the default network is selected.

    Example: projects/ PROJECT_ID /regions/ REGION /subnetworks/ SUBNET_NAME

  • JDBC_CONNECTOR_CLOUD_STORAGE_PATH : Required. The full Cloud Storage path, including the filename, where the JDBC connector jar is stored. You can use the following commands to download JDBC connectors for uploading to Cloud Storage:
    • MySQL: 
       wget http://dev.mysql.com/get/Downloads/Connector-J/mysql-connector-java-5.1.30.tar.gz
    • Postgres SQL: 
       wget https://jdbc.postgresql.org/download/postgresql-42.2.6.jar
    • Microsoft SQL Server: 
       wget https://repo1.maven.org/maven2/com/microsoft/sqlserver/mssql-jdbc/6.4.0.jre8/mssql-jdbc-6.4.0.jre8.jar
    • Oracle: 
       wget https://repo1.maven.org/maven2/com/oracle/database/jdbc/ojdbc8/21.7.0.0/ojdbc8-21.7.0.0.jar
  • The following variables are used to construct the required JDBC_CONNECTION_URL :
    • JDBC_HOST , JDBC_PORT , JDBC_DATABASE , or, for Oracle, JDBC_SERVICE , JDBC_USERNAME , and JDBC_PASSWORD : Required. JDBC host, port, database, username, and password.
      • MySQL: 
         jdbc:mysql:// JDBC_HOST 
: JDBC_PORT 
/ JDBC_DATABASE 
?user= JDBC_USERNAME 
&password= JDBC_PASSWORD
      • PostgreSQL: 
         jdbc:postgresql:// JDBC_HOST 
: JDBC_PORT 
/ JDBC_DATABASE 
?user= JDBC_USERNAME 
&password= JDBC_PASSWORD
      • Microsoft SQL Server: 
         jdbc:sqlserver:// JDBC_HOST 
: JDBC_PORT 
;databaseName= JDBC_DATABASE 
;user= JDBC_USERNAME 
;password= JDBC_PASSWORD
      • Oracle: 
         jdbc:oracle:thin:@// JDBC_HOST 
: JDBC_PORT 
/ JDBC_SERVICE 
?user= JDBC_USERNAME 
&password= JDBC_PASSWORD
    • DRIVER : Required. The JDBC driver which will be used for the connection:
      • MySQL: 
         com.mysql.cj.jdbc.Driver
      • Postgres SQL: 
         org.postgresql.Driver
      • Microsoft SQL Server: 
         com.microsoft.sqlserver.jdbc.SQLServerDriver
      • Oracle: 
         oracle.jdbc.driver.OracleDriver
    • QUERY or QUERY_FILE : Required. Set either QUERY or QUERY_FILE to specify the query to use to extract data from JDBC
    • INPUT_PARTITION_COLUMN , LOWERBOUND , UPPERBOUND , NUM_PARTITIONS : Optional. If used, all of the following parameters must be specified:
      • INPUT_PARTITION_COLUMN: JDBC input table partition column name.
      • LOWERBOUND: JDBC input table partition column lower bound used to determine the partition stride.
      • UPPERBOUND:JDBC input table partition column upper bound used to decide the partition stride.
      • NUM_PARTITIONS:The maximum number of partitions that can be used for parallelism of table reads and writes. If specified, this value is used for the JDBC input and output connection. Default: 10 .
    • FETCHSIZE : Optional. How many rows to fetch per round trip. Default: 10.
    • JDBC_SESSION_INIT : Optional. Session initialization statement to read Java templates.
    • TEMPVIEW and SQL_QUERY : Optional. You can use these two optional parameters to apply a Spark SQL transformation while loading data into Spanner. TEMPVIEW is the temporary view name, and SQL_QUERY is the query statement. TEMPVIEW and the table name in SQL_QUERY must match.
    • INSTANCE : Required. Spanner instance ID.
    • SPANNER_DATABASE : Required. Spanner database ID.
    • TABLE : Required. Spanner output table name.
    • MODE : Optional. Write mode for Spanner output. Options: Append , Overwrite , Ignore , or ErrorIfExists . Defaults to ErrorIfExists .
    • PRIMARY_KEY : Required. Comma separated Primary key columns needed when creating Spanner output table.
    • SERVICE_ACCOUNT : Optional. If not provided, the default Compute Engine service account is used.
    • PROPERTY and PROPERTY_VALUE : Optional. Comma-separated list of Spark property = value pairs.
    • LABEL and LABEL_VALUE : Optional. Comma-separated list of label = value pairs.
    • LOG_LEVEL : Optional. Level of logging. Can be one of ALL , DEBUG , ERROR , FATAL , INFO , OFF , TRACE , or WARN . Default: INFO .
    • KMS_KEY : Optional. The Cloud Key Management Service key to use for encryption. If a key is not specified, data is encrypted at rest using a Google-owned and Google-managed key.

      Example: projects/ PROJECT_ID /regions/ REGION /keyRings/ KEY_RING_NAME /cryptoKeys/ KEY_NAME

    Execute the following command:

    Linux, macOS, or Cloud Shell

    gcloud dataproc batches submit spark \
    --class=com.google.cloud.dataproc.templates.main.DataProcTemplate \
    --version="1.1" \
    --project=" PROJECT_ID 
" \
    --region=" REGION 
" \
    --jars="gs://dataproc-templates-binaries/ TEMPLATE_VERSION 
/java/dataproc-templates.jar, JDBC_CONNECTOR_CLOUD_STORAGE_PATH 
" \
    --subnet=" SUBNET 
" \
    --kms-key=" KMS_KEY 
" \
    --service-account=" SERVICE_ACCOUNT 
" \
    --properties=" PROPERTY 
= PROPERTY_VALUE 
" \
    --labels=" LABEL 
= LABEL_VALUE 
" \
    -- --template=JDBCTOSPANNER \
    --templateProperty log.level=" LOG_LEVEL 
" \
    --templateProperty project.id=" PROJECT_ID 
" \
    --templateProperty jdbctospanner.jdbc.url=" JDBC_CONNECTION_URL 
" \
    --templateProperty jdbctospanner.jdbc.driver.class.name=" DRIVER 
" \
    --templateProperty jdbctospanner.jdbc.fetchsize=" FETCHSIZE 
" \
    --templateProperty jdbctospanner.jdbc.sessioninitstatement=" JDBC_SESSION_INIT 
" \
    --templateProperty jdbctospanner.sql=" QUERY 
" \
    --templateProperty jdbctospanner.sql.file=" QUERY_FILE 
" \
    --templateProperty jdbctospanner.sql.numPartitions=" NUM_PARTITIONS 
" \
    --templateProperty jdbctospanner.sql.partitionColumn=" INPUT_PARTITION_COLUMN 
" \
    --templateProperty jdbctospanner.sql.lowerBound=" LOWERBOUND 
" \
    --templateProperty jdbctospanner.sql.upperBound=" UPPERBOUND 
" \
    --templateProperty jdbctospanner.output.instance=" INSTANCE 
" \
    --templateProperty jdbctospanner.output.database=" SPANNER_DATABASE 
" \
    --templateProperty jdbctospanner.output.table=" TABLE 
" \
    --templateProperty jdbctospanner.output.saveMode=" MODE 
" \
    --templateProperty jdbctospanner.output.primaryKey=" PRIMARY_KEY 
" \
    --templateProperty jdbctospanner.output.batch.size=" BATCHSIZE 
" \
    --templateProperty jdbctospanner.temp.table=" TEMPVIEW 
" \
    --templateProperty jdbctospanner.temp.query=" SQL_QUERY 
"

    Windows (PowerShell)

    gcloud dataproc batches submit spark `
    --class=com.google.cloud.dataproc.templates.main.DataProcTemplate `
    --version="1.1" `
    --project=" PROJECT_ID 
" `
    --region=" REGION 
" `
    --jars="gs://dataproc-templates-binaries/ TEMPLATE_VERSION 
/java/dataproc-templates.jar, JDBC_CONNECTOR_CLOUD_STORAGE_PATH 
" `
    --subnet=" SUBNET 
" `
    --kms-key=" KMS_KEY 
" `
    --service-account=" SERVICE_ACCOUNT 
" `
    --properties=" PROPERTY 
= PROPERTY_VALUE 
" `
    --labels=" LABEL 
= LABEL_VALUE 
" `
    -- --template=JDBCTOSPANNER `
    --templateProperty log.level=" LOG_LEVEL 
" `
    --templateProperty project.id=" PROJECT_ID 
" `
    --templateProperty jdbctospanner.jdbc.url=" JDBC_CONNECTION_URL 
" `
    --templateProperty jdbctospanner.jdbc.driver.class.name=" DRIVER 
" `
    --templateProperty jdbctospanner.jdbc.fetchsize=" FETCHSIZE 
" `
    --templateProperty jdbctospanner.jdbc.sessioninitstatement=" JDBC_SESSION_INIT 
" `
    --templateProperty jdbctospanner.sql=" QUERY 
" `
    --templateProperty jdbctospanner.sql.file=" QUERY_FILE 
" `
    --templateProperty jdbctospanner.sql.numPartitions=" NUM_PARTITIONS 
" `
    --templateProperty jdbctospanner.sql.partitionColumn=" INPUT_PARTITION_COLUMN 
" `
    --templateProperty jdbctospanner.sql.lowerBound=" LOWERBOUND 
" `
    --templateProperty jdbctospanner.sql.upperBound=" UPPERBOUND 
" `
    --templateProperty jdbctospanner.output.instance=" INSTANCE 
" `
    --templateProperty jdbctospanner.output.database=" SPANNER_DATABASE 
" `
    --templateProperty jdbctospanner.output.table=" TABLE 
" `
    --templateProperty jdbctospanner.output.saveMode=" MODE 
" `
    --templateProperty jdbctospanner.output.primaryKey=" PRIMARY_KEY 
" `
    --templateProperty jdbctospanner.output.batch.size=" BATCHSIZE 
" `
    --templateProperty jdbctospanner.temp.table=" TEMPVIEW 
" `
    --templateProperty jdbctospanner.temp.query=" SQL_QUERY 
"

    Windows (cmd.exe)

    gcloud dataproc batches submit spark ^
    --class=com.google.cloud.dataproc.templates.main.DataProcTemplate ^
    --version="1.1" ^
    --project=" PROJECT_ID 
" ^
    --region=" REGION 
" ^
    --jars="gs://dataproc-templates-binaries/ TEMPLATE_VERSION 
/java/dataproc-templates.jar, JDBC_CONNECTOR_CLOUD_STORAGE_PATH 
" ^
    --subnet=" SUBNET 
" ^
    --kms-key=" KMS_KEY 
" ^
    --service-account=" SERVICE_ACCOUNT 
" ^
    --properties=" PROPERTY 
= PROPERTY_VALUE 
" ^
    --labels=" LABEL 
= LABEL_VALUE 
" ^
    -- --template=JDBCTOSPANNER ^
    --templateProperty log.level=" LOG_LEVEL 
" ^
    --templateProperty project.id=" PROJECT_ID 
" ^
    --templateProperty jdbctospanner.jdbc.url=" JDBC_CONNECTION_URL 
" ^
    --templateProperty jdbctospanner.jdbc.driver.class.name=" DRIVER 
" ^
    --templateProperty jdbctospanner.jdbc.fetchsize=" FETCHSIZE 
" ^
    --templateProperty jdbctospanner.jdbc.sessioninitstatement=" JDBC_SESSION_INIT 
" ^
    --templateProperty jdbctospanner.sql=" QUERY 
" ^
    --templateProperty jdbctospanner.sql.file=" QUERY_FILE 
" ^
    --templateProperty jdbctospanner.sql.numPartitions=" NUM_PARTITIONS 
" ^
    --templateProperty jdbctospanner.sql.partitionColumn=" INPUT_PARTITION_COLUMN 
" ^
    --templateProperty jdbctospanner.sql.lowerBound=" LOWERBOUND 
" ^
    --templateProperty jdbctospanner.sql.upperBound=" UPPERBOUND 
" ^
    --templateProperty jdbctospanner.output.instance=" INSTANCE 
" ^
    --templateProperty jdbctospanner.output.database=" SPANNER_DATABASE 
" ^
    --templateProperty jdbctospanner.output.table=" TABLE 
" ^
    --templateProperty jdbctospanner.output.saveMode=" MODE 
" ^
    --templateProperty jdbctospanner.output.primaryKey=" PRIMARY_KEY 
" ^
    --templateProperty jdbctospanner.output.batch.size=" BATCHSIZE 
" ^
    --templateProperty jdbctospanner.temp.table=" TEMPVIEW 
" ^
    --templateProperty jdbctospanner.temp.query=" SQL_QUERY 
"

REST

Before using any of the request data, make the following replacements:

  • PROJECT_ID : Required. Your Google Cloud project ID listed in the IAM Settings .
  • REGION : Required. Compute Engine region .
  • TEMPLATE_VERSION : Required. Specify latest for the latest template version, or the date of a specific version, for example, 2023-03-17_v0.1.0-beta (visit gs://dataproc-templates-binaries or run gsutil ls gs://dataproc-templates-binaries to list available template versions).
  • SUBNET : Optional. If a subnet is not specified, the subnet in the specified REGION in the default network is selected.

    Example: projects/ PROJECT_ID /regions/ REGION /subnetworks/ SUBNET_NAME

  • JDBC_CONNECTOR_CLOUD_STORAGE_PATH : Required. The full Cloud Storage path, including the filename, where the JDBC connector jar is stored. You can use the following commands to download JDBC connectors for uploading to Cloud Storage:
    • MySQL: 
       wget http://dev.mysql.com/get/Downloads/Connector-J/mysql-connector-java-5.1.30.tar.gz
    • Postgres SQL: 
       wget https://jdbc.postgresql.org/download/postgresql-42.2.6.jar
    • Microsoft SQL Server: 
       wget https://repo1.maven.org/maven2/com/microsoft/sqlserver/mssql-jdbc/6.4.0.jre8/mssql-jdbc-6.4.0.jre8.jar
    • Oracle: 
       wget https://repo1.maven.org/maven2/com/oracle/database/jdbc/ojdbc8/21.7.0.0/ojdbc8-21.7.0.0.jar
  • The following variables are used to construct the required JDBC_CONNECTION_URL :
    • JDBC_HOST , JDBC_PORT , JDBC_DATABASE , or, for Oracle, JDBC_SERVICE , JDBC_USERNAME , and JDBC_PASSWORD : Required. JDBC host, port, database, username, and password.
      • MySQL: 
         jdbc:mysql:// JDBC_HOST 
: JDBC_PORT 
/ JDBC_DATABASE 
?user= JDBC_USERNAME 
&password= JDBC_PASSWORD
      • PostgreSQL: 
         jdbc:postgresql:// JDBC_HOST 
: JDBC_PORT 
/ JDBC_DATABASE 
?user= JDBC_USERNAME 
&password= JDBC_PASSWORD
      • Microsoft SQL Server: 
         jdbc:sqlserver:// JDBC_HOST 
: JDBC_PORT 
;databaseName= JDBC_DATABASE 
;user= JDBC_USERNAME 
;password= JDBC_PASSWORD
      • Oracle: 
         jdbc:oracle:thin:@// JDBC_HOST 
: JDBC_PORT 
/ JDBC_SERVICE 
?user= JDBC_USERNAME 
&password= JDBC_PASSWORD
    • DRIVER : Required. The JDBC driver which will be used for the connection:
      • MySQL: 
         com.mysql.cj.jdbc.Driver
      • Postgres SQL: 
         org.postgresql.Driver
      • Microsoft SQL Server: 
         com.microsoft.sqlserver.jdbc.SQLServerDriver
      • Oracle: 
         oracle.jdbc.driver.OracleDriver
    • QUERY or QUERY_FILE : Required. Set either QUERY or QUERY_FILE to specify the query to use to extract data from JDBC
    • INPUT_PARTITION_COLUMN , LOWERBOUND , UPPERBOUND , NUM_PARTITIONS : Optional. If used, all of the following parameters must be specified:
      • INPUT_PARTITION_COLUMN: JDBC input table partition column name.
      • LOWERBOUND: JDBC input table partition column lower bound used to determine the partition stride.
      • UPPERBOUND:JDBC input table partition column upper bound used to decide the partition stride.
      • NUM_PARTITIONS:The maximum number of partitions that can be used for parallelism of table reads and writes. If specified, this value is used for the JDBC input and output connection. Default: 10 .
    • FETCHSIZE : Optional. How many rows to fetch per round trip. Default: 10.
    • JDBC_SESSION_INIT : Optional. Session initialization statement to read Java templates.
    • TEMPVIEW and SQL_QUERY : Optional. You can use these two optional parameters to apply a Spark SQL transformation while loading data into Spanner. TEMPVIEW is the temporary view name, and SQL_QUERY is the query statement. TEMPVIEW and the table name in SQL_QUERY must match.
    • INSTANCE : Required. Spanner instance ID.
    • SPANNER_DATABASE : Required. Spanner database ID.
    • TABLE : Required. Spanner output table name.
    • MODE : Optional. Write mode for Spanner output. Options: Append , Overwrite , Ignore , or ErrorIfExists . Defaults to ErrorIfExists .
    • PRIMARY_KEY : Required. Comma separated Primary key columns needed when creating Spanner output table.
    • SERVICE_ACCOUNT : Optional. If not provided, the default Compute Engine service account is used.
    • PROPERTY and PROPERTY_VALUE : Optional. Comma-separated list of Spark property = value pairs.
    • LABEL and LABEL_VALUE : Optional. Comma-separated list of label = value pairs.
    • LOG_LEVEL : Optional. Level of logging. Can be one of ALL , DEBUG , ERROR , FATAL , INFO , OFF , TRACE , or WARN . Default: INFO .
    • KMS_KEY : Optional. The Cloud Key Management Service key to use for encryption. If a key is not specified, data is encrypted at rest using a Google-owned and Google-managed key.

      Example: projects/ PROJECT_ID /regions/ REGION /keyRings/ KEY_RING_NAME /cryptoKeys/ KEY_NAME

    HTTP method and URL:

    POST https://dataproc.googleapis.com/v1/projects/ PROJECT_ID 
/locations/ REGION 
/batches

    Request JSON body:

    {
  "environmentConfig": {
    "executionConfig": {
      "subnetworkUri": " SUBNET 
",
      "kmsKey": " KMS_KEY 
",
      "serviceAccount": " SERVICE_ACCOUNT 
"
    }
  },
  "labels": {
    " LABEL 
": " LABEL_VALUE 
"
  },
  "runtimeConfig": {
    "version": "1.1",
    "properties": {
      " PROPERTY 
": " PROPERTY_VALUE 
"
    }
  },
  "sparkBatch": {
    "mainClass": "com.google.cloud.dataproc.templates.main.DataProcTemplate",
    "args": [
      "--template","JDBCTOSPANNER",
      "--templateProperty","log.level= LOG_LEVEL 
",
      "--templateProperty","project.id= PROJECT_ID 
",
      "--templateProperty","jdbctospanner.jdbc.url= JDBC_CONNECTION_URL 
",
      "--templateProperty","jdbctospanner.jdbc.driver.class.name= DRIVER 
",
      "--templateProperty","jdbctospanner.jdbc.fetchsize= FETCHSIZE 
",
      "--templateProperty","jdbctospanner.jdbc.sessioninitstatement= JDBC_SESSION_INIT 
",
      "--templateProperty","jdbctospanner.sql= QUERY 
",
      "--templateProperty","jdbctospanner.sql.file= QUERY_FILE 
",
      "--templateProperty","jdbctospanner.sql.numPartitions= NUM_PARTITIONS 
",
      "--templateProperty","jdbctospanner.sql.partitionColumn= INPUT_PARTITION_COLUMN 
",
      "--templateProperty","jdbctospanner.sql.lowerBound= LOWERBOUND 
",
      "--templateProperty","jdbctospanner.sql.upperBound= UPPERBOUND 
",
      "--templateProperty","jdbctospanner.output.instance= INSTANCE 
",
      "--templateProperty","jdbctospanner.output.database= SPANNER_DATABASE 
",
      "--templateProperty","jdbctospanner.output.table= TABLE 
",
      "--templateProperty","jdbctospanner.output.saveMode= MODE 
",
      "--templateProperty","jdbctospanner.output.primaryKey= PRIMARY_KEY 
",
      "--templateProperty","jdbctospanner.output.batch.size= BATCHSIZE 
",
      "--templateProperty","jdbctospanner.temp.table= TEMPVIEW 
",
      "--templateProperty","jdbctospanner.temp.query= SQL_QUERY 
" 
    ],
    "jarFileUris": [
      "gs://dataproc-templates-binaries/ TEMPLATE_VERSION 
/java/dataproc-templates.jar"," JDBC_CONNECTOR_CLOUD_STORAGE_PATH 
"
    ]
  }
}

    To send your request, expand one of these options:

    You should receive a JSON response similar to the following:

    {
  "name": "projects/ PROJECT_ID 
/regions/ REGION 
/operations/ OPERATION_ID 
",
  "metadata": {
    "@type": "type.googleapis.com/google.cloud.dataproc.v1.BatchOperationMetadata",
    "batch": "projects/ PROJECT_ID 
/locations/ REGION 
/batches/ BATCH_ID 
",
    "batchUuid": "de8af8d4-3599-4a7c-915c-798201ed1583",
    "createTime": "2023-02-24T03:31:03.440329Z",
    "operationType": "BATCH",
    "description": "Batch"
  }
}