JDBC to BigQuery template

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 gcloud storage 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
          

• DATASET and TABLE: Required. Destination BigQuery dataset and table.
• 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
  • JDBC_PASSWORD

  Construct the JDBC_CONNECTION_URL using one of the following connector-specific formats:

  • MySQL:

    jdbc:mysql://JDBC_HOST:JDBC_PORT/JDBC_DATABASE?user=JDBC_USERNAME&password=JDBC_PASSWORD
              

  • Postgres SQL:

    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: Required. SQL Query to extract data from JDBC.
• MODE: Required. Write mode for BigQuery output. Options: append, overwrite, ignore, or errorifexists.
• TEMP_BUCKET: Required. Cloud Storage bucket name. This bucket is used for BigQuery loading.

  Example: gs://dataproc-templates/jdbc_to_cloud_storage_output

• INPUT_PARTITION_COLUMN, LOWERBOUND, UPPERBOUND, 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.
  • 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.
• TEMPVIEW and SQL_QUERY: Optional. You can use these two optional parameters to apply a Spark SQL transformation while loading data into BigQuery. TEMPVIEW is the temporary view name, and SQL_QUERY is the query statement. TEMPVIEW and the table name in SQL_QUERY must match.
• 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 encryption key.

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

Execute the following command:

gcloud dataproc batches submit spark \
    --class=com.google.cloud.dataproc.templates.main.DataProcTemplate \
    --version="1.2" \
    --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=JDBCTOBIGQUERY \
    --templateProperty log.level="LOG_LEVEL" \
    --templateProperty jdbctobq.bigquery.location="DATASET.TABLE" \
    --templateProperty jdbctobq.jdbc.url="JDBC_CONNECTION_URL" \
    --templateProperty jdbctobq.jdbc.driver.class.name="DRIVER" \
    --templateProperty jdbctobq.write.mode="MODE" \
    --templateProperty jdbctobq.temp.gcs.bucket="TEMP_BUCKET" \
    --templateProperty jdbctobq.sql="QUERY" \
    --templateProperty jdbctobq.sql.numPartitions="PARTITIONS" \
    --templateProperty jdbctobq.sql.partitionColumn="INPUT_PARTITION_COLUMN" \
    --templateProperty jdbctobq.sql.lowerBound="LOWERBOUND" \
    --templateProperty jdbctobq.sql.upperBound="UPPERBOUND" \
    --templateProperty jdbctobq.jdbc.fetchsize="FETCHSIZE" \
    --templateProperty jdbctobq.temp.table="TEMPVIEW" \
    --templateProperty jdbctobq.temp.query="SQL_QUERY"

gcloud dataproc batches submit spark `
    --class=com.google.cloud.dataproc.templates.main.DataProcTemplate `
    --version="1.2" `
    --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=JDBCTOBIGQUERY `
    --templateProperty log.level="LOG_LEVEL" `
    --templateProperty jdbctobq.bigquery.location="DATASET.TABLE" `
    --templateProperty jdbctobq.jdbc.url="JDBC_CONNECTION_URL" `
    --templateProperty jdbctobq.jdbc.driver.class.name="DRIVER" `
    --templateProperty jdbctobq.write.mode="MODE" `
    --templateProperty jdbctobq.temp.gcs.bucket="TEMP_BUCKET" `
    --templateProperty jdbctobq.sql="QUERY" `
    --templateProperty jdbctobq.sql.numPartitions="PARTITIONS" `
    --templateProperty jdbctobq.sql.partitionColumn="INPUT_PARTITION_COLUMN" `
    --templateProperty jdbctobq.sql.lowerBound="LOWERBOUND" `
    --templateProperty jdbctobq.sql.upperBound="UPPERBOUND" `
    --templateProperty jdbctobq.jdbc.fetchsize="FETCHSIZE" `
    --templateProperty jdbctobq.temp.table="TEMPVIEW" `
    --templateProperty jdbctobq.temp.query="SQL_QUERY"

gcloud dataproc batches submit spark ^
    --class=com.google.cloud.dataproc.templates.main.DataProcTemplate ^
    --version="1.2" ^
    --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=JDBCTOBIGQUERY ^
    --templateProperty log.level="LOG_LEVEL" ^
    --templateProperty jdbctobq.bigquery.location="DATASET.TABLE" ^
    --templateProperty jdbctobq.jdbc.url="JDBC_CONNECTION_URL" ^
    --templateProperty jdbctobq.jdbc.driver.class.name="DRIVER" ^
    --templateProperty jdbctobq.write.mode="MODE" ^
    --templateProperty jdbctobq.temp.gcs.bucket="TEMP_BUCKET" ^
    --templateProperty jdbctobq.sql="QUERY" ^
    --templateProperty jdbctobq.sql.numPartitions="PARTITIONS" ^
    --templateProperty jdbctobq.sql.partitionColumn="INPUT_PARTITION_COLUMN" ^
    --templateProperty jdbctobq.sql.lowerBound="LOWERBOUND" ^
    --templateProperty jdbctobq.sql.upperBound="UPPERBOUND" ^
    --templateProperty jdbctobq.jdbc.fetchsize="FETCHSIZE" ^
    --templateProperty jdbctobq.temp.table="TEMPVIEW" ^
    --templateProperty jdbctobq.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 gcloud storage 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
          

• DATASET and TABLE: Required. Destination BigQuery dataset and table.
• 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
  • JDBC_PASSWORD

  Construct the JDBC_CONNECTION_URL using one of the following connector-specific formats:

  • MySQL:

    jdbc:mysql://JDBC_HOST:JDBC_PORT/JDBC_DATABASE?user=JDBC_USERNAME&password=JDBC_PASSWORD
              

  • Postgres SQL:

    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: Required. SQL Query to extract data from JDBC.
• MODE: Required. Write mode for BigQuery output. Options: append, overwrite, ignore, or errorifexists.
• TEMP_BUCKET: Required. Cloud Storage bucket name. This bucket is used for BigQuery loading.

  Example: gs://dataproc-templates/jdbc_to_cloud_storage_output

• INPUT_PARTITION_COLUMN, LOWERBOUND, UPPERBOUND, 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.
  • 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.
• TEMPVIEW and SQL_QUERY: Optional. You can use these two optional parameters to apply a Spark SQL transformation while loading data into BigQuery. TEMPVIEW is the temporary view name, and SQL_QUERY is the query statement. TEMPVIEW and the table name in SQL_QUERY must match.
• 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 encryption 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": "1.2",
    "properties": {
      "PROPERTY": "PROPERTY_VALUE"
    }
  },
  "sparkBatch": {
    "mainClass": "com.google.cloud.dataproc.templates.main.DataProcTemplate",
    "args": [
      "--template","JDBCTOBIGQUERY",
      "--templateProperty","log.level=LOG_LEVEL",
      "--templateProperty","jdbctobq.bigquery.location=DATASET.TABLE",
      "--templateProperty","jdbctobq.jdbc.url=JDBC_CONNECTION_URL",
      "--templateProperty","jdbctobq.jdbc.driver.class.name=DRIVER",
      "--templateProperty","jdbctobq.sql=QUERY",
      "--templateProperty","jdbctobq.write.mode=MODE",
      "--templateProperty","jdbctobq.temp.gcs.bucket=TEMP_BUCKET",
      "--templateProperty","jdbctobq.sql.partitionColumn=INPUT_PARTITION_COLUMN",
      "--templateProperty","jdbctobq.sql.lowerBound=LOWERBOUND",
      "--templateProperty","jdbctobq.sql.upperBound=UPPERBOUND",
      "--templateProperty","jdbctobq.sql.numPartitions=PARTITIONS",
      "--templateProperty","jdbctobq.jdbc.fetchsize=FETCHSIZE"
    ],
    "jarFileUris": [
      "gs://dataproc-templates-binaries/TEMPLATE_VERSION/java/dataproc-templates.jar","gs://JDBC_CONNECTOR_GCS_PATH"
    ]
  }
}

To send your request, expand one of these options:

curl -X POST \
     -H "Authorization: Bearer $(gcloud auth print-access-token)" \
     -H "Content-Type: application/json; charset=utf-8" \
     -d @request.json \
     "https://dataproc.googleapis.com/v1/projects/PROJECT_ID/locations/REGION/batches"

$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred" }

Invoke-WebRequest `
    -Method POST `
    -Headers $headers `
    -ContentType: "application/json; charset=utf-8" `
    -InFile request.json `
    -Uri "https://dataproc.googleapis.com/v1/projects/PROJECT_ID/locations/REGION/batches" | Select-Object -Expand Content

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"
  }
}