JDBC to Cloud Storage template

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

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.
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
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=

DRIVER: Required. The JDBC driver that is 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

FORMAT: Required. Output data format. Options: avro, parquet, csv, or json. Default: avro. Note: If avro, you must add "file:///usr/lib/spark/external/spark-avro.jar" to the jars gcloud CLI flag or API field.
Example (the file:// prefix references a Dataproc Serverless jar file):
--jars=file:///usr/lib/spark/external/spark-avro.jar, [, ... other jars]
MODE: Required. Write mode for Cloud Storage output. Options: append, overwrite, ignore, or errorifexists.
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).
CLOUD_STORAGE_OUTPUT_PATH: Required. Cloud Storage path where output will be stored.
Example: gs://dataproc-templates/jdbc_to_cloud_storage_output
LOG_LEVEL: Optional. Level of logging. Can be one of ALL, DEBUG, ERROR, FATAL, INFO, OFF, TRACE, or WARN. Default: INFO.
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.
OUTPUT_PARTITION_COLUMN: Optional. Output partition column name.
FETCHSIZE: Optional. How many rows to fetch per round trip. Default: 10.
QUERY or QUERY_FILE: Required. Set either QUERY or QUERY_FILE to specify the query to use to extract data from JDBC
TEMP_VIEW and TEMP_QUERY: Optional. You can use these two optional parameters to apply a Spark SQL transformation while loading data into Cloud Storage. TEMPVIEW must be the same as table name used in query, and TEMP_QUERY is the query statement.
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.
JDBC_SESSION_INIT: Optional. Session initialization statement to read Java templates.
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-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 \
    --project="PROJECT_ID" \
    --region="REGION" \
    --version="1.1" \
    --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=JDBCTOGCS \
    --templateProperty project.id="PROJECT_ID" \
    --templateProperty log.level="LOG_LEVEL" \
    --templateProperty jdbctogcs.jdbc.url="JDBC_CONNECTION_URL" \
    --templateProperty jdbctogcs.jdbc.driver.class.name="DRIVER" \
    --templateProperty jdbctogcs.output.format="FORMAT" \
    --templateProperty jdbctogcs.output.location="CLOUD_STORAGE_OUTPUT_PATH" \
    --templateProperty jdbctogcs.sql="QUERY" \
    --templateProperty jdbctogcs.sql.file="QUERY_FILE" \
    --templateProperty jdbctogcs.sql.partitionColumn="INPUT_PARTITION_COLUMN" \
    --templateProperty jdbctogcs.sql.lowerBound="LOWERBOUND" \
    --templateProperty jdbctogcs.sql.upperBound="UPPERBOUND" \
    --templateProperty jdbctogcs.jdbc.fetchsize="FETCHSIZE" \
    --templateProperty jdbctogcs.sql.numPartitions="NUM_PARTITIONS" \
    --templateProperty jdbctogcs.write.mode="MODE" \
    --templateProperty dbctogcs.output.partition.col="OUTPUT_PARTITION_COLUMN" \
    --templateProperty jdbctogcs.temp.table="TEMP_VIEW" \
    --templateProperty jdbctogcs.temp.query="TEMP_QUERY"

Windows (PowerShell)

gcloud dataproc batches submit spark `
    --class=com.google.cloud.dataproc.templates.main.DataProcTemplate `
    --project="PROJECT_ID" `
    --region="REGION" `
    --version="1.1" `
    --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=JDBCTOGCS `
    --templateProperty project.id="PROJECT_ID" `
    --templateProperty log.level="LOG_LEVEL" `
    --templateProperty jdbctogcs.jdbc.url="JDBC_CONNECTION_URL" `
    --templateProperty jdbctogcs.jdbc.driver.class.name="DRIVER" `
    --templateProperty jdbctogcs.output.format="FORMAT" `
    --templateProperty jdbctogcs.output.location="CLOUD_STORAGE_OUTPUT_PATH" `
    --templateProperty jdbctogcs.sql="QUERY" `
    --templateProperty jdbctogcs.sql.file="QUERY_FILE" `
    --templateProperty jdbctogcs.sql.partitionColumn="INPUT_PARTITION_COLUMN" `
    --templateProperty jdbctogcs.sql.lowerBound="LOWERBOUND" `
    --templateProperty jdbctogcs.sql.upperBound="UPPERBOUND" `
    --templateProperty jdbctogcs.jdbc.fetchsize="FETCHSIZE" `
    --templateProperty jdbctogcs.sql.numPartitions="NUM_PARTITIONS" `
    --templateProperty jdbctogcs.write.mode="MODE" `
    --templateProperty dbctogcs.output.partition.col="OUTPUT_PARTITION_COLUMN" `
    --templateProperty jdbctogcs.temp.table="TEMP_VIEW" `
    --templateProperty jdbctogcs.temp.query="TEMP_QUERY"

Windows (cmd.exe)

gcloud dataproc batches submit spark ^
    --class=com.google.cloud.dataproc.templates.main.DataProcTemplate ^
    --project="PROJECT_ID" ^
    --region="REGION" ^
    --version="1.1" ^
    --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=JDBCTOGCS ^
    --templateProperty project.id="PROJECT_ID" ^
    --templateProperty log.level="LOG_LEVEL" ^
    --templateProperty jdbctogcs.jdbc.url="JDBC_CONNECTION_URL" ^
    --templateProperty jdbctogcs.jdbc.driver.class.name="DRIVER" ^
    --templateProperty jdbctogcs.output.format="FORMAT" ^
    --templateProperty jdbctogcs.output.location="CLOUD_STORAGE_OUTPUT_PATH" ^
    --templateProperty jdbctogcs.sql="QUERY" ^
    --templateProperty jdbctogcs.sql.file="QUERY_FILE" ^
    --templateProperty jdbctogcs.sql.partitionColumn="INPUT_PARTITION_COLUMN" ^
    --templateProperty jdbctogcs.sql.lowerBound="LOWERBOUND" ^
    --templateProperty jdbctogcs.sql.upperBound="UPPERBOUND" ^
    --templateProperty jdbctogcs.jdbc.fetchsize="FETCHSIZE" ^
    --templateProperty jdbctogcs.sql.numPartitions="NUM_PARTITIONS" ^
    --templateProperty jdbctogcs.write.mode="MODE" ^
    --templateProperty dbctogcs.output.partition.col="OUTPUT_PARTITION_COLUMN" ^
    --templateProperty jdbctogcs.temp.table="TEMP_VIEW" ^
    --templateProperty jdbctogcs.temp.query="TEMP_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.
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

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
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=

DRIVER: Required. The JDBC driver that is 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

FORMAT: Required. Output data format. Options: avro, parquet, csv, or json. Default: avro. Note: If avro, you must add "file:///usr/lib/spark/external/spark-avro.jar" to the jars gcloud CLI flag or API field.
Example (the file:// prefix references a Dataproc Serverless jar file):
--jars=file:///usr/lib/spark/external/spark-avro.jar, [, ... other jars]
MODE: Required. Write mode for Cloud Storage output. Options: append, overwrite, ignore, or errorifexists.
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).
CLOUD_STORAGE_OUTPUT_PATH: Required. Cloud Storage path where output will be stored.
Example: gs://dataproc-templates/jdbc_to_cloud_storage_output
LOG_LEVEL: Optional. Level of logging. Can be one of ALL, DEBUG, ERROR, FATAL, INFO, OFF, TRACE, or WARN. Default: INFO.
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.
OUTPUT_PARTITION_COLUMN: Optional. Output partition column name.
FETCHSIZE: Optional. How many rows to fetch per round trip. Default: 10.
QUERY or QUERY_FILE: Required. Set either QUERY or QUERY_FILE to specify the query to use to extract data from JDBC
TEMP_VIEW and TEMP_QUERY: Optional. You can use these two optional parameters to apply a Spark SQL transformation while loading data into Cloud Storage. TEMPVIEW must be the same as table name used in query, and TEMP_QUERY is the query statement.
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.
JDBC_SESSION_INIT: Optional. Session initialization statement to read Java templates.
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-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=JDBCTOGCS",
      "--templateProperty","log.level=LOG_LEVEL",
      "--templateProperty","project.id=PROJECT_ID",
      "--templateProperty","jdbctogcs.jdbc.url=JDBC_CONNECTION_URL",
      "--templateProperty","jdbctogcs.jdbc.driver.class.name=DRIVER",
      "--templateProperty","jdbctogcs.output.location=CLOUD_STORAGE_OUTPUT_PATH",
      "--templateProperty","jdbctogcs.write.mode=MODE",
      "--templateProperty","jdbctogcs.output.format=FORMAT",
      "--templateProperty","jdbctogcs.sql.numPartitions=NUM_PARTITIONS",
      "--templateProperty","jdbctogcs.jdbc.fetchsize=FETCHSIZE",
      "--templateProperty","jdbctogcs.sql=QUERY",
      "--templateProperty","jdbctogcs.sql.file=QUERY_FILE",
      "--templateProperty","jdbctogcs.sql.partitionColumn=INPUT_PARTITION_COLUMN",
      "--templateProperty","jdbctogcs.sql.lowerBound=LOWERBOUND",
      "--templateProperty","jdbctogcs.sql.upperBound=UPPERBOUND",
      "--templateProperty","jdbctogcs.output.partition.col=OUTPUT_PARTITION_COLUMN",
      "--templateProperty","jdbctogcs.temp.table=TEMP_VIEW",
      "--templateProperty","jdbctogcs.temp.query=TEMP_QUERY",
      "--templateProperty","jdbctogcs.jdbc.sessioninitstatement=JDBC_SESSION_INIT"
    ],
    "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:

curl (Linux, macOS, or Cloud Shell)

Note: The following command assumes that you have logged in to the gcloud CLI with your user account by running gcloud init or gcloud auth login , or by using Cloud Shell, which automatically logs you into the gcloud CLI . You can check the currently active account by running gcloud auth list.

Save the request body in a file named request.json, and execute the following command:

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"

PowerShell (Windows)

Note: The following command assumes that you have logged in to the gcloud CLI with your user account by running gcloud init or gcloud auth login . You can check the currently active account by running gcloud auth list.

Save the request body in a file named request.json, and execute the following command:

$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"
  }
}