Troubleshooting
Problem
This issue occurs when the JDBC Connection String provided in the stage configuration does not correspond to a JDBC driver class that StreamSets Transformer for Spark can automatically detect. StreamSets Transformer for Spark can automatically detect drivers for the following databases:
Apache Derby
IBM DB2
Microsoft SQL Server
MySQL
Oracle
PostgreSQL
Teradata
If you are using a JDBC URL that corresponds to one of these databases and still encounter the error, ensure that the connection string is correctly formatted.
For other databases, or if you are using a custom JDBC driver, Transformer for Spark cannot automatically detect the driver class. In such cases, you must manually specify the JDBC driver class name.
Symptom
The error may appear in JDBC stages when attempting to connect to a database. The error message indicates that StreamSets Transformer for Spark is unable to auto-detect the appropriate JDBC driver for the specified JDBC Connection String.
Resolving The Problem
Identify the JDBC Driver Class Name:
Determine the JDBC driver class name associated with your database. This information is usually available in the database’s documentation or from the JDBC driver provider.
Upload the Custom JDBC Driver:
Download the JDBC driver JAR file from your database provider.
In the Transformer for Spark pipeline, navigate to the JDBC stage where the error occurs.
Upload the driver JAR file to the stage.
Manually Specify the JDBC Driver Class:
Go to the "Advanced" tab in the stage configuration.
In the JDBC Driver dropdown, select "Bundle Custom Driver".
Enter the fully qualified JDBC Driver Class Name (e.g.,
com.amazon.redshift.jdbc42.Driverfor Amazon Redshift).
Restart Transformer for Spark:
After uploading the custom JDBC driver, restart StreamSets Transformer for Spark to apply the changes. This step is necessary for the new driver to be recognized by the Transformer.
Validate the Connection:
After specifying the driver class name and restarting Transformer for Spark, validate the pipeline to ensure your JDBC stage is now able to establish a connection with your database.
Example: Configuring the JDBC Driver for Amazon Redshift
If you are using Amazon Redshift and encounter the JDBC_03 error, follow these specific steps:
Download the Amazon Redshift JDBC driver (JDBC 4.2–compatible driver version 2.1 without the AWS SDK) from Amazon's website.
Upload the Redshift JDBC driver to your JDBC stage.
Restart Transformer for Spark.
Navigate to the "Advanced" tab of the JDBC Table stage.
In the JDBC Driver dropdown, select "Bundle Custom Driver".
Enter the Driver Class Name:
com.amazon.redshift.jdbc42.Driver.Validate the connection to Amazon Redshift.
For more details on configuring JDBC stages, refer to the official StreamSets Transformer for Spark documentation:
Document Location
Worldwide
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Document Information
Modified date:
15 March 2025
UID
ibm17186193