-
Verify Dependencies:
- Make sure that the required library or package containing the missing class (
com.databricks.cdc.spark.DebeziumJDBCMicroBatchProvider
) is correctly included in your environment.
- If you’re using Maven or SBT, ensure that the appropriate dependencies are added to your project configuration.
-
Check Databricks Documentation:
- While Debezium is commonly used for change data capture (CDC), Databricks Delta Lake (DLT) doesn’t necessarily require manual installation of Debezium.
-
Classpath and Environment:
- Ensure that the classpath for your DLT pipeline includes the necessary JAR files or packages containing Debezium-related classes.
- If you’re running your DLT pipeline on Databricks, check the cluster configuration and verify that the required libraries are attached to the cluster.
-
Restart the Cluster:
- Sometimes, changes to dependencies or configurations require a cluster restart. Try restarting your Databricks cluster after making any adjustments.
Remember to adapt these steps to your specific environment and setup. If you encounter any further issues, consider reaching out for additional assistance12.
Good luck with resolving the issue! 😊
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