There is no standard way to overwrite log4j configurations on clusters with custom configurations. You must overwrite the configuration files using init scripts.
The current configurations are stored in two log4j.properties files:
- On the driver:
%sh cat /home/ubuntu/databricks/spark/dbconf/log4j/driver/log4j.properties
- On the worker:
%sh cat /home/ubuntu/databricks/spark/dbconf/log4j/executor/log4j.properties
To set class-specific logging on the driver or on workers, use the following script:
%sh #!/bin/bash echo "Executing on Driver: $DB_IS_DRIVER" if [[ $DB_IS_DRIVER = "TRUE" ]]; then LOG4J_PATH="/home/ubuntu/databricks/spark/dbconf/log4j/driver/log4j.properties" else LOG4J_PATH="/home/ubuntu/databricks/spark/dbconf/log4j/executor/log4j.properties" fi echo "Adjusting log4j.properties here: ${LOG4J_PATH}" echo "log4j.<custom-prop>=<value>" >> ${LOG4J_PATH}
Replace <custom-prop> with the property name, and <value> with the property value.
Upload the script to DBFS and select a cluster using the cluster configuration UI.
You can also set log4j.properties for the driver in the same way.
See Cluster node initialization scripts (AWS | Azure | GCP) for more information.