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Troubleshooting Databricks collector issues

Collector runtime and troubleshooting

The catalog collector may run in several seconds to many minutes depending on the size and complexity of the system being crawled.

  • If the catalog collector runs without issues, you should see no output on the terminal, but a new file that matching *.dwec.ttl should be in the directory you specified for the output.

  • If there was an issue connecting or running the catalog collector, there will be either a stack trace or a *.log file. Both of those can be sent to support to investigate if the errors are not clear.

A list of common issues and problems encountered when running the collectors is available here.

Issue 1: Not all desired tables displayed after the collector run is complete

  • Cause: The parameters all-schemas or schema is missing from the Command line or YAML file.

  • Solution: Check your command or YAML file to make sure the all-schemas or schema parameter is setup properly.

Issue 2: Collector stops harvesting metadata and log messages show communication failures

The following error messages are observed in the error logs:

  • Communication link failure. Failed to connect to server. Reason: HTTP Response code: 504

  • Communication link failure. Failed to connect to server. Reason: HTTP Response code: 502

Within the Databricks Event log for the cluster, you may also see the following messages: Driver is up but is not responsive, likely due to GC or java.lang.OutOfMemoryError: GC overhead limit exceeded.

  • Cause: The Databricks cluster has insufficient memory. When there is a low amount of memory, garbage collection runs a lot and slows down the message. For details, see the Databricks troubleshooting article.

  • Solution: Change the Databricks cluster driver type to an instance that has more memory. For details, see the Databricks documentation.