How To Fix RSDA_HDP109 - Pending hive job '&1' was not completed in &2 seconds

RSDA_HDP109 - Overview

• Message type: E = Error

• Message class: RSDA_HDP -

• Message number: 109

• Message text: Pending hive job '&1' was not completed in &2 seconds

What causes this issue?

Current activity was canceled because there was no response from the
submitted hive job with application ID '&v1&' after &v2& seconds.

System Response

The system issues an error message and will not allow you to continue with this transaction until the error is resolved.

How to fix this error?

You have three options:
Try to repeat the activity at a later time<(>,<)>
Try to reduce the size of the archiving request, or
Contact your system administrator to perform one of the alternatives
mentioned below.

Procedure for System Administrators

Find out the reason for long-running hive jobs. Try to reduce their
runtime by applying the appropriate tuning measures to the Hadoop
cluster, or try to increase the timeout value by using parameter
WAIT_TIMEOUT_SEC of the affected near-line connection.

Error message extract from SAP system. Copyright SAP SE.

Smart SAP Assistant

• What is the cause and solution for SAP error message RSDA_HDP109 - Pending hive job '&1' was not completed in &2 seconds ?

  The SAP error message RSDA_HDP109 indicates that a pending Hive job did not complete within the specified time limit. This error typically occurs in the context of SAP Data Services or SAP BW when trying to execute a job that interacts with a Hive database.
  
  Cause:
  
  Long-running Queries: The Hive job may be taking longer than expected due to complex queries, large datasets, or inefficient query execution plans.
  Resource Constraints: The Hadoop cluster may be under heavy load, leading to resource contention and delays in job execution.
  
  Configuration Issues: There may be misconfigurations in the Hive or Hadoop settings that affect job execution times.
  Network Latency: High network latency between the SAP system and the Hadoop cluster can also contribute to delays.
  Job Queuing: The job may be queued behind other jobs in the Hadoop ecosystem, leading to longer wait times.
  
  
  Solution:
  
  Increase Timeout Settings: If the job is expected to take longer, consider increasing the timeout settings