How To Fix APPL_PROC_HUB_PR023 - End time of extraction job is &1

APPL_PROC_HUB_PR023 - Overview

• Message type: E = Error

• Message class: APPL_PROC_HUB_PR - Message Class for Purchase Requisition Extraction

• Message number: 023

• Message text: End time of extraction job is &1

Self-Explanatory Message

Since SAP believes that this specific error message is 'self-explanatory,' no more information has been given.The majority of messages in the SAP system have a message text, however this is frequently insufficient to comprehend or resolve the problem.

To make things easier, more detailed information is frequently added to describe the issue, how to fix it, and the necessary steps or configuration modifications.

Unfortunately, there isn't any extra information in this error notice.

What else can you do?

First, use our AnswerBot below to get a possible cause and solution (requires a premium subscription).

Also, review the in-depth Common Questions & Answers listed below; you could discover a solution there or be able to connect with others who have faced similar challenges.

You can also try searching the SAP support portal (support.sap.com) but you need a special user ID to access it. It is possible that an SAP support note exists that provides additional details about the mistake or even steps for fixing it.

Smart SAP Assistant

• What is the cause and solution for SAP error message APPL_PROC_HUB_PR023 - End time of extraction job is &1 ?

  The SAP error message APPL_PROC_HUB_PR023 typically indicates an issue related to the end time of an extraction job. This message is often encountered in the context of data extraction processes, particularly when using SAP's data warehousing or data integration tools.
  
  Cause:
  The error message APPL_PROC_HUB_PR023 usually arises due to one of the following reasons:
  
  Job Duration Exceeded: The extraction job may have taken longer than expected, leading to a situation where the end time of the job is not aligning with the expected time frame.
  
  Configuration Issues: There may be misconfigurations in the job scheduling or extraction settings that cause the job to run longer than anticipated.
  Resource Constraints: Insufficient system resources (CPU, memory, I/O) can lead to delays in job execution.
  Data Volume: A large volume of data being processed can also cause the job to exceed its expected duration.
  Network Issues: If the extraction involves data transfer over a network, any network latency or interruptions