How To Fix STREX552 - IndexServer Memory

STREX552 - Overview

• Message type: E = Error

• Message class: STREX - Message for TREX ABAP Client

• Message number: 552

• Message text: IndexServer Memory

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?

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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.

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Smart SAP Assistant

• What is the cause and solution for SAP error message STREX552 - IndexServer Memory ?

  The SAP error message STREX552 typically indicates that the Index Server in the SAP HANA database is running low on memory. This can lead to performance issues or even system instability if not addressed. Here’s a breakdown of the cause, potential solutions, and related information:
  Cause
  
  High Workload: The Index Server may be handling a high volume of queries or transactions, consuming more memory than usual.
  Memory Configuration: The memory allocated to the Index Server may be insufficient for the current workload.
  Memory Leaks: There could be memory leaks in the application or database processes that are consuming memory over time.
  Large Data Sets: Queries involving large data sets or complex calculations can require significant memory resources.
  Improperly Optimized Queries: Inefficient SQL queries can lead to excessive memory usage.
  
  Solutions
  
  Monitor Memory Usage: Use SAP HANA Studio or HANA Cockpit to monitor memory usage and identify which queries or processes are consuming the most memory.
  Optimize Queries: Review and