How To Fix RSRCACHE020 - Size from which entries are to be written to larger persistence

RSRCACHE020 - Overview

• Message type: E = Error

• Message class: RSRCACHE - Messages for OLAP Cache

• Message number: 020

• Message text: Size from which entries are to be written to larger persistence

What causes this issue?

The cache mode "Query Aggregate" uses a cluster table and BLOB storage
(table with XSTRING area) to store cache entries with query data. This
setting specifies the size limit up to which the system is to write to
the memory area for smaller query results and when it is to use the
memory area for larger data.
Using the following two settings, you can specify which of the memory
areas is to be used for the query results that are larger than the key
figure specified here.
You specify which memory area is to be used when you create the cache
entry for the query data; once specified, this value cannot be changed,
even if the cache entry is later larger than the predefined key figure.

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?

Procedure for System Administrators

Error message extract from SAP system. Copyright SAP SE.

Smart SAP Assistant

• What is the cause and solution for SAP error message RSRCACHE020 - Size from which entries are to be written to larger persistence ?

  The SAP error message RSRCACHE020 typically indicates an issue related to the resource cache in the SAP system, specifically concerning the size of the entries that are being written to a larger persistence layer. This error can occur in various contexts, such as when dealing with the SAP BW (Business Warehouse) or other SAP applications that utilize caching mechanisms.
  
  Cause:
  The error message RSRCACHE020 is generally triggered when the system attempts to write entries to a persistence layer, but the size of the entries exceeds the defined limits or thresholds. This can happen due to several reasons, including:
  
  
  Configuration Issues: The settings for the resource cache or persistence layer may not be properly configured, leading to size mismatches.
  Data Volume: The volume of data being processed may be larger than what the system can handle at once, especially if there are large datasets being loaded or processed.
  Memory Limitations: The system may be running low