3331899 - You are experiencing performance or memory issues while entering data or copying facts in a table in SAP Analytics Cloud (SAC)

Symptom

You are experiencing performance or memory issues while entering data or copying facts in a table.

Environment

SAP Analytics Cloud - all versions

Cause

There are several reasons that can cause performance and/or memory issues for data entry:

General issues due to version sizes
Slow data entry
Slow copy & paste
Performance issues with mass data entry

See also Help page: Best Practices for Optimizing Performance During Planning for further detailed information as well as KBA 2855559 and KBA 2511489 for more general hints regarding performance issues.

Resolution

General issues due to version sizes

Large private version sizes can affect the overall performance for every step in the planning workflow (see Help page: Data and Performance). Therefore, consider using separate versions of smaller size for planning workflows instead of executing all planning steps on the Actual version.
To avoid possible performance or memory issues when working on very large versions, the application triggers a warning when the size of a private version exceeds a certain limit. This limit can be overridden in the model settings, but it is best to first rethink the design if the amount of facts is really needed (see KBA 3128225 for related memory issues).
It can happen that data actions have accidentally caused overly large versions by adding unnecessary zero values. In this case, such superfluous zero values can be pruned following the instructions in KBA 3102951.
If public version sizes cannot be reduced, it is strongly recommended to use a Planning Area for public edit versions to reduce their sizes (see Help page: Optimize Planning Models Using the Planning Area). Alternatively, one can use read data access control to reduce the visible version sizes or create smaller private versions using filters.
Version sizes can be monitored in the version statistics: see https://blogs.sap.com/2022/10/14/sap-analytics-cloud-private-versions-statistics-and-analysis/

Slow data entry

When entering data for a public version, the version first needs to be set into edit mode. When the first data entry on a public version is significantly slower than the data entries afterwards, consider the recommendations for large version sizes above.
In some cases, the story layout is leading to long query runtimes, but tables still load fast thanks to cache hits. The expensive layout becomes noticeable when starting to plan, as data entries lead to cache invalidation, so cannot profit from cache reads. For example, if the default layout is loading fast, but expanding a hierarchy node takes considerably longer, then the cache is hiding the actual query runtime. Try to use a simpler story layout for tables that involve planning.
Further items can possibly affect data entry performance and should thus be used with special care:
- Accounts/measures with exception aggregation Average: Every data entry on a cell with such an exception aggregation needs additional processing steps querying the underlying data. This can cause longer runtimes for large version sizes or for mass data entry.
- There are more points that can potentially affect data entry performance, e.g., data locking, disaggregating to many member combinations, filters & story layouts using non-key attributes, many unnecessary cell locks, and others. See Help page: Disaggregation of Values During Data Entry for a better understanding of the underlying processes.

Slow copy & paste

When copying data within a table, there are two types of paste operations: pasting underlying values and pasting overall values (see Help page: Copying and Pasting Cell Values). The default mode for copying within a table is to copy underlying values; for the other mode (pasting overall values) and for pasting from an external sheet refer to the recommendations above, as these are executed as data entries.
When copy-pasting underlying values from one region to another, copying less cells on higher granularity can result in better performance than copying the same region viewed at a lower granularity. E.g., copying facts from one year to another will lead to the same result and generally be faster than copying on month level.

Performance issues with mass data entry

When entering or pasting into several hundreds or thousands of cells at the same time, it is essential to have a simple story design to avoid dependency checks of the affected cells: see Help page: Performance Considerations. Not adhering to these recommendations will lead to a quadratic growth of runtime with the number of changed cells.
Mass data entry on empty cells for scenarios with many dimensions in drill can be costly, see KBA 3287839 for more details and recommendations.
Try to avoid updating too many cells at the same time. There is a limit of 30000 cells that can be changed by a mass data entry, see KBA 3277934. However, keep in mind that a mass data entry might run into a timeout already for a much smaller number of changed cells if the version size is not reasonably small or if the story design does not adhere to above recommendations.

Keywords

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Product

SAP Analytics Cloud all versions