Error
Error Code:
5174
SAP S/4HANA Error 5174: Array Size Limit Exceeded
Description
This error indicates that the SAP S/4HANA system attempted to allocate or expand an array, but the requested size surpassed the maximum allowed limit. It typically occurs during operations involving significant data processing, such as running complex reports or executing transactions that handle large datasets.
Error Message
ERR_TEXT_COMMON_INVALID_ARRAY_ARGUMENT
Known Causes
4 known causesExcessive Data Volume
The operation is attempting to process an exceptionally large amount of data that exceeds the system's array capacity.
System Configuration Limits
Specific SAP S/4HANA system parameters or application settings are configured with restrictive limits for array allocation.
Custom Development Issue
A custom report, program, or enhancement contains logic that inadvertently attempts to create an array larger than permitted.
Underlying Memory Constraints
The server or application instance hosting SAP S/4HANA has insufficient available memory to accommodate the requested array size.
Solutions
3 solutions available1. Optimize Data Retrieval for Large Arrays medium
Reduce the size of arrays passed to functions by fetching only necessary data.
1
Identify the ABAP program or function module that is causing the error. This often involves analyzing the ST22 dump for the specific program name and error context.
2
Review the data structures and internal tables being populated before being passed to a function or operation that might be hitting the array size limit. Look for opportunities to filter data at the source.
3
If dealing with SELECT statements, ensure that the `WHERE` clause is as specific as possible to retrieve only the required records. Avoid `SELECT *` if not absolutely necessary.
SELECT field1, field2 FROM your_table WHERE condition = 'value'.4
In ABAP, consider using `FOR ALL ENTRIES` judiciously. If the driving table is very large, it might be more efficient to process data in smaller chunks or to use a different approach altogether.
DATA: lt_data TYPE STANDARD TABLE OF your_structure.5
For bulk operations, explore using newer ABAP features or SAP HANA specific SQL constructs that are optimized for large datasets and might handle array processing more efficiently than older methods.
2. Increase System-Level Array Limits (Caution Advised) advanced
Temporarily increase system parameters related to array sizes, but understand the potential impact.
1
Access the SAP system's profile parameters. This is typically done through transaction RZ10.
2
Search for profile parameters related to array sizes or memory allocation for internal tables. Common parameters might include `rdisp/max_wprun_time` (indirectly related to processing time for large operations) or specific memory parameters. However, direct 'array size' parameters are less common and often implicitly managed by the runtime environment.
3
If a specific parameter is identified (e.g., a parameter related to the maximum number of elements in a certain type of internal table, though this is rare for general ABAP), consider increasing its value cautiously. **This is a system-wide change and can have performance implications.**
4
After changing parameters, restart the relevant SAP instances or application servers for the changes to take effect.
5
Monitor system performance closely after the change. If performance degrades or other issues arise, revert the parameter change immediately.
3. Review and Refactor Problematic ABAP Code advanced
Analyze and rewrite ABAP code that is generating excessively large arrays.
1
Use the ABAP Debugger to step through the code execution leading up to the error. Pay close attention to the size of internal tables and how they are populated.
2
Identify loops that are adding an excessive number of entries to an internal table. Consider if all these entries are truly necessary at that stage.
LOOP AT source_table INTO wa_source.
APPEND wa_source TO target_table.
ENDLOOP.3
Explore alternative data processing strategies. Instead of populating a large array and then processing it, consider processing data record by record or in smaller batches within the loop itself.
LOOP AT source_table INTO wa_source.
CALL FUNCTION 'YOUR_PROCESSING_FUNCTION' EXPORTING iv_data = wa_source.
ENDLOOP.4
If a function module or method is called with a large table parameter, examine the implementation of that function/method to see if it can be optimized to handle data in chunks or if it has internal limits.
5
Consider using database-level operations (e.g., SQL) within ABAP to perform aggregations or filtering before bringing data into ABAP internal tables. This can significantly reduce the volume of data processed in memory.
SELECT SUM(amount) INTO lv_total_amount FROM your_table WHERE ...