Error
Error Code:
2055
SAP S/4HANA Error 2055: Maximum Row Limit Reached
Description
This error signifies that a database table or one of its partitions in SAP S/4HANA has reached its maximum allowed number of rows. It commonly occurs during data loading, transaction processing, or system upgrades when new records attempt to exceed this defined limit.
Error Message
Maximum number of rows per table or partition reached
Known Causes
3 known causesUncontrolled Data Growth
Accumulation of transactional data, logs, or master data over time without proper archiving or cleanup processes, leading to tables exceeding their intended capacity.
Incorrect Table Partitioning
The current design or configuration of table partitions might not adequately accommodate expected data volumes, causing individual partitions to fill up prematurely.
Large Data Migration/Import
Attempting to load an unusually large volume of data during a migration, initial data load, or mass import process can quickly push tables beyond their row limits.
Solutions
4 solutions available1. Archive Old Data medium
Reduce table size by archiving historical data that is no longer actively needed.
1
Identify tables experiencing the row limit. Use transaction SARA to find relevant archiving objects for S/4HANA. Common candidates include financial documents (FI_DOC), material documents (MM_MATBEL), and sales documents (SD_VBRK).
2
Execute the archiving session using SARA. This involves defining selection criteria for data to be archived (e.g., fiscal year, document date range) and then running the write program. The system will then mark the data for deletion.
3
Execute the deletion session using SARA. This process physically removes the archived data from the database, thereby reducing the row count.
4
Monitor table row counts after archiving to confirm the reduction. You can use tools like transaction DB02 or SQL queries to check table sizes and row counts.
SELECT table_name, num_rows FROM dba_tables WHERE table_name = 'YOUR_TABLE_NAME';2. Partition Large Tables advanced
Distribute data across multiple partitions for better manageability and performance.
1
Identify tables that are approaching or have reached the row limit and are candidates for partitioning. Consult SAP Notes and documentation for recommended partitioning strategies for S/4HANA tables.
2
Define a partitioning strategy. This typically involves choosing a partitioning key (e.g., date, company code) and the type of partitioning (e.g., range, hash).
3
Create new partitions or re-partition the existing table. This is a database-level operation and requires careful planning and execution to minimize downtime. The exact SQL syntax will depend on your underlying database (e.g., HANA, Oracle). For SAP HANA, this might involve `ALTER TABLE ... ADD PARTITION` or `ALTER TABLE ... MODIFY PARTITION` statements.
Example for SAP HANA (conceptual, consult specific documentation):
ALTER TABLE "SAPSR3"."YOUR_TABLE_NAME" ADD PARTITION 10 START ('2023-01-01') END ('2023-12-31') EVERY ('1' MONTH);4
Consider data redistribution if necessary. If the table is already at its limit, you might need to move existing data into new partitions.
5
Monitor partition usage and performance after implementation.
3. Review and Optimize Data Retention Policies easy
Re-evaluate business requirements for data retention to identify opportunities for reducing data volume.
1
Engage with business process owners to understand the actual need for keeping historical data for extended periods.
2
Identify data that can be purged based on legal, regulatory, or business requirements. This might involve data that has passed its statutory retention period.
3
Implement a regular data purging strategy. This can be achieved through custom programs, SAP archiving objects, or database-level scripts, depending on the data and system configuration.
4
Document the updated data retention policies and communicate them to relevant stakeholders.
4. Investigate and Address Duplicate/Stale Data medium
Identify and remove redundant or obsolete data that may be contributing to the row limit.
1
Analyze table content for potential duplicate records or data that is no longer referenced or used by business processes. This may require custom SQL queries or analysis tools.
SELECT column1, column2, COUNT(*) FROM "SAPSR3"."YOUR_TABLE_NAME" GROUP BY column1, column2 HAVING COUNT(*) > 1;2
Develop and execute a strategy for removing duplicate or stale data. This should be done with extreme caution and thorough testing, as incorrect deletion can lead to data integrity issues. Consider creating a staging table to move data to, perform deduplication, and then re-insert.
3
Implement data validation checks in your applications or during data entry to prevent the creation of duplicate records in the future.
4
Schedule regular data clean-up routines to maintain data quality and prevent future row limit issues.