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Message type: E = Error
Message class: RSDU_REPART - Messages for Repartitioning InfoProviders
Message number: 815
Message text: The estimated fact table size of &1 GB is close to the DB limit of &2 GB
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RSDU_REPART815
- The estimated fact table size of &1 GB is close to the DB limit of &2 GB ?The SAP error message RSDU_REPART815 indicates that the estimated size of a fact table in your SAP BW (Business Warehouse) system is approaching the database limit. This can lead to performance issues or even prevent the loading of data if the limit is exceeded. Here’s a breakdown of the cause, potential solutions, and related information:
Cause:
- Data Volume: The primary cause of this error is that the volume of data being loaded into the fact table is large, and the estimated size is nearing the maximum allowed size for the database.
- Database Limitations: Different databases have different limits on the size of tables. For example, some databases may have a limit of 2 GB, while others may support larger sizes.
- Data Model Design: Inefficient data modeling or not properly archiving old data can lead to excessive growth in the size of fact tables.
Solutions:
- Data Archiving: Implement data archiving strategies to remove old or less frequently accessed data from the fact table. This can help reduce the size of the table.
- Partitioning: Consider partitioning the fact table if your database supports it. This can help manage large datasets more effectively and improve performance.
- Data Compression: Use data compression techniques if supported by your database. This can help reduce the physical size of the data stored.
- Review Data Model: Analyze the data model to ensure that it is optimized. Remove unnecessary fields or aggregates that may be contributing to the size.
- Increase Database Limits: If possible, consider upgrading your database or changing configurations to allow for larger table sizes. Consult your database administrator for options.
- Load Data in Batches: If applicable, load data in smaller batches to avoid hitting the size limit during data loads.
Related Information:
By addressing the underlying causes and implementing the suggested solutions, you can mitigate the risk of encountering this error in the future.
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