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Message type: E = Error
Message class: CA_TTE - TTE Messages
Message number: 575
Message text: Elapsed time for processing document (Kernel): &1 milliseconds
The system reports the elapsed time that was needed to process the
whole document including tax determination, tax calculation and
building the output document. It is reported in milliseconds (1000th of
a second).
The system issues an error message and will not allow you to continue with this transaction until the error is resolved.
Error message extract from SAP system. Copyright SAP SE.
CA_TTE575
- Elapsed time for processing document (Kernel): &1 milliseconds ?The SAP error message CA_TTE575 indicates that there is a performance issue related to the processing time of a document in the SAP system. The message specifies the elapsed time taken for processing a document, which is represented by the placeholder
&1
in milliseconds. This message is typically a warning rather than a critical error, and it serves to inform users or administrators that the processing time for a specific operation is longer than expected.Cause:
- System Performance Issues: High system load, insufficient hardware resources (CPU, memory, disk I/O), or network latency can lead to increased processing times.
- Inefficient Code: Custom ABAP code or poorly optimized queries can cause delays in processing.
- Database Performance: Slow database queries or locks on database tables can lead to increased processing times.
- Large Data Volumes: Processing large volumes of data can naturally take more time.
- Background Jobs: If there are many background jobs running simultaneously, they can compete for resources, leading to delays.
Solution:
- Performance Analysis: Use transaction codes like ST03N (Workload Analysis), ST04 (Database Performance), and ST22 (Dump Analysis) to analyze system performance and identify bottlenecks.
- Optimize Code: Review and optimize any custom ABAP code or queries that may be causing delays. Use tools like the ABAP Runtime Analysis (transaction SE30) to identify performance issues in the code.
- Database Optimization: Check for long-running database queries and optimize them. Ensure that database statistics are up to date and consider indexing frequently accessed tables.
- System Resources: Monitor system resources and consider upgrading hardware if the system is consistently under heavy load.
- Batch Processing: If processing large volumes of data, consider breaking the data into smaller batches to reduce processing time.
- Background Job Management: Schedule background jobs during off-peak hours to minimize resource contention.
Related Information:
By addressing the underlying causes of the performance issue, you can reduce the elapsed time for processing documents and improve overall system efficiency.
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