SAP Advanced ABAP – Parallel Processing
Improve the performance of any ABAP report
What you’ll learn
SAP Advanced ABAP – Parallel Processing
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Parallel processing technique1: RFC function module with STARTING NEW TASK
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Parallel processing technique2: SPTA similar processing framework
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Parallel processing technique3: Background Job Parallel processing
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Learn the Advanced ABAP concept of parallel processing to improve the performance of any ABAP report
Requirements
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SAP ABAP understanding
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SAP ABAP debugging
Description
Every SAP ABAP developer would have encountered issues regarding performance tuning. As an ABAPer, we generally attack the select queries and try to optimize the performance; however, even after taking all performance measures as per standard ABAP practices, there is no significant performance improvement.
below are some scenarios where you need parallel processing,
- Client complaining about performance issues; all possible modification to improve performance is already done but seen not much improvement in performance
- Massive data to be processed
- An SAP standard piece of code in a custom report takes a lot of time to execute.
- Long-running background jobs.
The course will help you learn different parallel processing techniques in SAPÂ ABAP and help you solve the performance issues in your ABAP report.
In this course, we discussed three ways to achieve parallel processing.
- RFC function module with STARTING NEW TASK
- SPTA parallel processing framework
- Background job parallel processing
The basic concept behind the parallel processing framework is to divide the large volume of data into several small work packets and process different work packets into other tasks so that each work packet will be processed simultaneously in parallel, significantly reducing time. Using a similar processing framework, we can dramatically improve the processing time of any program, mainly where data volume is very high.
Who this course is for:
- SAP ABAP consultants who want to improve the performance of ABAP reports through parallel processing