SAP ABAP - Parallel Processing

Improve the performance of any ABAP report

Ratings: 4.96 / 5.00




Description

Every SAP ABAP developer would have definitely encountered issues regarding performance tuning. As an ABAPer, we generally attack the select queries and try to optimize the performance but even after having taken all performance measure as per standard ABAP practices, but 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

  • Huge data to be process

  • An SAP standard piece of code in custom report taking a lot of time for execution

  • Long running background jobs


The course will help you learn different parallel processing techniques in SAP ABAP and help you solve the performance issues in your ABAP report.

In this course we have discussed 3 different 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 different tasks, so each work packet will be processed at the same time in parallels, and it will significantly reduce time. Using parallel processing framework we can significantly improve the processing time of any program, particularly where data volume is very high.

What You Will Learn!

  • Parallel processing technique1: RFC function module with STARTING NEW TASK
  • Parallel processing technique2: SPTA parallel processing framework
  • Parallel processing technique3: Background Job Parallel processing
  • Learn Advanced ABAP concept of parallel processing to improve performance of any ABAP report

Who Should Attend!

  • SAP ABAP consultants who want to improve the performance of ABAP report through parallel processing