Introduction:
In the world of ABAP development, optimizing performance is crucial for delivering efficient and responsive applications. By implementing effective performance optimization techniques, you can enhance the runtime of ABAP programs, improve user experience, and maximize system resources. In this blog, we will explore advanced techniques for optimizing performance in ABAP development.
1. Database Access Optimization:
Efficient database access is key to improving ABAP program performance. Minimizing database roundtrips and utilizing appropriate access methods can significantly reduce database load and response times.
- Use WHERE clause in your SELECT statement to restrict the volume of data retrieved. Very important !!
- Design your Query to Use as much index fields as possible in your WHERE statement
- Use INNER (or OUTER under some circumstances) JOIN in your SELECT statement to retrieve the matching records at one shot
- Avoid using nested SELECT statement and SELECT within LOOPs, better use JOINs or FOR ALL ENTRIES. Use FOR ALL ENTRIES when the internal table is already there or the end of some processing. Try JOINs if the SELECT are right behind each other
- Avoid using INTO CORRESPONDING FIELDS OF TABLE during buffered access. Otherwise use the most appropriate for the program.
- Avoid using SELECT * and Select only the required fields from the table.
- Avoid using ORDER BY in SELECT statements if it differs from used index (instead, sort the resulting internal table), because this may add additional work to the database system which is unique, while there may be many ABAP servers
- INDEX: Creation of Index for improving performance should not be taken without thought. Index speeds up the performance but at the same time adds two overheads namely; memory and insert/append performance. When INDEX is created, memory is used up for storing the index and index sizes can be quite big on large transaction tables! When inserting new entry in the table, all the index's are updated. More index more time. More the amount of data, bigger the indices, larger the time for updating all the indices
- Avoid Executing an identical Select (same SELECT, same parameter) multiple times in the program. Buffer in your abap code.
- Avoid using join statements if adequate standard views exist no performance impact
Another technique is using buffering mechanisms. ABAP provides different buffering options. By buffering frequently accessed data, you can avoid unnecessary database hits and enhance performance.
- Defining a table as buffered (SE11) can help in improving the performance but this has to be used with caution. Buffering of tables leads to data being read from the buffer rather than from table. Buffer sync with table happens periodically, only if something changes which is happen rarely. If this table is a transaction table chances are that the data is changing for a particular selection criteria, therefore application tables are usually not suited for table buffering. Using table buffering in such cases is not recommended. Use Table Buffering for configuration data and sometimes for Master Data..
- Avoid using complex Selects on buffered tables-, because SAP may not be able to interpret this request, and may transmit the request to the database- The code inspector tells which commands bypass the buffer
2. Coding Techniques:
Carefully crafted coding practices can greatly impact performance. Avoiding nested loops, reducing unnecessary calculations and data processing, and optimizing string operations and memory usage are important considerations. For instance, when working with large internal tables, using the binary search option or hashed tables can significantly improve search performance.
- Use HASHED tables where-ever possible. Otherwise SORTED tables. STANDARD tables should be the last choice.
- Use assign instead of into in LOOPs for table types with large work areas, if the data is being modified.
- When in doubt call transaction SE30 and check your code.
- If you must use a STANDARD table and you are using a READ, sort the table appropriately and use the addition BINARY SEARCH to speed up the search.
- PERFORM : When writing a subroutine, always provide type for all the parameters. This reduces the overhead which is present when system determines on it's own each type from the formal parameters that are passed. It also makes for more robust programming.
Additionally, optimizing string concatenation using the '&&' operator instead of the '+' operator or CONCATENATE statement can yield better results. Avoiding excessive memory usage and leveraging appropriate data structures like sorted tables or hashed tables can also enhance performance.
3. Parallel Processing:
Leveraging parallel processing techniques can distribute workload and execute tasks concurrently, leading to improved performance. Asynchronous RFC calls enable you to execute time-consuming tasks in the background, freeing up the main program for other operations. Background processing using job scheduling allows for executing heavy processes during off-peak hours, reducing the load during peak usage.
Utilizing SAP NetWeaver Process Integration (PI) or other middleware solutions enables distributing tasks across multiple servers for parallel execution. This technique is particularly beneficial for data-intensive operations or long-running processes.
4. Performance Traces and Runtime Analysis:
ABAP provides powerful tools for performance analysis. By using these tools, developers can pinpoint areas for optimization and make code improvements based on the analysis results.
ST05 is the performance trace. It contain the SQL Trace plus RFC, enqueue and buffer trace. Mainly the SQL trace is is used to measure the performance of the select statements of the program.
SE30 is the Runtime Analysis transaction and can be used to measure the application performance.
SAT transaction is the replacement of the pretty outdated SE30. Provides same functionality as SE30 plus some additional features.
ST12 transaction (part of ST-A/PI software component) is a combination of ST05 and SAT. Very powerful performance analysis tool used primarily by SAP Support.
One of the best tools for static performance analyzing is
Code Inspector (SCI). There are many options for finding common mistakes and possible performance bottlenecks.
For example, analyzing the runtime analysis results can highlight which parts of the program consume the most time and identify inefficient loops or database access. Performance traces provide detailed information on SQL statements, database fetches, and memory consumption, aiding in fine-tuning performance-critical code sections.
5. Indexing and Table Partitioning:
Optimizing database indexes and implementing table partitioning techniques are crucial for improving ABAP performance. Properly defined indexes and partitioning schemes can significantly enhance data retrieval and manipulation speed.
By analyzing database access patterns and identifying frequently queried fields, you can create appropriate indexes to reduce query execution time. Table partitioning based on specific criteria, such as date range or specific values, can further optimize data retrieval and improve performance.
Use partitioning to manage large tables and indexes by dividing them into smaller, more manageable pieces. Partitions, like a large-scale index, provide faster and easier access to data.
Each partition can reside on a separate segment. Partitions are database objects and can be managed independently. You can, for example, load data and create indexes at the partition level. Yet partitions are transparent to the end user, who can select, insert, and delete data using the same DML commands whether the table is partitioned or not.
SAP ASE supports horizontal partitioning, in which a selection of table rows can be distributed among disk devices. Individual table or index rows are assigned to a partition according to a partitioning strategy.
Partitioning is the basis for parallel processing, which can significantly improve performance.
6. Memory Management:
Efficient memory management is essential for optimal performance. Dynamic memory allocation, avoiding memory leaks, and utilizing internal table work areas are important considerations.
Using field symbols or ASSIGN statement for dynamic memory allocation enables efficient usage of memory resources. Proper deallocation of memory, especially in loops or recursive functions, helps prevent memory leaks. Utilizing internal table work areas for data processing can improve performance by reducing overhead.
Conclusion:
Optimizing performance in ABAP development is a continuous process that requires a combination of sound coding practices, efficient database access, and effective utilization of system resources. By implementing the advanced techniques discussed in this blog, developers can significantly improve the runtime of ABAP programs, resulting in faster and more responsive applications. Regular monitoring and periodic performance analysis are crucial to identify areas for improvement and ensure optimal performance in ABAP development.
Remember, every ABAP program is unique, and performance optimization techniques may vary depending on specific requirements and scenarios. Experimentation and profiling are essential for achieving the best performance outcomes.
