In SAP systems, selecting the right data extraction method plays a pivotal role in ensuring system efficiency and performance. With vast amounts of data stored in SAP databases, it's essential to choose the right method for data retrieval, especially to keep operations responsive and well-optimized.
In this article, we will explore various SAP data selection techniques such as the Open Cursor, Core Data Services (CDS) views, Database views, and some other advanced strategies. Each has its strengths and weaknesses and understanding them will help you determine the best fit for your specific use case.
1. The Open Cursor Method: A Classic Approach
The Open Cursor method in SAP ABAP is a traditional technique used for data selection. It works by opening a database cursor to fetch records in smaller, manageable sets. This approach is particularly useful when working with large datasets since it doesn't overload the system by fetching everything at once.
Syntax -
OPEN CURSOR [WITH HOLD] cursor_name FOR
SELECT fields FROM source
[WHERE condition]
[GROUP BY fields]
[HAVING cond]
[ORDER BY fields].
the WITH HOLD attribute prevents a cursor from closing when a database commit occurs in Native SQL.
the WHERE condition will help to fetch the filter data from the database
the GROUP BY will create groups based on the value of the mentioned field
HAVING will add more filtration to the data extracted
ORDER BY is used to sort the data with the fields mentioned, the default sort order is ascending, and one can use DESC to sort in descending.
Example:
If you use OPEN CURSOR and CALL FUNCTION 'DB_COMMIT', use the addition "WITH HOLD". The database commit won't close the cursors. NB: COMMIT WORK always closes all opened cursors.
This method ensures that only small chunks of data are fetched, which helps prevent memory overload and improves system stability when dealing with large datasets. However, it requires careful manual control of the cursor, making it less convenient compared to more modern approaches.
Strengths:
- Suitable for processing large datasets in small chunks.
- Prevents memory overload by limiting data fetched in each iteration.
Drawbacks:
- Requires manual cursor management.
- Lacks advanced performance optimization compared to newer techniques.
2. Core Data Services (CDS) Views: A Modern, High-Performance Approach
CDS Views represent a modern approach to data selection in SAP, offering a more optimized and abstract way of handling data retrieval. CDS views allow you to define models at the database level using SQL-like syntax, making complex queries more manageable and improving performance. Designed to fully exploit the capabilities of the SAP HANA database, CDS views provide the ability to perform high-level operations directly on the database.
Example:
They can be further used to create rich CDS views ready for consumption and can primarily used with analytics tools and reporting applications like SAP Analysis for Office, Lumira, and the S/4HANA Query Browser, allowing you to expose data from your business model for analysis and visualization in various reporting formats, they are designed to be consumed by different analytical applications by providing a structured data model with specific annotations for data interpretation.
CDS views are highly efficient because they allow for powerful data manipulation at the database level, reducing the need for complex logic in the ABAP layer. They are also well-integrated with newer SAP technologies like SAP Fiori and S/4HANA.
Strengths:
- Optimized for performance, especially with SAP HANA.
- Declarative, SQL-like syntax makes it easier to handle complex queries.
- Provides advanced features like annotations, associations, and computed fields.
- Seamlessly integrates with modern SAP technologies.
Drawbacks:
- Requires learning and understanding of CDS concepts.
- May not be suitable for legacy systems without SAP HANA.
3. Database Views: A Simple, Traditional Tool
Database Views in SAP provide a virtual representation of one or more database tables. While database views are not as feature-rich as CDS views, they offer a simple and effective way to combine and access related data from multiple tables. They are ideal for straightforward joins and data extraction, especially when performance is not the primary concern.
Example:
Where Database_view is the Database view created using transaction SE11.
Although database views do not provide the same level of performance optimization or flexibility as CDS views, they still serve as a useful tool in certain scenarios, particularly for simpler queries.
Strengths:
- Easy to define and use.
- Useful for basic data access and reporting.
Drawbacks:
- Lacks advanced capabilities like calculated fields or associations.
- Performance is lower compared to CDS views, especially for complex queries.
4. A Comparative Overview: Choosing the Right Approach
The following table summarizes the key differences between the three data selection techniques discussed:
| Feature |
Open Cursor
|
CDS Views |
Database Views |
| Performance |
Medium |
High |
Low to Medium |
| Memory Usage |
Low |
High, but optimized for large sets |
Low to Medium |
| Support for Complex Queries |
Low |
High |
Low |
| Ease of Use |
Medium |
Medium to High |
High |
| Maintainability |
Medium |
High |
Medium |
| Compatibility with Modern SAP |
Low |
High (SAP HANA, S/4HANA, Fiori) |
Low |
| Handling Large Datasets |
High
|
High |
Medium |
5. Advanced Data Selection Techniques and Best Practices
While the three techniques above are commonly used for data selection, several advanced strategies can further optimize performance in SAP environments:
a) Buffered Data Reads
SAP offers table buffering to speed up data retrieval for frequently accessed data. By storing table data in memory, buffering reduces the load on the database, leading to faster data access for small-to-medium-sized tables.
b) Parallel Processing
For larger datasets or more complex operations, parallel processing can distribute the workload across multiple threads. This approach can significantly reduce processing time for time-consuming operations such as joins or aggregations.
c) AMDP (ABAP Managed Database Procedures)
For scenarios requiring complex calculations or database-specific optimizations, AMDP allows you to write SQL Script (or other database-specific languages) directly in ABAP, moving the computation to the database level. This is particularly powerful for SAP HANA users, where database-side processing is much faster.
Conclusion:
Each data selection technique in SAP has its advantages and ideal use cases. The Open Cursor method is a reliable choice when working with large datasets incrementally but lacks modern optimizations. CDS Views are the best choice for high performance and flexibility, especially in environments using SAP HANA or S/4HANA. Database Views offer a simpler alternative for less complex queries, though their performance and flexibility are more limited.
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