Optimizing CDS Views: Best Practices and Performance Enhancements.
Uloženo v:
| Název: | Optimizing CDS Views: Best Practices and Performance Enhancements. |
|---|---|
| Autoři: | Beereddy, Sravanthi |
| Zdroj: | Journal of Computer Science & Technology Studies; May/Jun2025, Vol. 7 Issue 3, p701-740, 40p |
| Témata: | ELECTRONIC data processing, USER interfaces, MATHEMATICAL optimization, DATABASES, USER experience |
| Abstrakt: | This comprehensive technical article explores optimization strategies for ABAP Core Data Services (CDS) views within SAP environments. Beginning with an introduction to CDS and its implementation of the Code-to-Data paradigm, the article examines how this architectural approach shifts processing from application to database layers, resulting in significant performance improvements. The document presents detailed best practices for optimizing CDS views, including efficient join strategies, filter optimization techniques, effective use of annotations, simplification of complex logical expressions, union operation enhancements, and authorization handling recommendations. It further explores ABAP code efficiency when working with CDS views, emphasizing the importance of proper abstraction through DDL names, selective attribute retrieval, effective OData query implementation, and shifting calculations to the data layer. The article concludes with user interface performance enhancement strategies, covering library and dependency loading optimization, asynchronous processing implementation, user experience improvements through engaging elements, CDN utilization, and preloading techniques for faster rendering. Throughout, the document references SAP technical documentation, community discussions, and performance studies to substantiate recommended approaches. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of Computer Science & Technology Studies is the property of Al-Kindi Center for Research & Development and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Databáze: | Complementary Index |
Nájsť tento článok vo Web of Science Buďte první, kdo okomentuje tento záznam!