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Mastering Apex Programming

You're reading from   Mastering Apex Programming A Salesforce developer's guide to learn advanced techniques and programming best practices for building robust and scalable enterprise-grade applications

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Product type Paperback
Published in Nov 2023
Publisher Packt
ISBN-13 9781837638352
Length 394 pages
Edition 2nd Edition
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Author (1):
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Paul Battisson Paul Battisson
Author Profile Icon Paul Battisson
Paul Battisson
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Table of Contents (28) Chapters Close

Preface 1. Section 1: Triggers, Testing, and Security
2. Chapter 1: Common Apex Mistakes FREE CHAPTER 3. Chapter 2: Debugging Apex 4. Chapter 3: Triggers and Managing Trigger Execution 5. Chapter 4: Exceptions and Exception Handling 6. Chapter 5: Testing Apex Code 7. Chapter 6: Secure Apex Programming 8. Section 2: Asynchronous Apex
9. Chapter 7: Utilizing Future Methods 10. Chapter 8: Working with Batch Apex 11. Chapter 9: Working with Queueable Apex 12. Chapter 10: Scheduling Apex Jobs 13. Section 3: Integrations
14. Chapter 11: Integrating with Salesforce 15. Chapter 12: Using Platform Events 16. Chapter 13: Apex and Flow 17. Chapter 14: Apex REST and Custom Web Services 18. Chapter 15: Outbound Integrations – REST 19. Chapter 16: Outbound Integrations – SOAP 20. Chapter 17: DataWeave in Apex 21. Section 4: Apex Performance
22. Chapter 18: Performance and the Salesforce Governor Limits 23. Chapter 19: Performance Profiling 24. Chapter 20: Improving Apex Performance 25. Chapter 21: Performance and Application Architectures 26. Index 27. Other Books You May Enjoy

Improving CPU time

CPU time is the amount of time spent running Apex code during a transaction. It is difficult to pin down exactly, as many factors can come into play that determine how much time is spent running a piece of code; however, in general, there are two ways to improve CPU usage:

  • Working on a smaller amount of data (that is, doing less work)
  • Operating on data in a more efficient manner

It is always important to consider whether the first option is possible. Can we make our query more selective (there’s more on this in the Improving query selectivity section ahead) or simply reduce the amount of work we do to speed up the system? A standard synchronous transaction has 10,000 ms of CPU time available. If we process 10,000 records, that means 1 ms each. For 1,000 records, that means 10 ms each – again, not a lot of time but 10x the previous allocation. Anything we can do, therefore, to reduce the scope of the data we work on will be beneficial...

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