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Mastering Apex Programming

You're reading from   Mastering Apex Programming A developer's guide to learning advanced techniques and best practices for building robust Salesforce applications

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Product type Paperback
Published in Nov 2020
Publisher Packt
ISBN-13 9781800200920
Length 368 pages
Edition 1st Edition
Languages
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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 (21) 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 and Apex REST
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. Chapter 11: Using Platform Events 14. Chapter 12: Apex REST and Custom Web Services 15. Section 3 – Apex Performance
16. Chapter 13: Performance and the Salesforce Governor Limits 17. Chapter 14: Performance Profiling 18. Chapter 15: Improving Apex Performance 19. Chapter 16: Performance and Application Architectures 20. Other Books You May Enjoy

Reducing heap size usage

The heap size is the amount of memory being used to store the various objects, variables, and state of the Apex transaction in memory as it is being processed. For synchronous operations, this is capped at 6 MB and is doubled to 12 MB for asynchronous processes.

Put simply, the way to improve usage of the heap size is to hold less information in memory. Heap size is an interesting governor limit as it has little impact on visible performance to the end user. The end user will never be aware of some code taking 1 MB or 5 MB of heap up, unlike CPU time, where they will perceive the delay in responsiveness. Should you be working with larger datasets, the heap size can start to grow and a number of actions can be taken to reduce it. For the first of these, let's return to for loops.

Batched for loops

When discussing for loops in the preceding examples, we noted how storing the records we wish to iterate through in a variable to improve CPU time leads...

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