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Hands-On High Performance with Go

You're reading from   Hands-On High Performance with Go Boost and optimize the performance of your Golang applications at scale with resilience

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Product type Paperback
Published in Mar 2020
Publisher Packt
ISBN-13 9781789805789
Length 406 pages
Edition 1st Edition
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Author (1):
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Bob Strecansky Bob Strecansky
Author Profile Icon Bob Strecansky
Bob Strecansky
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Table of Contents (20) Chapters Close

Preface 1. Section 1: Learning about Performance in Go
2. Introduction to Performance in Go FREE CHAPTER 3. Data Structures and Algorithms 4. Understanding Concurrency 5. STL Algorithm Equivalents in Go 6. Matrix and Vector Computation in Go 7. Section 2: Applying Performance Concepts in Go
8. Composing Readable Go Code 9. Template Programming in Go 10. Memory Management in Go 11. GPU Parallelization in Go 12. Compile Time Evaluations in Go 13. Section 3: Deploying, Monitoring, and Iterating on Go Programs with Performance in Mind
14. Building and Deploying Go Code 15. Profiling Go Code 16. Tracing Go Code 17. Clusters and Job Queues 18. Comparing Code Quality Across Versions 19. Other Books You May Enjoy

Briefing on memory profiling

We can perform similar actions to the CPU testing that we did in the previous section with memory. Let's take a look at another method to handle profiling, using the testing functionality. Let's use an example that we created back in Chapter 2, Data Structures and Algorithms—the o-logn function. We can use the benchmark that we have already created for this particular function and add some memory profiling to this particular test. We can execute the go test -memprofile=heap.dump -bench command.

We will see a similar output to what we saw in Chapter 2, Data Structures and Algorithms:

The only difference is that now we'll have the heap profile from this test. If we view it with the profiler, we'll see data about the heap usage rather than the CPU usage. We'll also be able to see the memory allocation for each of our...

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