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Haskell High Performance Programming

You're reading from   Haskell High Performance Programming Write Haskell programs that are robust and fast enough to stand up to the needs of today

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Product type Paperback
Published in Sep 2016
Publisher Packt
ISBN-13 9781786464217
Length 408 pages
Edition 1st Edition
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Author (1):
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Samuli Thomasson Samuli Thomasson
Author Profile Icon Samuli Thomasson
Samuli Thomasson
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Table of Contents (16) Chapters Close

Preface 1. Identifying Bottlenecks FREE CHAPTER 2. Choosing the Correct Data Structures 3. Profile and Benchmark to Your Heart's Content 4. The Devil's in the Detail 5. Parallelize for Performance 6. I/O and Streaming 7. Concurrency and Performance 8. Tweaking the Compiler and Runtime System (GHC) 9. GHC Internals and Code Generation 10. Foreign Function Interface 11. Programming for the GPU with Accelerate 12. Scaling to the Cloud with Cloud Haskell 13. Functional Reactive Programming 14. Library Recommendations Index

Logging in Haskell


A final thing we'll consider is more related to I/O than streaming: logging in Haskell applications. Logging is important in any sufficiently important application.

In a small scale, a list- or DList-based WriterT monad is often all that is needed: it's simple and potentially pure (if the underlying monad is pure). However, on a bigger scale it doesn't make sense to store messages in an internal pure data structure. Instead, it's most efficient to write them to disk (or over a network) immediately (likely still using a buffer, though).

Furthermore, it would be nice if the logging functionality could be decoupled from other application code, even reused between different applications.

A popular solution which provides just that kind of decoupling is the monad-logger library. It uses a library called Fastlogger, which provides logging that scales in multicore environments. Most notoriously, FastLogger is used in the Web Application Interface (WAI) package used by many high...

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