Diagnosing Haskell Space Leaks from Lazy Thunks and IO Pipelines
A practical diagnostic guide for Haskell space leaks from lazy evaluation and IO pipelines, using RTS stats, heap profiling, and targeted strictness fixes.
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A practical diagnostic guide for Haskell space leaks from lazy evaluation and IO pipelines, using RTS stats, heap profiling, and targeted strictness fixes.
Haskell's default laziness stores data fields as thunks. Making data types strict by default with StrictData prevents space leaks from thunk buildup, while selective laziness preserves composability where it matters.
Lazy foldl can build a huge chain of thunks, causing space leaks. Use foldl’ and strictness annotations to keep memory constant, and verify with GHC’s +RTS -s runtime statistics.
Forcing accumulator evaluation with BangPatterns prevents space leaks in Haskell state transforms, keeping memory constant regardless of input size.
Long-running Haskell services leak memory through lazy thunks in accumulators. Here's how BangPatterns, strict fields, and StrictData fix it — plus the WHNF trap and how to verify the fix with +RTS -s.