Parallel streams? When to use and Pitfalls.

What is it?

A way to execute stream operations in parallel using the ForkJoinPool. Created via list.parallelStream() or stream.parallel().

When to use?

• Large datasets.
• Computationally intensive tasks per element.
• When the order of processing does not matter.

Pitfalls in Web Applications:

• Common Pool Contention: By default, all parallel streams share the same global ForkJoinPool.commonPool(). One heavy stream can block the entire application's parallel tasks.
• Thread Safety: Operations inside must be stateless and thread-safe.
• Overhead: For small datasets, the overhead of splitting and merging tasks makes parallel streams slower than sequential ones.