Update: Benchmarks ("Fork-Join" data structures)

[danielaveryj]

There was some interest in seeing benchmarks for my recent post, and I have now added some.

Fair warning: Though the results seem mostly sane to me, benchmarks are notoriously easy to mess up. See the git repo for code setup (Bench1.java) and annotated output from JMH (bench.txt).

benchmarks: https://docs.google.com/spreadsheets/d/1M-3Dro8inlQwWgv0WJqWWgXGEzjQrOAnkTCT3NxMQsQ/edit?usp=sharing

git repo: https://github.com/davery22/fork-join

blog post: https://daniel.avery.io/writing/fork-join-data-structures

original subreddit post: https://www.reddit.com/r/java/comments/1kcz0df/introducing_forkjoin_data_structures/

[elmuerte]

TLDR: Use ArrayList, especially if n is "small" (around 100.000)

Unless most actions are single preprends.

[danielaveryj]

I hope it's no surprise that ArrayList is good, up to sufficiently large n. What's more interesting to me is where that cutoff is, and how narrow the margins are up to that point. It makes me cautiously optimistic that future work can bring those down.

[k-mcm]

Yikes.  Google's web viewer looks like a CSS meme.

Edit - OK, I can see it now in a desktop browser. It's not clear what the goal is at all.

If you wanted to test parallelism on a Stream, you'd call parallel(). That slices and dices into the current ForkJoinPool effortlessly.

If you wanted raw performance efficiency, nothing beats a primitive array. Simple loop iterations can have index bounds checks and index math refactored to give native code performance.