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pdqsort isn't stable and still suffers from killer inputs. Not sure how well this will paste: Name | Items | Type | Best | Average | Loops |

pdqsort isn't stable and still suffers from killer inputs. Not sure how well this will paste: Name | Items | Type | Best | Average | Loops | Samples | Distribution -------- | -------- | ---- | -------- | -------- | --------- | ------- | ---------------- blitsort | 100000 | 32 | 0.005962 | 0.006532 | 1 | 100 | random order pdqsort | 100000 | 32 | 0.002665 | 0.002802 | 1 | 100 | random order | | | | | | | blitsort | 100000 | 32 | 0.000069 | 0.000078 | 1 | 100 | ascending order pdqsort | 100000 | 32 | 0.000098 | 0.000100 | 1 | 100 | ascending order | | | | | | | blitsort | 100000 | 32 | 0.001138 | 0.001196 | 1 | 100 | ascending saw pdqsort | 100000 | 32 | 0.003245 | 0.003317 | 1 | 100 | ascending saw | | | | | | | blitsort | 100000 | 32 | 0.003777 | 0.003843 | 1 | 100 | generic order pdqsort | 100000 | 32 | 0.000819 | 0.000851 | 1 | 100 | generic order | | | | | | | blitsort | 100000 | 32 | 0.000051 | 0.000060 | 1 | 100 | descending order pdqsort | 100000 | 32 | 0.000202 | 0.000207 | 1 | 100 | descending order | | | | | | | blitsort | 100000 | 32 | 0.000815 | 0.000845 | 1 | 100 | descending saw pdqsort | 100000 | 32 | 0.002307 | 0.002368 | 1 | 100 | descending saw | | | | | | | blitsort | 100000 | 32 | 0.001761 | 0.001774 | 1 | 100 | random tail pdqsort | 100000 | 32 | 0.002560 | 0.002572 | 1 | 100 | random tail | | | | | | | blitsort | 100000 | 32 | 0.003328 | 0.003374 | 1 | 100 | random half pdqsort | 100000 | 32 | 0.002651 | 0.002854 | 1 | 100 | random half | | | | | | | blitsort | 100000 | 32 | 0.000593 | 0.000938 | 1 | 100 | ascending tiles pdqsort | 100000 | 32 | 0.002316 | 0.002482 | 1 | 100 | ascending tiles

nightcracker 5y ago
What do you mean by "suffers from killer inputs"? It is always O(n log n) by falling back to heapsort, so I don't think any input can be described as a "killer".
mlochbaum 5y ago
You should explain these issues in the repository, not in Hacker News comments! A benchmark of 100,000 32 bit integers suggests that you will be comparing against algorithms that do well on that benchmark when it's not the case at all. The concept of stability doesn't apply when elements that compare the same are indistinguishable, which is the case for integers. And I think it's an exaggeration to say pdqsort has "killer inputs". In your benchmarks the patterned data always sorts faster than random, so the most you can say is that merge sort exploits some kinds of structure better (I have seen patterns where it does worse, but not by much). I expect timsort has some similar advantages over blitsort because of its ability to find natural runs while blitsort always starts at size 32—try an up-down pattern with runs of length 50 for instance. The absolute worse case for pdqsort is a fallback to heapsort. With pivot randomization it's pretty much impossible on large arrays unless they are engineered to make pdqsort fail, and you end up sorting the array three times slower or something. Not much of a DOS attack. Having a fast merge sort is definitely useful in a lot of situations (my thoughts at [1]), and I've been interested in quadsort particularly for that purpose (blitsort seems to emphasize lower external memory usage which I've never had a use for). Half as fast as pdqsort on random data is actually somewhat better than I expected. It feels dishonest to see "Blitsort has exceptional performance" followed by selective benchmarks showing worse algorithms, and it makes it much harder to figure out what blitsort is good for. [1] https://mlochbaum.github.io/BQN/implementation/primitive/sort.html#on-quicksort-versus-merge-sort https://mlochbaum.github.io/BQN/implementation/primitive/sor...
- scandum 5y ago
  Well, blitsort's performance is exceptional in the sense that it's 15% faster than the next fastest stable in-place sort. As for stability, it's useful when you need to sort a table with an integer index. So it might be of value to database software. I probably should point out some of the weakness on the README. Agreed on pdqsort being 3x slower worst case on "killer" input, but it's my understanding that's why it's not being used to replace std::sort. As for runs of 50, haven't benched those, though I assume gridsort (https://github.com/scandum/gridsort https://github.com/scandum/gridsort) would handle those rather well.
  - 5y ago

nightcracker 5y ago

What do you mean by "suffers from killer inputs"? It is always O(n log n) by falling back to heapsort, so I don't think any input can be described as a "killer".

mlochbaum 5y ago

You should explain these issues in the repository, not in Hacker News comments! A benchmark of 100,000 32 bit integers suggests that you will be comparing against algorithms that do well on that benchmark when it's not the case at all. The concept of stability doesn't apply when elements that compare the same are indistinguishable, which is the case for integers. And I think it's an exaggeration to say pdqsort has "killer inputs". In your benchmarks the patterned data always sorts faster than random, so the most you can say is that merge sort exploits some kinds of structure better (I have seen patterns where it does worse, but not by much). I expect timsort has some similar advantages over blitsort because of its ability to find natural runs while blitsort always starts at size 32—try an up-down pattern with runs of length 50 for instance. The absolute worse case for pdqsort is a fallback to heapsort. With pivot randomization it's pretty much impossible on large arrays unless they are engineered to make pdqsort fail, and you end up sorting the array three times slower or something. Not much of a DOS attack. Having a fast merge sort is definitely useful in a lot of situations (my thoughts at [1]), and I've been interested in quadsort particularly for that purpose (blitsort seems to emphasize lower external memory usage which I've never had a use for). Half as fast as pdqsort on random data is actually somewhat better than I expected. It feels dishonest to see "Blitsort has exceptional performance" followed by selective benchmarks showing worse algorithms, and it makes it much harder to figure out what blitsort is good for. [1] https://mlochbaum.github.io/BQN/implementation/primitive/sort.html#on-quicksort-versus-merge-sort https://mlochbaum.github.io/BQN/implementation/primitive/sor...

scandum 5y ago
Well, blitsort's performance is exceptional in the sense that it's 15% faster than the next fastest stable in-place sort. As for stability, it's useful when you need to sort a table with an integer index. So it might be of value to database software. I probably should point out some of the weakness on the README. Agreed on pdqsort being 3x slower worst case on "killer" input, but it's my understanding that's why it's not being used to replace std::sort. As for runs of 50, haven't benched those, though I assume gridsort (https://github.com/scandum/gridsort https://github.com/scandum/gridsort) would handle those rather well.
- 5y ago