Hello! Thank you for your comments!
PL> - in Limiter.put: Nice catch! A good example when series of minor code refactorings lead to something strange. Webrev is updated in-place: http://cr.openjdk.java.net/~tvaleev/patches/sortedLimit/webrev/ PL> Also, what do you think of the following merging strategy that PL> doesn't need to allocate a temporary array each time you perform a sortTail(): I think, the main goal of such algos is to reduce comparator calls. Allocating additional buffer and some copying operations should not be very expensive (especially given the fact that we don't know comparator call cost and it could be pretty high). Actually I have a couple of additional optimizations in mind which may speedup some input patterns. But before working on that I would like to get the green light for this feature. I already spent quite a big time working on proof-of-concept implementation. Paul, could you please comment on this? If some time is necessary for the evaluation, no problem, I will wait. If additional clarifications are necessary from my side, I would be happy to answer any questions. With best regards, Tagir Valeev. PL> "first" phase: PL> - accumulate elements data[0] ... data[limit-1] and when reaching PL> limit, sort them and set first = false (this differs from your PL> logic which accumulates up to data.length elements at first PL> and is a better strategy, because it starts the second phase PL> as soon as possible and second phase is more optimal since it PL> already filters elements that accumulates) PL> "second" phase: PL> - accumulate elements < data[limit-1] into data[limit] ... PL> data[data.length-1] and when reaching length, sort the tail and PL> perform merge which looks like this: PL> - simulate merge of data[0] ... data[limit-1] with data[limit] PL> ... data[size-1] deriving end indices i and j of each PL> sub-sequence: data[0] ... data[i-1] and data[limit] ... data[j-1]; PL> - move elements data[0] ... data[i-1] to positions PL> data[limit-i] ... data[limit-1] PL> - perform in-place merge of data[limit-i] ... data[limit-1] and PL> data[limit] ... data[j-1] into data[0] ... data[limit-1] PL> This, I think, results in dividing the additional copying PL> operations by 2 in average and eliminates allocation of PL> temporary array for merging for the cost of pre-merge step PL> which just derives the end indices. There's a chance that this PL> might improve performance because it trades memory writes for reads. PL> What do you think? PL> Regards, Peter PL> On 03/05/2016 06:35 PM, Tagir F. Valeev wrote: PL> PL> PL> Hello! PL> One of the popular bulk data operation is to find given number of PL> least or greatest elements. Currently Stream API provides no dedicated PL> operation to do this. Of course, it could be implemented by custom PL> collector and some third-party libraries already provide it. However PL> it would be quite natural to use existing API: PL> stream.sorted().limit(k) - k least elements PL> stream.sorted(Comparator.reverseOrder()).limit(k) - k greatest elements. PL> In fact people already doing this. Some samples could be found on PL> GitHub: PL> https://github.com/search?l=java&q=%22sorted%28%29.limit%28%22&type=Code&utf8=%E2%9C%93 PL> Unfortunately current implementation of such sequence of operations is PL> suboptimal: first the whole stream content is dumped into intermediate PL> array, then sorted fully and after that k least elements is selected. PL> On the other hand it's possible to provide a special implementation PL> for this particular case which takes O(k) additional memory and in PL> many cases works significantly faster. PL> I wrote proof-of-concept implementation, which could be found here: PL> http://cr.openjdk.java.net/~tvaleev/patches/sortedLimit/webrev/ PL> The implementation switches to new algorithm if limit is less than PL> 1000 which is quite common for such scenario (supporting bigger values PL> is also possible, but would require more testing). New algorithm PL> allocates an array of 2*limit elements. When its size is reached, it PL> sorts the array (using Arrays.sort) and discards the second half. PL> After that only those elements are accumulated which are less than the PL> worst element found so far. When array is filled again, the second PL> half is sorted and merged with the first half. PL> Here's JMH test with results which covers several input patterns: PL> http://cr.openjdk.java.net/~tvaleev/patches/sortedLimit/jmh/ PL> You may check summary first: PL> http://cr.openjdk.java.net/~tvaleev/patches/sortedLimit/jmh/summary.txt PL> Speedup values bigger than 1 are good. PL> The most significant regression in the sequential mode of the new PL> implementation is the ever decreasing input (especially with the low PL> limit value). Still, it's not that bad (given the fact that old PL> implementation processes such input very fast). On the other hand, for PL> random input new implementation could be in order of magnitude faster. PL> Even for ever ascending input noteable speedup (like 40%) could be PL> achieved. PL> For parallel stream the new implementation is almost always faster, PL> especially if you ignore the cases when parallel stream is PL> unprofitable. PL> What do you think about this improvement? Could it be included into PL> JDK-9? Are there any issues I'm unaware of? I would be really happy to PL> complete this work if this is supported by JDK team. Current PL> implementation has no primitive specialization and does not optimize PL> the sorting out if the input is known to be sorted, but it's not very PL> hard to add these features as well if you find my idea useful. PL> With best regards, PL> Tagir Valeev. PL> PL> PL>
