Hello! One of the popular bulk data operation is to find given number of least or greatest elements. Currently Stream API provides no dedicated operation to do this. Of course, it could be implemented by custom collector and some third-party libraries already provide it. However it would be quite natural to use existing API:
stream.sorted().limit(k) - k least elements stream.sorted(Comparator.reverseOrder()).limit(k) - k greatest elements. In fact people already doing this. Some samples could be found on GitHub: https://github.com/search?l=java&q=%22sorted%28%29.limit%28%22&type=Code&utf8=%E2%9C%93 Unfortunately current implementation of such sequence of operations is suboptimal: first the whole stream content is dumped into intermediate array, then sorted fully and after that k least elements is selected. On the other hand it's possible to provide a special implementation for this particular case which takes O(k) additional memory and in many cases works significantly faster. I wrote proof-of-concept implementation, which could be found here: http://cr.openjdk.java.net/~tvaleev/patches/sortedLimit/webrev/ The implementation switches to new algorithm if limit is less than 1000 which is quite common for such scenario (supporting bigger values is also possible, but would require more testing). New algorithm allocates an array of 2*limit elements. When its size is reached, it sorts the array (using Arrays.sort) and discards the second half. After that only those elements are accumulated which are less than the worst element found so far. When array is filled again, the second half is sorted and merged with the first half. Here's JMH test with results which covers several input patterns: http://cr.openjdk.java.net/~tvaleev/patches/sortedLimit/jmh/ You may check summary first: http://cr.openjdk.java.net/~tvaleev/patches/sortedLimit/jmh/summary.txt Speedup values bigger than 1 are good. The most significant regression in the sequential mode of the new implementation is the ever decreasing input (especially with the low limit value). Still, it's not that bad (given the fact that old implementation processes such input very fast). On the other hand, for random input new implementation could be in order of magnitude faster. Even for ever ascending input noteable speedup (like 40%) could be achieved. For parallel stream the new implementation is almost always faster, especially if you ignore the cases when parallel stream is unprofitable. What do you think about this improvement? Could it be included into JDK-9? Are there any issues I'm unaware of? I would be really happy to complete this work if this is supported by JDK team. Current implementation has no primitive specialization and does not optimize the sorting out if the input is known to be sorted, but it's not very hard to add these features as well if you find my idea useful. With best regards, Tagir Valeev.
