The current TopDocCollector only allocates a ScoreDoc when the given
score causes a new ScoreDoc to be added into the queue, but it does
not reuse anything that overflows out of the queue.
So, reusing the overflow out of the queue should reduce object
allocations. especially for indexes that tend to have better scoring
docs at the end. I wouldn't expect a 30% improvement out of that,
but it would help, if only to reduce occasional performance
deteriorations.
Regards,
Paul Elschot
On Monday 10 December 2007 08:11:50 Shai Erera wrote:
> Hi
>
> Lucene's PQ implements two methods: put (assumes the PQ has room for the
> object) and insert (checks whether the object can be inserted etc.). The
> implementation of insert() requires the application that uses it to allocate
> a new object every time it calls insert. Specifically, it cannot reuse the
> objects that were removed from the PQ.
> I've done some measurements on the performance that search would gain by
> using that method, through the change of TopDocCollector.
>
> PriorityQueue change (added insertWithOverflow method)
> -----------------------------------------------------------------------------------
> /**
> * insertWithOverflow() is similar to insert(), except its return value:
> it
> * returns the object (if any) that was dropped off the heap because it
> was
> * full. This can be the given parameter (in case it is smaller than the
> * full heap's minimum, and couldn't be added) or another object that
> was
> * previously the smallest value in the heap and now has been replaced
> by a
> * larger one.
> */
> public Object insertWithOverflow(Object element) {
> if (size < maxSize) {
> put(element);
> return null;
> } else if (size > 0 && !lessThan(element, top())) {
> Object ret = heap[1];
> heap[1] = element;
> adjustTop();
> return ret;
> } else {
> return element;
> }
> }
> [Very similar to insert(), only it returns the object that was kicked out of
> the Queue, or null]
>
> TopDocCollector's current implementation of collect()
> ----------------------------------------------------------------------------
> public void collect(int doc, float score) {
> if (score > 0.0f) {
> totalHits++;
> if (hq.size() < numHits || score >= minScore) {
> hq.insert(new ScoreDoc(doc, score));
> minScore = ((ScoreDoc)hq.top()).score; // maintain minScore
> }
> }
> }
> [See how it allocates a new ScoreDoc every time this method is called]
>
> TopDocCollector's new implementation of collect()
> -----------------------------------------------------------------------------
> public void collect(int doc, float score) {
> if (score == 0.0f) {
> return;
> }
> totalHits++;
> if (hq.size() < numHits || score >= minScore) {
> if (sd == null) {
> sd = new ScoreDoc(doc, score);
> } else {
> sd.doc = doc;
> sd.score = score;
> }
> sd = (ScoreDoc) hq.insertWithOverflow(sd);
> minScore = ((ScoreDoc)hq.top()).score; // maintain minScore
> }
> }
> [sd is a class memeber of the collector, of type ScoreDoc]
>
> Now for the performance tests. I've done two tests:
> 1. Calling TopDocCollector.collect 1,000,000, 10,000,000 and 100,000,000
> times using both implementations. Here are the results:
> 1M 10M 100M
> Current Collector 218 ms 1,907ms 20,000ms
> Modified Collector 141 ms 1,297ms 12,672ms
> As you can see, the new implementation 30-40% faster.
>
> 2. Wrote some tasks in the benchmark package that makes use of the new PQ
> while executing a real search over an index with 1M documents, of small size
> (10 characters). Here are the results:
> Current TopDocCollector
> -----------------------------------------------------------------------------------------------------------------------------------------------
> ------------> Report Sum By (any) Name (5 about 6 out of 6)
> Operation round runCnt recsPerRun rec/s elapsedSec
> avgUsedMem avgTotalMem
> CreateIndex 0 1 1 10.6 0.09
> 2,219,112 4,389,376
> AddDocs_1000000 - 0 - - 1 - - 1000000 - 52,075.2 - - 19.20 -
> 34,497,176 - 52,689,408
> CloseIndex 0 2 1 0.1 16.62
> 26,178,972 51,378,688
> OpenIndex - - - 0 - - 1 - - - - 1 - - 1,000.0 - - 0.00 -
> 48,771,304 - 50,067,968
> --> MySearch 0 1 1 5.3 0.19
> 48,771,304 50,067,968
>
>
> Modified TopDocCollector
> -----------------------------------------------------------------------------------------------------------------------------------------------
> ------------> Report Sum By (any) Name (5 about 6 out of 6)
> Operation round runCnt recsPerRun rec/s elapsedSec
> avgUsedMem avgTotalMem
> CreateIndex 0 1 1 10.6 0.09
> 2,207,008 4,389,376
> AddDocs_1000000 - 0 - - 1 - - 1000000 - 50,955.4 - - 19.62 -
> 32,531,992 - 44,825,088
> CloseIndex 0 2 1 0.1 16.84
> 57,853,148 61,929,984
> OpenIndex - - - 0 - - 1 - - - - 1 - - 1,000.0 - - 0.00 -
> 57,792,136 - 61,929,984
> --> MySearch 0 1 1 7.1 0.14
> 57,939,856 61,929,984
> Notice the time difference in search (0.14 modified vs. 0.19 current). Here
> too, a 30% improvement.
>
> One thing that I wasn't able to show, but I think it's pretty much clear -->
> the new implementation causes a lot less object allocations. Consider the
> typical search for 10 results over an index with 1M documents. The current
> implementation will allocate 1M (!) ScoreDoc instances, while the new one
> will allocate 11 (10 for the PQ and 1 for reusing). On heavily loaded
> systems, this will result in far less work for the GC.
>
> I would like to suggest to reflect this new implementation in PriorityQueue
> and also modify TopDocCollector to make use of this new method. Several ways
> to do it:
> 1. Add insertWithOverflow to PQ (I hate the name and I'm willing to accept
> better ones), make insert() deprecated (let's say in 2.3) and release after
> that (2.4?) rename insertWithOverflow to insert(). A complex process, but it
> won't break existing applications' code.
> 2. Change insert's signature and state that applications that move to
> 2.3(for example), need to change their code as well (actually it won't
> compile).
> 3. Any other alternatives?
>
> And .. of course, review the classes in the Lucene code that use PQ and
> modify them as necessary.
>
> A very long email for a very simple (but important) performance improvement.
>
> Shai
>
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