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* previously the smallest value in the heap and now has been
replaced
by a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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