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https://issues.apache.org/jira/browse/LUCENE-6828?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14947328#comment-14947328
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Tom Burton-West commented on LUCENE-6828:
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We have a use case where some our users want set-based results. They don't care
about relevance ranking or sorting, they just want a list of all unique ids
(external, not Lucene ids) that meet some search criteria. Sometimes these sets
are in the millions. We distribute our index over many shards, so an efficient
method of grabbing all the result ids for large result sets would be extremely
useful.
Tom Burton-West
https://www.hathitrust.org/blogs/large-scale-search
> Speed up requests for many rows
> -------------------------------
>
> Key: LUCENE-6828
> URL: https://issues.apache.org/jira/browse/LUCENE-6828
> Project: Lucene - Core
> Issue Type: Improvement
> Components: core/search
> Affects Versions: 4.10.4, 5.3
> Reporter: Toke Eskildsen
> Priority: Minor
> Labels: memory, performance
>
> Standard relevance ranked searches for top-X results uses the HitQueue class
> to keep track of the highest scoring documents. The HitQueue is a binary heap
> of ScoreDocs and is pre-filled with sentinel objects upon creation.
> Binary heaps of Objects in Java does not scale well: The HitQueue uses 28
> bytes/element and memory access is scattered due to the binary heap algorithm
> and the use of Objects. To make matters worse, the use of sentinel objects
> means that even if only a tiny number of documents matches, the full amount
> of Objects is still allocated.
> As long as the HitQueue is small (< 1000), it performs very well. If top-1M
> results are requested, it performs poorly and leaves 1M ScoreDocs to be
> garbage collected.
> An alternative is to replace the ScoreDocs with a single array of packed
> longs, each long holding the score and the document ID. This strategy
> requires only 8 bytes/element and is a lot lighter on the GC.
> Some preliminary tests has been done and published at
> https://sbdevel.wordpress.com/2015/10/05/speeding-up-core-search/
> These indicate that a long[]-backed implementation is at least 3x faster than
> vanilla HitDocs for top-1M requests.
> For smaller requests, such as top-10, the packed version also seems
> competitive, when the amount of matched documents exceeds 1M. This needs to
> be investigated further.
> Going forward with this idea requires some refactoring as Lucene is currently
> hardwired to the abstract PriorityQueue. Before attempting this, it seems
> prudent to discuss whether speeding up large top-X requests has any value?
> Paging seems an obvious contender for requesting large result sets, but I
> guess the two could work in tandem, opening up for efficient large pages.
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