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https://issues.apache.org/jira/browse/LUCENE-5299?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13847577#comment-13847577
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Otis Gospodnetic commented on LUCENE-5299:
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{quote}
I think this could have real-world applicability, but I don't have evidence yet
in terms of a high query concurrency benchmark. Let's take as an example a
32-core server that serves 100 QPS at an average latency of 100ms. You'd expect
10 search tasks/threads to be active on average. So in theory you have 22 cores
available for helping out with the search.
{quote}
In other words somebody bought overly expensive server? Partial-joking aside,
sure, yes, that can happen. Without looking at the patch, I like the idea -
why not if the ability to parallelize improves query latency in such
situations, while not negatively impacting those whose CPU cores are already
being pushed to the max through query concurrency.
Showing more numbers will help convince everyone. :)
> Refactor Collector API for parallelism
> --------------------------------------
>
> Key: LUCENE-5299
> URL: https://issues.apache.org/jira/browse/LUCENE-5299
> Project: Lucene - Core
> Issue Type: Improvement
> Reporter: Shikhar Bhushan
> Attachments: LUCENE-5299.patch, LUCENE-5299.patch, LUCENE-5299.patch,
> LUCENE-5299.patch, LUCENE-5299.patch, benchmarks.txt
>
>
> h2. Motivation
> We should be able to scale-up better with Solr/Lucene by utilizing multiple
> CPU cores, and not have to resort to scaling-out by sharding (with all the
> associated distributed system pitfalls) when the index size does not warrant
> it.
> Presently, IndexSearcher has an optional constructor arg for an
> ExecutorService, which gets used for searching in parallel for call paths
> where one of the TopDocCollector's is created internally. The
> per-atomic-reader search happens in parallel and then the
> TopDocs/TopFieldDocs results are merged with locking around the merge bit.
> However there are some problems with this approach:
> * If arbitary Collector args come into play, we can't parallelize. Note that
> even if ultimately results are going to a TopDocCollector it may be wrapped
> inside e.g. a EarlyTerminatingCollector or TimeLimitingCollector or both.
> * The special-casing with parallelism baked on top does not scale, there are
> many Collector's that could potentially lend themselves to parallelism, and
> special-casing means the parallelization has to be re-implemented if a
> different permutation of collectors is to be used.
> h2. Proposal
> A refactoring of collectors that allows for parallelization at the level of
> the collection protocol.
> Some requirements that should guide the implementation:
> * easy migration path for collectors that need to remain serial
> * the parallelization should be composable (when collectors wrap other
> collectors)
> * allow collectors to pick the optimal solution (e.g. there might be memory
> tradeoffs to be made) by advising the collector about whether a search will
> be parallelized, so that the serial use-case is not penalized.
> * encourage use of non-blocking constructs and lock-free parallelism,
> blocking is not advisable for the hot-spot of a search, besides wasting
> pooled threads.
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