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https://issues.apache.org/jira/browse/SOLR-9764?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15851332#comment-15851332
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Varun Thacker commented on SOLR-9764:
-------------------------------------
I tried running a small benchmark to see how much memory does this save:
Indexed 10M documents and started solr with 4G of heap. Then on this static
index I fired 10k queries {code}{!cache=false}*:*{code}
Freed memory was calculated by firing 10k queries then forcing a GC and reading
the freed memory in GC viewer.
Freed Memory:
Trunk with this patch: 1301MB
Solr 6.3 : 1290MB
A FixedBitSet of 10M entries translates to a long array of size=156250 = 1.2 MB
The filterCache/queryResultCache didn't have any entries but maybe I'm missing
something here. I'll look into the test setup over the next couple of days to
see what's wrong
> Design a memory efficient DocSet if a query returns all docs
> ------------------------------------------------------------
>
> Key: SOLR-9764
> URL: https://issues.apache.org/jira/browse/SOLR-9764
> Project: Solr
> Issue Type: Improvement
> Security Level: Public(Default Security Level. Issues are Public)
> Reporter: Michael Sun
> Assignee: Yonik Seeley
> Fix For: 6.5, master (7.0)
>
> Attachments: SOLR_9764_no_cloneMe.patch, SOLR-9764.patch,
> SOLR-9764.patch, SOLR-9764.patch, SOLR-9764.patch, SOLR-9764.patch,
> SOLR-9764.patch, SOLR-9764.patch, SOLR-9764.patch
>
>
> In some use cases, particularly use cases with time series data, using
> collection alias and partitioning data into multiple small collections using
> timestamp, a filter query can match all documents in a collection. Currently
> BitDocSet is used which contains a large array of long integers with every
> bits set to 1. After querying, the resulted DocSet saved in filter cache is
> large and becomes one of the main memory consumers in these use cases.
> For example. suppose a Solr setup has 14 collections for data in last 14
> days, each collection with one day of data. A filter query for last one week
> data would result in at least six DocSet in filter cache which matches all
> documents in six collections respectively.
> This is to design a new DocSet that is memory efficient for such a use case.
> The new DocSet removes the large array, reduces memory usage and GC pressure
> without losing advantage of large filter cache.
> In particular, for use cases when using time series data, collection alias
> and partition data into multiple small collections using timestamp, the gain
> can be large.
> For further optimization, it may be helpful to design a DocSet with run
> length encoding. Thanks [~mmokhtar] for suggestion.
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