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https://issues.apache.org/jira/browse/SOLR-9764?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15712868#comment-15712868
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Michael Sun commented on SOLR-9764:
-----------------------------------

bq. Lucene does have this implemented already – RoaringDocIdSet
That's cool. Let me check it out to understand pros and cons. Thanks 
[~elyograg] to point it out.

bq. I do not know how it would perform when actually used as a filterCache 
entry, compared to the current bitset implementation.
For this particular use case (a query matches all docs), the approach in patch 
should be better than roaring bitmap. The patch designed a MatchAllDocSet for 
this use case, which uses no memory other than storing the size. In addition, 
MatchAllDocSet would be faster in creating DocSet, union, intersect etc. since 
no real bit manipulation is required. 

> 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
>         Attachments: SOLR-9764.patch, SOLR-9764.patch, SOLR-9764.patch, 
> SOLR-9764.patch, SOLR-9764.patch, SOLR_9764_no_cloneMe.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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