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From "Misha Dmitriev (JIRA)" <>
Subject [jira] [Commented] (HIVE-15882) HS2 generating high memory pressure with many partitions and concurrent queries
Date Wed, 22 Feb 2017 22:09:44 GMT


Misha Dmitriev commented on HIVE-15882:

Yes, I did take a heap dump and rerun the tool after applying the patch (actually, two patches:
the one mentioned in this ticket so far and another one, that interns some data within PartitionDesc
objects). The results are predictable: the sources of memory waste that I fixed went away,
though some other remain.

As for how much memory is saved: this question is more tricky than it sounds. In general,
the more memory you give to the Java app (the higher is -Xmx), the more it would use (it would
just run the GC less frequently). So you have to measure the size of "live set" (what remains
after full GC), but this is more difficult. In my benchmark, with its high concurrency, I
suspect it's further complicated by the fact that higher -Xmx will allow more concurrency,
and thus even the live set will probably grow. So far I think that the metric that would be
reasonably accurate is how many more concurrent requests I will be able to run in this benchmark
before OOMing its again. Any other suggestions are welcome.

> HS2 generating high memory pressure with many partitions and concurrent queries
> -------------------------------------------------------------------------------
>                 Key: HIVE-15882
>                 URL:
>             Project: Hive
>          Issue Type: Improvement
>          Components: HiveServer2
>            Reporter: Misha Dmitriev
>            Assignee: Misha Dmitriev
>         Attachments: HIVE-15882.01.patch, hs2-crash-2000p-500m-50q.txt
> I've created a Hive table with 2000 partitions, each backed by two files, with one row
in each file. When I execute some number of concurrent queries against this table, e.g. as
> {code}
> for i in `seq 1 50`; do beeline -u jdbc:hive2://localhost:10000 -n admin -p admin -e
"select count(i_f_1) from misha_table;" & done
> {code}
> it results in a big memory spike. With 20 queries I caused an OOM in a HS2 server with
-Xmx200m and with 50 queries - in the one with -Xmx500m.
> I am attaching the results of jxray ( analysis of a heap dump that was
generated in the 50queries/500m heap scenario. It suggests that there are several opportunities
to reduce memory pressure with not very invasive changes to the code:
> 1. 24.5% of memory is wasted by duplicate strings (see section 6). With String.intern()
calls added in the ~10 relevant places in the code, this overhead can be highly reduced.
> 2. Almost 20% of memory is wasted due to various suboptimally used collections (see section
8). There are many maps and lists that are either empty or have just 1 element. By modifying
the code that creates and populates these collections, we may likely save 5-10% of memory.
> 3. Almost 20% of memory is used by instances of java.util.Properties. It looks like these
objects are highly duplicate, since for each Partition each concurrently running query creates
its own copy of Partion, PartitionDesc and Properties. Thus we have nearly 100,000 (50 queries
* 2,000 partitions) Properties in memory. By interning/deduplicating these objects we may
be able to save perhaps 15% of memory.
> So overall, I think there is a good chance to reduce HS2 memory consumption in this scenario
by ~40%.

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