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From "Josh Elser (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (ACCUMULO-4626) improve cache hit rate via weak reference map
Date Thu, 04 May 2017 18:44:04 GMT

    [ https://issues.apache.org/jira/browse/ACCUMULO-4626?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15997203#comment-15997203
] 

Josh Elser commented on ACCUMULO-4626:
--------------------------------------

bq. In either case, I'm wondering if we should be looking at off-heap caching in general.

With the limits of the JVM and more and more memory on new hardware being the norm, it's not
a bad idea.

HBase's hybrid on-heap+off-heap approach for blockcache has done pretty well (there are some
good benchmarks out there too from Nick Dimiduk -- albeit from a few years ago by now). They
keep an "L1" block cache on heap (LruMap, TinyLFU) and use BucketCache (with the file backend)
as an "L2" to be able to really saturate extra memory not being used on the machine. It's
a nice approach where you can stay on the JVM for really hot stuff, but still use available
memory without incurring the pain of large JVM heaps.

> improve cache hit rate via weak reference map
> ---------------------------------------------
>
>                 Key: ACCUMULO-4626
>                 URL: https://issues.apache.org/jira/browse/ACCUMULO-4626
>             Project: Accumulo
>          Issue Type: Improvement
>          Components: tserver
>            Reporter: Adam Fuchs
>              Labels: performance, stability
>          Time Spent: 1h
>  Remaining Estimate: 0h
>
> When a single iterator tree references the same RFile blocks in different branches we
sometimes get cache misses for one iterator even though the requested block is held in memory
by another iterator. This is particularly important when using something like the IntersectingIterator
to intersect many deep copies. Instead of evicting completely, keeping evicted blocks into
a WeakReference value map can avoid re-reading blocks that are currently referenced by another
deep copied source iterator.
> We've seen this in the field for some of Sqrrl's queries against very large tablets.
The total memory usage for these queries can be equal to the size of all the iterator block
reads times the number of readahead threads times the number of files times the number of
IntersectingIterator children when cache miss rates are high. This might work out to something
like:
> {code}
> 16 readahead threads * 200 deep copied children * 99% cache miss rate * 20 files * 252KB
per reader = ~16GB of memory
> {code}
> In most cases, evicting to a weak reference value map changes the cache miss rate from
very high to very low and has a dramatic effect on total memory usage.



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