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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, 20 Apr 2017 01:46:04 GMT

    [ https://issues.apache.org/jira/browse/ACCUMULO-4626?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15975909#comment-15975909
] 

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

Thanks for the explanation, Adam.

bq. the sum of sizes of the referenced blocks across all of the concurrently running queries
exceeds the 25% or so of the total cache that is reserved for single-use blocks

That seems really aggressive in terms of eviction to me. Are we getting poor cache utilization
because of that? Maybe there's some other characteristic which keeps more-often accessed blocks
in cache?

I'm trying to get a better understanding (admittedly without yet pulling up the code) about
how this would affect more real-life workloads.

> 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: 10m
>  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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