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From "Ben Manes (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (ACCUMULO-4626) improve cache hit rate via weak reference map
Date Wed, 26 Apr 2017 05:54:04 GMT

    [ https://issues.apache.org/jira/browse/ACCUMULO-4626?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15984217#comment-15984217
] 

Ben Manes commented on ACCUMULO-4626:
-------------------------------------

I would be interested to know if there was a difference in hit rates between the two caches,
prior to your improvement. It tends to evict new and idle arrivals more aggressively, as those
are often pollutants. That could be beneficial or a liability, depending on how recency biased
the workload is. We have an adaptive approach that uses bill climbing to tune towards recency
or frequency, which corrects for this. I hope to incorporate that after I finish my timer
wheel based policy (variable expiration).

> 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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