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From "Adam Fuchs (JIRA)" <>
Subject [jira] [Commented] (ACCUMULO-4626) improve cache hit rate via weak reference map
Date Wed, 26 Apr 2017 15:22:04 GMT


Adam Fuchs commented on ACCUMULO-4626:

I did the observations on the 1.7 branch, so the new cache wasn't an option at the time. Theoretically
speaking, LRU is the optimal cache algorithm for this particular problem, so any divergence
from that would be worse. The LruBlockCache is only mostly LRU, so the fact that it reserves
25% for blocks accessed once may make it less effective than the TinyLfuBlockCache.

I think you may want to take this behavior of accessing the same block multiple times in a
single scan in your hill climbing work -- maybe try to account for that as a single access?

> improve cache hit rate via weak reference map
> ---------------------------------------------
>                 Key: ACCUMULO-4626
>                 URL:
>             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
> {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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