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From "Ben Manes (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (HBASE-15560) TinyLFU-based BlockCache
Date Tue, 04 Oct 2016 21:11:20 GMT

    [ https://issues.apache.org/jira/browse/HBASE-15560?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15546678#comment-15546678
] 

Ben Manes commented on HBASE-15560:
-----------------------------------

I know the frustration and agree that feature flags should have a clear deprecation cycle.
You might want to consider a special deprecation annotation indicating the release (or date)
that a flag should be removed by. A custom checkstyle / pmd rule would be easy to write and
allow for validating in the build. If the flag is rot due to lack of testing then it pushes
for a decision to be made.

In general I would have performance tested this myself, but due to not being an HBase user
that would be meaningless. Its been fun to provide the patch and work through the process,
as requested by [~ebortnik], but I do need help on that last mile. So I am looking forward
to digging into the results when we have some hard numbers.

> TinyLFU-based BlockCache
> ------------------------
>
>                 Key: HBASE-15560
>                 URL: https://issues.apache.org/jira/browse/HBASE-15560
>             Project: HBase
>          Issue Type: Improvement
>          Components: BlockCache
>    Affects Versions: 2.0.0
>            Reporter: Ben Manes
>            Assignee: Ben Manes
>         Attachments: HBASE-15560.patch, HBASE-15560.patch, HBASE-15560.patch, HBASE-15560.patch,
HBASE-15560.patch, HBASE-15560.patch, HBASE-15560.patch, tinylfu.patch
>
>
> LruBlockCache uses the Segmented LRU (SLRU) policy to capture frequency and recency of
the working set. It achieves concurrency by using an O( n ) background thread to prioritize
the entries and evict. Accessing an entry is O(1) by a hash table lookup, recording its logical
access time, and setting a frequency flag. A write is performed in O(1) time by updating the
hash table and triggering an async eviction thread. This provides ideal concurrency and minimizes
the latencies by penalizing the thread instead of the caller. However the policy does not
age the frequencies and may not be resilient to various workload patterns.
> W-TinyLFU ([research paper|http://arxiv.org/pdf/1512.00727.pdf]) records the frequency
in a counting sketch, ages periodically by halving the counters, and orders entries by SLRU.
An entry is discarded by comparing the frequency of the new arrival (candidate) to the SLRU's
victim, and keeping the one with the highest frequency. This allows the operations to be performed
in O(1) time and, though the use of a compact sketch, a much larger history is retained beyond
the current working set. In a variety of real world traces the policy had [near optimal hit
rates|https://github.com/ben-manes/caffeine/wiki/Efficiency].
> Concurrency is achieved by buffering and replaying the operations, similar to a write-ahead
log. A read is recorded into a striped ring buffer and writes to a queue. The operations are
applied in batches under a try-lock by an asynchronous thread, thereby track the usage pattern
without incurring high latencies ([benchmarks|https://github.com/ben-manes/caffeine/wiki/Benchmarks#server-class]).
> In YCSB benchmarks the results were inconclusive. For a large cache (99% hit rates) the
two caches have near identical throughput and latencies with LruBlockCache narrowly winning.
At medium and small caches, TinyLFU had a 1-4% hit rate improvement and therefore lower latencies.
The lack luster result is because a synthetic Zipfian distribution is used, which SLRU performs
optimally. In a more varied, real-world workload we'd expect to see improvements by being
able to make smarter predictions.
> The provided patch implements BlockCache using the [Caffeine|https://github.com/ben-manes/caffeine]
caching library (see HighScalability [article|http://highscalability.com/blog/2016/1/25/design-of-a-modern-cache.html]).
> Edward Bortnikov and Eshcar Hillel have graciously provided guidance for evaluating this
patch ([github branch|https://github.com/ben-manes/hbase/tree/tinylfu]).



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