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https://issues.apache.org/jira/browse/HBASE-13259?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14368154#comment-14368154
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zhangduo commented on HBASE-13259:
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I mean could we test it with a size much larger than available memory? i.e.,
100G RAM, 500G bucket cache on SSD?
If we only test it with a size smaller than available memory, then I think we
need to beat the offheap engine, not file engine(It is good if you can beat
both of them:))
> mmap() based BucketCache IOEngine
> ---------------------------------
>
> Key: HBASE-13259
> URL: https://issues.apache.org/jira/browse/HBASE-13259
> Project: HBase
> Issue Type: New Feature
> Components: BlockCache
> Affects Versions: 0.98.10
> Reporter: Zee Chen
> Fix For: 2.2.0
>
> Attachments: HBASE-13259-v2.patch, HBASE-13259.patch, ioread-1.svg,
> mmap-0.98-v1.patch, mmap-1.svg, mmap-trunk-v1.patch
>
>
> Of the existing BucketCache IOEngines, FileIOEngine uses pread() to copy data
> from kernel space to user space. This is a good choice when the total working
> set size is much bigger than the available RAM and the latency is dominated
> by IO access. However, when the entire working set is small enough to fit in
> the RAM, using mmap() (and subsequent memcpy()) to move data from kernel
> space to user space is faster. I have run some short keyval gets tests and
> the results indicate a reduction of 2%-7% of kernel CPU on my system,
> depending on the load. On the gets, the latency histograms from mmap() are
> identical to those from pread(), but peak throughput is close to 40% higher.
> This patch modifies ByteByfferArray to allow it to specify a backing file.
> Example for using this feature: set hbase.bucketcache.ioengine to
> mmap:/dev/shm/bucketcache.0 in hbase-site.xml.
> Attached perf measured CPU usage breakdown in flames graph.
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