[ 
https://issues.apache.org/jira/browse/HBASE-13259?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14503941#comment-14503941
 ] 

zhangduo commented on HBASE-13259:
----------------------------------

I can pick this up and address the 'ugly ByteBufferArray'.
But we do not have enough time to test it on large dataset if we want to catch 
up with the first rc of 1.1 I think. It is a tuning work, the time we need is 
unpredictable. We can file a new issue to hold the tuning work and resolve this 
issue before the first rc of 1.1.

What do you think? [~ndimiduk] 
Thanks.

> 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: 2.0.0, 1.1.0
>
>         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.



--
This message was sent by Atlassian JIRA
(v6.3.4#6332)

Reply via email to