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https://issues.apache.org/jira/browse/HBASE-7404?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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chunhui shen updated HBASE-7404:
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Attachment: 7404-trunk-v13.patch
Attaching newest patchv13 as review comments
> Bucket Cache:A solution about CMS,Heap Fragment and Big Cache on HBASE
> ----------------------------------------------------------------------
>
> Key: HBASE-7404
> URL: https://issues.apache.org/jira/browse/HBASE-7404
> Project: HBase
> Issue Type: New Feature
> Affects Versions: 0.94.3
> Reporter: chunhui shen
> Assignee: chunhui shen
> Fix For: 0.96.0, 0.94.5
>
> Attachments: 7404-trunk-v10.patch, 7404-trunk-v11.patch,
> 7404-trunk-v12.patch, 7404-trunk-v13.patch, BucketCache.pdf,
> hbase-7404-94v2.patch, hbase-7404-trunkv2.patch, hbase-7404-trunkv9.patch,
> Introduction of Bucket Cache.pdf
>
>
> First, thanks @neil from Fusion-IO share the source code.
> What's Bucket Cache?
> It could greatly decrease CMS and heap fragment by GC
> It support a large cache space for High Read Performance by using high speed
> disk like Fusion-io
> 1.An implementation of block cache like LruBlockCache
> 2.Self manage blocks' storage position through Bucket Allocator
> 3.The cached blocks could be stored in the memory or file system
> 4.Bucket Cache could be used as a mainly block cache(see CombinedBlockCache),
> combined with LruBlockCache to decrease CMS and fragment by GC.
> 5.BucketCache also could be used as a secondary cache(e.g. using Fusionio to
> store block) to enlarge cache space
> How about SlabCache?
> We have studied and test SlabCache first, but the result is bad, because:
> 1.SlabCache use SingleSizeCache, its use ratio of memory is low because kinds
> of block size, especially using DataBlockEncoding
> 2.SlabCache is uesd in DoubleBlockCache, block is cached both in SlabCache
> and LruBlockCache, put the block to LruBlockCache again if hit in SlabCache ,
> it causes CMS and heap fragment don't get any better
> 3.Direct heap performance is not good as heap, and maybe cause OOM, so we
> recommend using "heap" engine
> See more in the attachment and in the patch
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