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Date: Thu, 24 Sep 2015 23:29:04 +0000 (UTC)
From: "Ted Yu (JIRA)" <jira@apache.org>
To: issues@hbase.apache.org
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Subject: [jira] [Commented] (HBASE-13408) HBase In-Memory Memstore
 Compaction
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    [ https://issues.apache.org/jira/browse/HBASE-13408?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14907245#comment-14907245 ] 

Ted Yu commented on HBASE-13408:
--------------------------------

bq. getCellSet() which can be very inefficient.

Under which scenario(s) would this method be inefficient ?

bq. The compaction pipeline may generate different type of mutable segments.

I thought the compaction pipeline would generate immutable segments ?

bq. HStoreFileScanner can be refactored to implement StoreSegmentScanner

Would the above be done in a future patch or different JIRA ?

> HBase In-Memory Memstore Compaction
> -----------------------------------
>
>                 Key: HBASE-13408
>                 URL: https://issues.apache.org/jira/browse/HBASE-13408
>             Project: HBase
>          Issue Type: New Feature
>            Reporter: Eshcar Hillel
>            Assignee: Eshcar Hillel
>             Fix For: 2.0.0
>
>         Attachments: HBASE-13408-trunk-v01.patch, HBASE-13408-trunk-v02.patch, HBASE-13408-trunk-v03.patch, HBASE-13408-trunk-v04.patch, HBaseIn-MemoryMemstoreCompactionDesignDocument-ver02.pdf, HBaseIn-MemoryMemstoreCompactionDesignDocument.pdf, InMemoryMemstoreCompactionEvaluationResults.pdf, InMemoryMemstoreCompactionScansEvaluationResults.pdf, StoreSegmentandStoreSegmentScannerClassHierarchies.pdf
>
>
> A store unit holds a column family in a region, where the memstore is its in-memory component. The memstore absorbs all updates to the store; from time to time these updates are flushed to a file on disk, where they are compacted. Unlike disk components, the memstore is not compacted until it is written to the filesystem and optionally to block-cache. This may result in underutilization of the memory due to duplicate entries per row, for example, when hot data is continuously updated. 
> Generally, the faster the data is accumulated in memory, more flushes are triggered, the data sinks to disk more frequently, slowing down retrieval of data, even if very recent.
> In high-churn workloads, compacting the memstore can help maintain the data in memory, and thereby speed up data retrieval. 
> We suggest a new compacted memstore with the following principles:
> 1.	The data is kept in memory for as long as possible
> 2.	Memstore data is either compacted or in process of being compacted 
> 3.	Allow a panic mode, which may interrupt an in-progress compaction and force a flush of part of the memstore.
> We suggest applying this optimization only to in-memory column families.
> A design document is attached.
> This feature was previously discussed in HBASE-5311.


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