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From "Eshcar Hillel (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (HBASE-13408) HBase In-Memory Memstore Compaction
Date Tue, 21 Jul 2015 11:47:06 GMT

    [ https://issues.apache.org/jira/browse/HBASE-13408?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14634999#comment-14634999
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Eshcar Hillel commented on HBASE-13408:
---------------------------------------

Is your first concern ``how can an admin safely decide on the number of region per region
server if the memory trace of a region may be bigger than flush size?''
First, this can happen also with default memstore implementation, and for this reason the
blocking flush size is defined, and we make sure not to cross this upper limit even with compacted
memstore implementation.
Second, while less trivial, it is still possible to come up with a reasonable computation
if you have an upper limit on the number of regions with compacted memstore at any point in
time.

Regarding you second question, the compaction pipeline is composed of memstore segments (1
or more). Each memstore segment has a cell set, currently this is the same data structure
as in the active segment, namely a skip list. If found useful it is possible to change the
format in which the cells are stored in the pipeline after compaction.

[~anoop.hbase] I hope to answer your questions.

> 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
>         Attachments: HBaseIn-MemoryMemstoreCompactionDesignDocument-ver02.pdf, HBaseIn-MemoryMemstoreCompactionDesignDocument.pdf,
InMemoryMemstoreCompactionEvaluationResults.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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