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https://issues.apache.org/jira/browse/HBASE-13408?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15025386#comment-15025386
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Eshcar Hillel commented on HBASE-13408:
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Latency spikes are from the evaluation we did with the 0.98 branch (posted July
14).
In the more recent evaluation we did we were able to identify the cause of the
spikes and avoid it (anyway thanks for suggesting to help :) ).
Without the spikes it is easier to see the benefit of the new feature.
> 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, HBASE-13408-trunk-v05.patch,
> HBASE-13408-trunk-v06.patch, HBASE-13408-trunk-v07.patch,
> HBASE-13408-trunk-v08.patch, HBASE-13408-trunk-v09.patch,
> HBASE-13408-trunk-v10.patch,
> HBaseIn-MemoryMemstoreCompactionDesignDocument-ver02.pdf,
> HBaseIn-MemoryMemstoreCompactionDesignDocument-ver03.pdf,
> HBaseIn-MemoryMemstoreCompactionDesignDocument-ver04.pdf,
> HBaseIn-MemoryMemstoreCompactionDesignDocument.pdf,
> InMemoryMemstoreCompactionEvaluationResults.pdf,
> InMemoryMemstoreCompactionMasterEvaluationResults.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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