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https://issues.apache.org/jira/browse/HBASE-3242?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12970038#action_12970038
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stack commented on HBASE-3242:
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What about doing the following (I thought this was what you were describing
Nicolas but it seems like you are describing something else). When we hit N
HLogs, we currently flush those MemStores that hold the oldest edits. What if
in stead, we ran through the oldest M HLogs and rewrote them all into one new
HLog file dropping edits that have made it into StoreFiles: i.e. those whose
seqid is < what is the oldest seqid on the regionserver. We'd then atomically
swap out the N old HLogs, moving aside for replication or snapshotting or
whatever but the HRS would now replace the N HLogs w/ the newly written HLog in
its HLog accounting. This would not be a compaction, more a cleaning process.
> HLog Compactions
> ----------------
>
> Key: HBASE-3242
> URL: https://issues.apache.org/jira/browse/HBASE-3242
> Project: HBase
> Issue Type: Improvement
> Components: regionserver
> Reporter: Nicolas Spiegelberg
>
> Currently, our memstore flush algorithm is pretty trivial. We let it grow to
> a flushsize and flush a region or grow to a certain log count and then flush
> everything below a seqid. In certain situations, we can get big wins from
> being more intelligent with our memstore flush algorithm. I suggest we look
> into algorithms to intelligently handle HLog compactions. By compaction, I
> mean replacing existing HLogs with new HLogs created using the contents of a
> memstore snapshot. Situations where we can get huge wins:
> 1. In the incrementColumnValue case, N HLog entries often correspond to a
> single memstore entry. Although we may have large HLog files, our memstore
> could be relatively small.
> 2. If we have a hot region, the majority of the HLog consists of that one
> region and other region edits would be minuscule.
> In both cases, we are forced to flush a bunch of very small stores. Its
> really hard for a compaction algorithm to be efficient when it has no
> guarantees of the approximate size of a new StoreFile, so it currently does
> unconditional, inefficient compactions. Additionally, compactions & flushes
> suck because they invalidate cache entries: be it memstore or LRUcache. If
> we can limit flushes to cases where we will have significant HFile output on
> a per-Store basis, we can get improved performance, stability, and reduced
> failover time.
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