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https://issues.apache.org/jira/browse/HBASE-6852?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13460736#comment-13460736
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Todd Lipcon commented on HBASE-6852:
------------------------------------
bq. getAndIncrement into just one cpu instruction
True, but it's a pretty expensive instruction, since it has to steal that cache
line from whichever other core used it previously, and I believe acts as a full
memory barrier as well (eg flushing write-combining buffers)
The cliff click counter is effective but has more memory usage. Aggregating
stuff locally and pushing to metrics seems ideal, but if we can't do that
easily, then having the metrics per-thread and then occasionally grabbing them
would work too. Memcached metrics work like that.
> SchemaMetrics.updateOnCacheHit costs too much while full scanning a table
> with all of its fields
> ------------------------------------------------------------------------------------------------
>
> Key: HBASE-6852
> URL: https://issues.apache.org/jira/browse/HBASE-6852
> Project: HBase
> Issue Type: Improvement
> Components: metrics
> Affects Versions: 0.94.0
> Reporter: Cheng Hao
> Priority: Minor
> Labels: performance
> Fix For: 0.94.3, 0.96.0
>
> Attachments: onhitcache-trunk.patch
>
>
> The SchemaMetrics.updateOnCacheHit costs too much while I am doing the full
> table scanning.
> Here is the top 5 hotspots within regionserver while full scanning a table:
> (Sorry for the less-well-format)
> CPU: Intel Westmere microarchitecture, speed 2.262e+06 MHz (estimated)
> Counted CPU_CLK_UNHALTED events (Clock cycles when not halted) with a unit
> mask of 0x00 (No unit mask) count 5000000
> samples % image name symbol name
> -------------------------------------------------------------------------------
> 98447 13.4324 14033.jo void
> org.apache.hadoop.hbase.regionserver.metrics.SchemaMetrics.updateOnCacheHit(org.apache.hadoop.hbase.io.hfile.BlockType$BlockCategory,
> boolean)
> 98447 100.000 14033.jo void
> org.apache.hadoop.hbase.regionserver.metrics.SchemaMetrics.updateOnCacheHit(org.apache.hadoop.hbase.io.hfile.BlockType$BlockCategory,
> boolean) [self]
> -------------------------------------------------------------------------------
> 45814 6.2510 14033.jo int
> org.apache.hadoop.hbase.KeyValue$KeyComparator.compareRows(byte[], int, int,
> byte[], int, int)
> 45814 100.000 14033.jo int
> org.apache.hadoop.hbase.KeyValue$KeyComparator.compareRows(byte[], int, int,
> byte[], int, int) [self]
> -------------------------------------------------------------------------------
> 43523 5.9384 14033.jo boolean
> org.apache.hadoop.hbase.regionserver.StoreFileScanner.reseek(org.apache.hadoop.hbase.KeyValue)
> 43523 100.000 14033.jo boolean
> org.apache.hadoop.hbase.regionserver.StoreFileScanner.reseek(org.apache.hadoop.hbase.KeyValue)
> [self]
> -------------------------------------------------------------------------------
> 42548 5.8054 14033.jo int
> org.apache.hadoop.hbase.KeyValue$KeyComparator.compare(byte[], int, int,
> byte[], int, int)
> 42548 100.000 14033.jo int
> org.apache.hadoop.hbase.KeyValue$KeyComparator.compare(byte[], int, int,
> byte[], int, int) [self]
> -------------------------------------------------------------------------------
> 40572 5.5358 14033.jo int
> org.apache.hadoop.hbase.io.hfile.HFileBlockIndex$BlockIndexReader.binarySearchNonRootIndex(byte[],
> int, int, java.nio.ByteBuffer, org.apache.hadoop.io.RawComparator)~1
> 40572 100.000 14033.jo int
> org.apache.hadoop.hbase.io.hfile.HFileBlockIndex$BlockIndexReader.binarySearchNonRootIndex(byte[],
> int, int, java.nio.ByteBuffer, org.apache.hadoop.io.RawComparator)~1 [self]
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