[
https://issues.apache.org/jira/browse/HBASE-6134?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13289168#comment-13289168
]
chunhui shen commented on HBASE-6134:
-------------------------------------
Writers#doRun
{code}
LOG.debug("Writer thread " + this + ": starting");
while (true) {
RegionEntryBuffer buffer = entryBuffers.getChunkToWrite();
if (buffer == null) {
// No data currently available, wait on some more to show up
synchronized (dataAvailable) {
if (shouldStop) return;
try {
dataAvailable.wait(1000);
} catch (InterruptedException ie) {
if (!shouldStop) {
throw new RuntimeException(ie);
}
}
}
continue;
}
assert buffer != null;
try {
writeBuffer(buffer);
} finally {
entryBuffers.doneWriting(buffer);
}
}
{code}
entryBuffers.getChunkToWrite() won't return null as long as there is data in
the buffer
> Improvement for split-worker to speed up distributed-split-log
> --------------------------------------------------------------
>
> Key: HBASE-6134
> URL: https://issues.apache.org/jira/browse/HBASE-6134
> Project: HBase
> Issue Type: Improvement
> Components: wal
> Reporter: chunhui shen
> Assignee: chunhui shen
> Priority: Critical
> Fix For: 0.96.0
>
> Attachments: HBASE-6134.patch, HBASE-6134v2.patch, HBASE-6134v3.patch
>
>
> First，we do the test between local-master-splitting and
> distributed-log-splitting
> Environment：34 hlog files, 5 regionservers,(after kill one, only 4 rs do ths
> splitting work), 400 regions in one hlog file
> local-master-split:60s+
> distributed-log-splitting:165s+
> In fact, in our production environment, distributed-log-splitting also took
> 60s with 30 regionservers for 34 hlog files (regionserver may be in high load)
> We found split-worker split one log file took about 20s
> (30ms~50ms per writer.close(); 10ms per create writers )
> I think we could do the improvement for this:
> Parallelizing the create and close writers in threads
> In the patch, change the logic for distributed-log-splitting same as the
> local-master-splitting and parallelizing the close in threads.
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