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From "Ivan Bella (JIRA)" <>
Subject [jira] [Created] (ACCUMULO-4777) Root tablet got spammed with 1.8 million log entries
Date Fri, 05 Jan 2018 16:48:00 GMT
Ivan Bella created ACCUMULO-4777:

             Summary: Root tablet got spammed with 1.8 million log entries
                 Key: ACCUMULO-4777
             Project: Accumulo
          Issue Type: Bug
    Affects Versions: 1.8.1
            Reporter: Ivan Bella
            Priority: Critical

We had a tserver that was handling accumulo.metadata tablets that somehow got into a loop
where it created over 22K empty wal logs.  There were around 70 metadata tablets and this
resulted in around 1.8 million log entries in added to the accumulo.root table.  The only
reason it stopped creating wal logs is because it ran out of open file handles.  This took
us many hours and cups of coffee to clean up.

The log contained the following messages in a tight loop:

log.TabletServerLogger INFO : Using next log hdfs://...
tserver.TabletServfer INFO : Writing log marker for hdfs://...
tserver.TabletServer INFO : Marking hdfs://... closed
log.DfsLogger INFO : Slow sync cost ...

Unfortunately we did not have DEBUG turned on so we have no debug messages.

Tracking through the code there are three places where the TabletServerLogger.close method
is called:
1) via resetLoggers in the TabletServerLogger, but nothing calls this method so this is ruled
2) when the log gets too large or too old, but neither of those checks should have been hitting
3) In a loop that is executed (while (!success)) in the TabletServerLogger.write method. 
In this case when we unsuccessfullty write something to the wal, then that one is closed and
a new one is created.  This loop will go forever until we successfully write out the entry.
 A DfsLogger.LogClosedException seems the most logical reason.  This is most likely because
a ClosedChannelException was thrown from the DfsLogger.write methods (around line 609 in DfsLogger).

So the root cause was most likely hadoop related.  However in accumulo we probably should
not be doing a tight retry loop around a hadoop failure.  I recommend at a minimum doing some
sort of exponential back off and perhaps setting a limit on the number of retries resulting
in a critical tserver failure.

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