hbase-dev mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From lars hofhansl <lhofha...@yahoo.com>
Subject Re: Long running replication: possible improvements
Date Fri, 27 Jul 2012 20:17:08 GMT
So part of the problem seems to be HBase client (HTable) used in ReplicationSink taking a long
time to fail in case something is slow/wrong in the slave cluster, correct?
We faced similar problems with HTables in our app servers, where in some scenarios the client
would be waiting in various retry loops for up to 20 minutes before finally throwing an exception
(worst case is when ZK is down or not reachable)

So here for the ReplicationSink's client we could aggressively lower the various timeouts,
set ZK retry to 0, etc, since the source will retry anyway; and hence there would be less
of a chance for the ReplicationSink to hog the priority handlers.

For use we brought the "time-to-exception" down to 20s (worst case).

-- Lars

----- Original Message -----
From: Jean-Daniel Cryans <jdcryans@apache.org>
To: dev@hbase.apache.org
Sent: Thursday, July 26, 2012 4:58 PM
Subject: Re: Long running replication: possible improvements

On Wed, Jul 25, 2012 at 5:58 PM, Himanshu Vashishtha
<hvashish@cs.ualberta.ca> wrote:
> Hi,
> Replication works good when run in short span. But its performance for
> a long running setup seems to degrade at the slave cluster side. To an
> extant, it made it unresponsive in one of our testing environment. As
> per jstack on one node, all its priority handlers were blocked in the
> replicateLogEntries method, which is blocked as the cluster is in bad
> shape (2/4 nodes died; root is unassigned; and the node which had it
> previously became un-responsive; and the only other remaining node
> doesn't have any priority handler left to take care of the root region
> assignment).


Currently the best way to fix this would be to have a separate set of
handlers completely.

> The memory footprint of the app also increases (based on
> `top`; unfortunately, no gc logs at the moment).

You don't want to rely on top for that since it's a java application.
Set you Xms as big as your Xmx and your application will always use
all the memory it's given.

> The replicateLogEntries is a high QOS method; ReplicationSink's
> overall behavior is to act as a native hbase client and replicate the
> mutations in its cluster. This may take some time, in case region is
> splitting, possible gc pause, etc at the target region servers. It
> enters in the retrying loop, and this blocks the priority handler
> serving that method.
> Meanwhile, other master cluster region servers are also shipping edits
> (to this, or other regionservers). This makes the situation more
> worse.
> I wonder whether others have seen this before. Please share.

See my first answer.

> There is some scope of improvements at Sink side:
> a) ReplicationSink#replicateLogEntries: Make it a normal operation (no
> high QOS annotation), and ReplicationSink periodically checks whether
> the client is still connected or not. In case its not, just throws an
> exception and bail out. The client will do a resend of the shipment
> anyway. This frees up theĀ  handlers from blocking, and cluster's
> normal operation will not be impeded.

It wasn't working any better before HBASE-4280 :)

> b) Have a threadpool in ReplicationSink and process per table request
> in parallel. Should help in case of multi table replication.

Currently it's trying to apply the edits sequentially, going parallel
would apply them in the wrong order. Note that when a region server
fail we do continue to replicate the new edits while we also replicate
the backlog from the old server so currently it's not 100% perfect.

> c) Freeing the memory consumed by the shipped array, as soon as the
> mutation list is populated. Currently, if the call to multi is blocked
> (by any reason), the regionserver enters in the retrying logic... and
> since entries of WALEdits array is copied as Put/Delete objects, it
> can be freed.

So free up the entries array at each position after the Put or Delete
was created? We could do that, although it's not a big saving
considering that entries will be at most 64MB big. In production here
we run with just 1 MB.


View raw message