hbase-issues mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From "Andrew Purtell (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (HBASE-22301) Consider rolling the WAL if the HDFS write pipeline is slow
Date Mon, 29 Apr 2019 22:48:00 GMT

    [ https://issues.apache.org/jira/browse/HBASE-22301?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16829796#comment-16829796

Andrew Purtell commented on HBASE-22301:

I sent an email to dev@hbase titled "Trunk only commits are a waste of everyone's time". I
am making this claim on that thread (smile). Let's take any response to that to the email

Back soon with a patch for branch-1 that takes the union of this approach and HBASE-21806

> Consider rolling the WAL if the HDFS write pipeline is slow
> -----------------------------------------------------------
>                 Key: HBASE-22301
>                 URL: https://issues.apache.org/jira/browse/HBASE-22301
>             Project: HBase
>          Issue Type: Improvement
>          Components: wal
>            Reporter: Andrew Purtell
>            Assignee: Andrew Purtell
>            Priority: Minor
>             Fix For: 3.0.0, 1.5.0, 2.3.0
>         Attachments: HBASE-22301-branch-1.patch, HBASE-22301-branch-1.patch, HBASE-22301-branch-1.patch,
HBASE-22301-branch-1.patch, HBASE-22301-branch-1.patch
> Consider the case when a subset of the HDFS fleet is unhealthy but suffering a gray failure
not an outright outage. HDFS operations, notably syncs, are abnormally slow on pipelines
which include this subset of hosts. If the regionserver's WAL is backed by an impacted pipeline,
all WAL handlers can be consumed waiting for acks from the datanodes in the pipeline (recall
that some of them are sick). Imagine a write heavy application distributing load uniformly
over the cluster at a fairly high rate. With the WAL subsystem slowed by HDFS level issues,
all handlers can be blocked waiting to append to the WAL. Once all handlers are blocked, the
application will experience backpressure. All (HBase) clients eventually have too many outstanding
writes and block.
> Because the application is distributing writes near uniformly in the keyspace, the probability
any given service endpoint will dispatch a request to an impacted regionserver, even a single
regionserver, approaches 1.0. So the probability that all service endpoints will be affected
approaches 1.0.
> In order to break the logjam, we need to remove the slow datanodes. Although there is
HDFS level monitoring, mechanisms, and procedures for this, we should also attempt to take
mitigating action at the HBase layer as soon as we find ourselves in trouble. It would be
enough to remove the affected datanodes from the writer pipelines. A super simple strategy
that can be effective is described below:
> This is with branch-1 code. I think branch-2's async WAL can mitigate but still can be
susceptible. branch-2 sync WAL is susceptible. 
> We already roll the WAL writer if the pipeline suffers the failure of a datanode and
the replication factor on the pipeline is too low. We should also consider how much time
it took for the write pipeline to complete a sync the last time we measured it, or the max
over the interval from now to the last time we checked. If the sync time exceeds a configured
threshold, roll the log writer then too. Fortunately we don't need to know which datanode
is making the WAL write pipeline slow, only that syncs on the pipeline are too slow and exceeding
a threshold. This is enough information to know when to roll it. Once we roll it, we will
get three new randomly selected datanodes. On most clusters the probability the new pipeline
includes the slow datanode will be low. (And if for some reason it does end up with a problematic
datanode again, we roll again.)
> This is not a silver bullet but this can be a reasonably effective mitigation.
> Provide a metric for tracking when log roll is requested (and for what reason).
> Emit a log line at log roll time that includes datanode pipeline details for further
debugging and analysis, similar to the existing slow FSHLog sync log line.
> If we roll too many times within a short interval of time this probably means there is
a widespread problem with the fleet and so our mitigation is not helping and may be exacerbating
those problems or operator difficulties. Ensure log roll requests triggered by this new feature
happen infrequently enough to not cause difficulties under either normal or abnormal conditions. A very
simple strategy that could work well under both normal and abnormal conditions is to define
a fairly lengthy interval, default 5 minutes, and then insure we do not roll more than once
during this interval for this reason.

This message was sent by Atlassian JIRA

View raw message