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From "Mikhail Antonov (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (HBASE-17018) Spooling BufferedMutator
Date Fri, 04 Nov 2016 21:17:58 GMT

    [ https://issues.apache.org/jira/browse/HBASE-17018?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15637715#comment-15637715
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Mikhail Antonov commented on HBASE-17018:
-----------------------------------------

At a high level idea of having BufferedMutator or similar client API manage separate persistent
storage with atomicity / replay guarantees sounds somewhat weird to me. Is that the problem
to be solved outside of HBase? Or should it be bulk ingest or some sort as mentioned above?

> Spooling BufferedMutator
> ------------------------
>
>                 Key: HBASE-17018
>                 URL: https://issues.apache.org/jira/browse/HBASE-17018
>             Project: HBase
>          Issue Type: New Feature
>            Reporter: Joep Rottinghuis
>         Attachments: YARN-4061 HBase requirements for fault tolerant writer.pdf
>
>
> For Yarn Timeline Service v2 we use HBase as a backing store.
> A big concern we would like to address is what to do if HBase is (temporarily) down,
for example in case of an HBase upgrade.
> Most of the high volume writes will be mostly on a best-effort basis, but occasionally
we do a flush. Mainly during application lifecycle events, clients will call a flush on the
timeline service API. In order to handle the volume of writes we use a BufferedMutator. When
flush gets called on our API, we in turn call flush on the BufferedMutator.
> We would like our interface to HBase be able to spool the mutations to a filesystems
in case of HBase errors. If we use the Hadoop filesystem interface, this can then be HDFS,
gcs, s3, or any other distributed storage. The mutations can then later be re-played, for
example through a MapReduce job.



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