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https://issues.apache.org/jira/browse/HBASE-17018?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15765627#comment-15765627
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Joep Rottinghuis commented on HBASE-17018:
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[~enis] thanks for the comments. Interesting food for thought.
I should have made that more clear in the requirements doc, but for ATS we
actually have many writers and a shared bank of readers. The Yarn Resource
Manager does have its own writer, but there will be a writer per active
application in the cluster. In the current version these are spawned in the
NodeManager as an auxiliary service, but we intend to make the per application
writer a specially managed standalone container. For large deployments that
means that there could be hundreds of parallel writers.
On our case we launch ~1K containers per second. If we write 100 metrics each,
the total volume written into HBase is considerable, and that isn't counting
the longer running applications that want to send their data between once per
minute and once per 10 minutes (depending on what the particular HBase cluster
can handle).
On top of that we will probably have one shared HBase cluster (per datacenter)
hosting data for multiple Yarn clusters.
The simplicity of always dual writing does sound appealing. The dependency on
yet another service would be hard to sell. The hard dependency on HBase being
up is exactly what we're trying to tackle in this jira.
We'll discuss with the other ATS devs to see if adding a BK type of solution is
tenable.
> Spooling BufferedMutator
> ------------------------
>
> Key: HBASE-17018
> URL: https://issues.apache.org/jira/browse/HBASE-17018
> Project: HBase
> Issue Type: New Feature
> Reporter: Joep Rottinghuis
> Attachments: HBASE-17018.master.001.patch,
> HBASE-17018.master.002.patch, HBASE-17018.master.003.patch,
> HBASE-17018.master.004.patch,
> HBASE-17018SpoolingBufferedMutatorDesign-v1.pdf, 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.
> https://reviews.apache.org/r/54882/
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