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https://issues.apache.org/jira/browse/CASSANDRA-12888?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15818832#comment-15818832
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victor commented on CASSANDRA-12888:
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Hey Benjamin,
thanks for your feedback. At least you refer to "slow" and "painful", but not
"massive failure / data loss", right? ;)
Still the measure on the complexity to handle is not clear to me. Is it more
complex than handling "manually denormalized tables"? How much more and in
which and in which aspects, if I may ask? I'm not a Cassandra expert, so I
can't say I have deeper understanding of Tables than MVs. From what I interpret
of your comment, MVs seem to be at least more complex to operate in a
production cluster than normal tables. From a developer perspective, they are
very appealing and remove some burden on the code.
Are you aware of any description on how to deal with these "painful" scenarios?
Thanks a lot!
> Incremental repairs broken for MVs and CDC
> ------------------------------------------
>
> Key: CASSANDRA-12888
> URL: https://issues.apache.org/jira/browse/CASSANDRA-12888
> Project: Cassandra
> Issue Type: Bug
> Components: Streaming and Messaging
> Reporter: Stefan Podkowinski
> Assignee: Benjamin Roth
> Priority: Critical
> Fix For: 3.0.x, 3.x
>
>
> SSTables streamed during the repair process will first be written locally and
> afterwards either simply added to the pool of existing sstables or, in case
> of existing MVs or active CDC, replayed on mutation basis:
> As described in {{StreamReceiveTask.OnCompletionRunnable}}:
> {quote}
> We have a special path for views and for CDC.
> For views, since the view requires cleaning up any pre-existing state, we
> must put all partitions through the same write path as normal mutations. This
> also ensures any 2is are also updated.
> For CDC-enabled tables, we want to ensure that the mutations are run through
> the CommitLog so they can be archived by the CDC process on discard.
> {quote}
> Using the regular write path turns out to be an issue for incremental
> repairs, as we loose the {{repaired_at}} state in the process. Eventually the
> streamed rows will end up in the unrepaired set, in contrast to the rows on
> the sender site moved to the repaired set. The next repair run will stream
> the same data back again, causing rows to bounce on and on between nodes on
> each repair.
> See linked dtest on steps to reproduce. An example for reproducing this
> manually using ccm can be found
> [here|https://gist.github.com/spodkowinski/2d8e0408516609c7ae701f2bf1e515e8]
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