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https://issues.apache.org/jira/browse/HIVE-13348?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15257932#comment-15257932
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Naveen Gangam commented on HIVE-13348:
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Thanks for the clarification. I understood this feature to be some sort of
queuing/batching of the events at the source that are periodically processed
while removing negating events. It wasnt clear to me if this filtering was
going to be done downstream or at the source. It now makes sense to me. Thanks
again
> Add Event Nullification support for Replication
> -----------------------------------------------
>
> Key: HIVE-13348
> URL: https://issues.apache.org/jira/browse/HIVE-13348
> Project: Hive
> Issue Type: Sub-task
> Components: Import/Export
> Reporter: Sushanth Sowmyan
> Labels: gsoc2016
>
> Replication, as implemented by HIVE-7973 works as follows:
> a) For every singly modification to the hive metastore, an event gets
> triggered that logs a notification object.
> b) Replication tools such as falcon can consume these notification objects as
> a HCatReplicationTaskIterator from
> HCatClient.getReplicationTasks(lastEventId, maxEvents, dbName, tableName).
> c) For each event, we generate statements and distcp requirements for falcon
> to export, distcp and import to do the replication (along with requisite
> changes to export and import that would allow state management).
> The big thing missing from this picture is that while it works, it is pretty
> dumb about how it works in that it will exhaustively process every single
> event generated, and will try to do the export-distcp-import cycle for all
> modifications, irrespective of whether or not that will actually get used at
> import time.
> We need to build some sort of filtering logic which can process a batch of
> events to identify events that will result in effective no-ops, and to
> nullify those events from the stream before passing them on. The goal is to
> minimize the number of events that the tools like Falcon would actually have
> to process.
> Examples of cases where event nullification would take place:
> a) CREATE-DROP cases: If an object is being created in event#34 that will
> eventually get dropped in event#47, then there is no point in replicating
> this along. We simply null out both these events, and also, any other event
> that references this object between event#34 and event#47.
> b) APPEND-APPEND : Some objects are replicated wholesale, which means every
> APPEND that occurs would cause a full export of the object in question. At
> this point, the prior APPENDS would all be supplanted by the last APPEND.
> Thus, we could nullify all the prior such events.
> Additional such cases can be inferred by analysis of the Export-Import relay
> protocol definition at
> https://issues.apache.org/jira/secure/attachment/12725999/EXIMReplicationReplayProtocol.pdf
> or by reasoning out various event processing orders possible.
> Replication, as implemented by HIVE-7973 is merely a first step for
> functional support. This work is needed for replication to be efficient at
> all, and thus, usable.
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