Github user HeartSaVioR commented on the issue:
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Abandoning the patch. While I think the JIRA issue is still valid, looks
like we should address watermark issue to have correct number of late events.
Thanks for reviewing @jose-torres @arunmaha
Github user jose-torres commented on the issue:
https://github.com/apache/spark/pull/21617
Well, "clear" is relative. Since we're trying to provide functionality in
the Dataframe API, it's perfectly alright for the RDD graph to end up looking a
bit weird. It seems feasible to do somet
Github user HeartSaVioR commented on the issue:
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@jose-torres
Yes, you're right. They would be the rows which applies other
transformation and filtering, not origin input rows. I just haven't find proper
alternative word than "input row"
Github user jose-torres commented on the issue:
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LGTM, but note that the rows being counted here are the rows persisted into
the state store, which aren't necessarily the input rows. So the side-channel
described in the JIRA would be orthogona
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Github user dongjoon-hyun commented on the issue:
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Retest this please.
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add to whitelist
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cc. @tdas @zsxwing @jose-torres @jerryshao @arunmahadevan @HyukjinKwon
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