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retest this please
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Github user cloud-fan commented on the issue:
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yea it's not a substitute for passing commit messages to job abort, I
already updated this PR to do it.
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Github user rdblue commented on the issue:
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> There is no restriction to let the output of data writers be visible to
other writers, so it's possible to launch a write task just for cleaning up the
data of other writers.
Agreed.
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> I'm not following what you mean here.
I'm answering the question of @steveloughran about the semantic of data
writers. Ideally transaction means the readers can only see the data after
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> The only contract Spark needs is: data written/committed by tasks should
not be visible to data source readers until the job-level commitment. But they
can be visible to others like other writing
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+1 for the ability to return statistics: the remote stores have lots of
information which committers may return
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Github user cloud-fan commented on the issue:
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Several things to discuss:
1. Since Spark can't disable speculation during runtime, currently there is
not much benefit to provide an interface for data source to disable
speculation,
Github user cloud-fan commented on the issue:
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Hi @steveloughran , thanks for your comments! We should have a detailed
specification of this framework, especially for the behaviors at Spark side.
I'll update soon.
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One other thing that would be good now and invaluable in future is for the
`DataWriter.commit()` call to return a `Map[String,Long]` of statistics
alongside the message sent to the committer.
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People may know that I'm busy with some S3 committers which work with
Hadoop MapReduce & Spark, with an import of Ryan's commtter into the Hadoop
codebase. Thisa includes changes to s3a
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