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retest this, please
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@zsxwing
Given that Spark 2.4 vote passes, could we revisit and make progress on
this?
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@gaborgsomogyi Yeah... I'm just waiting for it. Btw I proposed solution on
SPARK-10816 as well and it is also waiting for response. I'm going to work on
another item or review others so that I
Github user gaborgsomogyi commented on the issue:
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> Do you have more to review?
No. BTW I've just seen a -1 for 2.4 RC...
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Kindly ask for reviewing. Please never mind when you're busy with fixing
bugs on Spark 2.4 RC.
@gaborgsomogyi I guess I left two things for committer decision: 1. define
soft boundary
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Just rebased.
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@gaborgsomogyi Totally makes sense. Let me address while the patch is
reviewed by committers. I may get recommendations to rename the config or even
more, so addressing documentation would be
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One more thing just came to my mind is the documentation. The parameter
documentation is a gap even for the original feature. As it has been grown and
several additional parameters added it
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retest this, please
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> just wondering why org.apache.spark.sql.kafka010.CachedKafkaProducer uses
com.google.common.cache.LoadingCache?
Because KafkaProducer is thread-safe unless it enables transaction,
Github user gaborgsomogyi commented on the issue:
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No objection about `org.apache.commons.pool2.impl.GenericKeyedObjectPool`
stuff but just wondering why
`org.apache.spark.sql.kafka010.CachedKafkaProducer` uses
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Now vote for Spark 2.4 is in progress. If we are not in stand-by mode for
any blocker issues for Spark 2.4 RC, I'd be really happy if someone could
revisit this and continue reviewing.
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Regarding metrics in FetchedDataPool, I just add basic metrics so that
tests can leverage on verification. I was adding numActive as well as numIdle,
but tracking and measuring them needs more
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@zsxwing
If it means code freeze for 2.4 is just around the corner then sure! We can
focus on blockers for releasing 2.4, and revisit this again. Let me reflect
@gaborgsomogyi review
Github user zsxwing commented on the issue:
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Thanks for your PR. This is really a big change. It will need very careful
review as it changes a lot of critical code path and the current Kafka consumer
logic is really complicated. Let's hold
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Retest this, please.
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retest this please
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retest this, please
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Two tests failed and not relevant to this patch.
* org.apache.spark.scheduler.DAGSchedulerSuite.Barrier task failures from
the same stage attempt don't trigger multiple stage retries
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retest this, please
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From the stack trace of test failure, it doesn't look like relevant to the
code change I guess. Jenkins shows REGRESSION but the test is added at Aug 25,
2018 so aged less than 7 days, which is
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Updated the description of PR to reflect the new approach.
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I just applied a new approach: "separate of concerns". This approach does
pooling for both kafka consumers as well as fetched data.
Both pools support eviction on idle objects, which
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Thanks @attilapiros I fixed the missing spots you left comments.
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