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2018-06-21 Thread squito
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2018-06-19 Thread attilapiros
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2018-06-18 Thread squito
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2018-06-18 Thread tgravescs
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2018-06-15 Thread squito
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2018-06-15 Thread attilapiros
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2018-06-12 Thread squito
Github user squito commented on the issue: https://github.com/apache/spark/pull/21068 Tom and I had a chance to discuss this in person, and after some back and forth I think we decided that maybe its best to remove the limit but have the application fail if the entire cluster is

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2018-05-31 Thread squito
Github user squito commented on the issue: https://github.com/apache/spark/pull/21068 hey sorry I have been meaning to respond to this but keep getting sidetracked. As Tom and I are going to meet in person next week anyway, I figure at this point it makes sense to just wait till we

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2018-05-30 Thread tgravescs
Github user tgravescs commented on the issue: https://github.com/apache/spark/pull/21068 well the downside to that and not just failing the application is similar to what @squito was mentioning, if the cluster is just busy and you can't get containers on those last few nodes, it

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2018-05-30 Thread attilapiros
Github user attilapiros commented on the issue: https://github.com/apache/spark/pull/21068 @tgravescs what about removing YARN_BLACKLIST_MAX_NODE_BLACKLIST_RATIO config and when the set of backlisted nodes reaches numClusterNodes I stop synchronising the backlisted nodes toward YARN

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2018-05-29 Thread tgravescs
Github user tgravescs commented on the issue: https://github.com/apache/spark/pull/21068 so specifically on the limit, I'm ok with removing it as long as we have the basic check to fail. I guess perhaps you are saying the limit and that check are essentially the same thing? I was

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2018-05-23 Thread squito
Github user squito commented on the issue: https://github.com/apache/spark/pull/21068 I mean when `YarnAllocatorBlacklistTracker` decides to blacklist because of allocation failures, it doesn't send any message back to the driver -- so the driver doesn't have a msg in the logs, nor

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2018-05-23 Thread tgravescs
Github user tgravescs commented on the issue: https://github.com/apache/spark/pull/21068 What do you mean by adding notification to the driver? Like I mentioned I'm fine with removing the limit for now but I think we have to do something here if the entire cluster gets blacklisted,

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2018-05-23 Thread squito
Github user squito commented on the issue: https://github.com/apache/spark/pull/21068 I totally understand your motivation for wanting the limit. But I'm trying to balance that against behavior which might not really achieve the desired effect and be even more confusing in some

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2018-05-22 Thread tgravescs
Github user tgravescs commented on the issue: https://github.com/apache/spark/pull/21068 Ah, sorry haven't had time to get to back to this. Yeah the driver interaction could be an issue. But whether its the limit or just the yarn side blacklisting I think you would need some

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2018-05-21 Thread squito
Github user squito commented on the issue: https://github.com/apache/spark/pull/21068 ping @tgravescs . honestly I still don't love the blacklist limit, especially since it makes reporting back to the driver pretty confusing, and I don't think it buys us much. But I can live with

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[GitHub] spark issue #21068: [SPARK-16630][YARN] Blacklist a node if executors won't ...

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[GitHub] spark issue #21068: [SPARK-16630][YARN] Blacklist a node if executors won't ...

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[GitHub] spark issue #21068: [SPARK-16630][YARN] Blacklist a node if executors won't ...

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[GitHub] spark issue #21068: [SPARK-16630][YARN] Blacklist a node if executors won't ...

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2018-04-26 Thread SparkQA
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[GitHub] spark issue #21068: [SPARK-16630][YARN] Blacklist a node if executors won't ...

2018-04-25 Thread squito
Github user squito commented on the issue: https://github.com/apache/spark/pull/21068 A couple more high-level thoughts: 1) Do we want to have a event posted about the node getting blacklisted? I think it would be useful. But then there needs to be a msg from the

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2018-04-20 Thread tgravescs
Github user tgravescs commented on the issue: https://github.com/apache/spark/pull/21068 ok sounds fine to me, so we should review as is then --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For

[GitHub] spark issue #21068: [SPARK-16630][YARN] Blacklist a node if executors won't ...

2018-04-19 Thread squito
Github user squito commented on the issue: https://github.com/apache/spark/pull/21068 @tgravescs on the blacklist ratio for task-based blacklisting -- there is nothing, but there are some related jiras: [SPARK-22148](https://issues.apache.org/jira/browse/SPARK-22148) &

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2018-04-18 Thread tgravescs
Github user tgravescs commented on the issue: https://github.com/apache/spark/pull/21068 thanks for filing that jira @squito, I agree we should have blacklisting work with dynamic allocation disabled as well. (A bit of a tangent from this jira) I'm actually wondering now about the

[GitHub] spark issue #21068: [SPARK-16630][YARN] Blacklist a node if executors won't ...

2018-04-18 Thread squito
Github user squito commented on the issue: https://github.com/apache/spark/pull/21068 I think Tom makes a good case for why this should live in the YarnAllocator as you have it. I also don't think you need to worry about creating an abstract class yet, that refactoring can

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2018-04-17 Thread attilapiros
Github user attilapiros commented on the issue: https://github.com/apache/spark/pull/21068 Yes we can create an abstract class from `YarnAllocatorBlacklistTracker` (like `AbstractAllocatorBlacklistTracker`) where the method `synchronizeBlacklistedNodes` can have different

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2018-04-17 Thread squito
Github user squito commented on the issue: https://github.com/apache/spark/pull/21068 > actually the only other thing I need to make sure is there aren't any delays if we now send the information from yarn allocator back to scheduler and then I assume it would need to get it back

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2018-04-17 Thread tgravescs
Github user tgravescs commented on the issue: https://github.com/apache/spark/pull/21068 actually the only other thing I need to make sure is there aren't any delays if we now send the information from yarn allocator back to scheduler and then I assume it would need to get it back

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