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[DCOS-51636] Use spark.executor.memoryOverhead instead of spark.mesos.executor.memoryOverhead #64
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farhan5900
requested review from
akirillov,
alembiewski,
rpalaznik and
samvantran
samvantran
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Aug 29, 2019
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LGTM - let's make sure tests pass
…park into DCOS-51636-rename-executor-memoverhead-config
akirillov
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Aug 31, 2019
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Thanks, @farhan5900, LGTM.
A few questions:
- where is this change coming from? It's a good improvement but do we have any associated request or upstream Jira ticket?
- do we need to update tests in mesosphere/spark-build? I believe we don't set
memoryOverheadexplicitly but it's worth checking
Author
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There is no upstream ticket or request for this change. It was more of internal improvement suggested during implementation of I have checked all the tests in |
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Thanks, @farhan5900. The main issue with this PR is that it leads to a divergence with Apache Spark: users used to I'd suggest doing the following (given that there's no semantic difference between
Please take into account the cadence of Apache releases - the difference in this property will become available to Apache Spark users only in the next releases of 2.4 and 3.0 |
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As there exists similar property for YARN: |
farhan5900
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that referenced
this pull request
Oct 2, 2020
…in optimizations <!-- Thanks for sending a pull request! Here are some tips for you: 1. If this is your first time, please read our contributor guidelines: https://spark.apache.org/contributing.html 2. Ensure you have added or run the appropriate tests for your PR: https://spark.apache.org/developer-tools.html 3. If the PR is unfinished, add '[WIP]' in your PR title, e.g., '[WIP][SPARK-XXXX] Your PR title ...'. 4. Be sure to keep the PR description updated to reflect all changes. 5. Please write your PR title to summarize what this PR proposes. 6. If possible, provide a concise example to reproduce the issue for a faster review. --> ### What changes were proposed in this pull request? <!-- Please clarify what changes you are proposing. The purpose of this section is to outline the changes and how this PR fixes the issue. If possible, please consider writing useful notes for better and faster reviews in your PR. See the examples below. 1. If you refactor some codes with changing classes, showing the class hierarchy will help reviewers. 2. If you fix some SQL features, you can provide some references of other DBMSes. 3. If there is design documentation, please add the link. 4. If there is a discussion in the mailing list, please add the link. --> This is a followup of apache#26434 This PR use one special shuffle reader for skew join, so that we only have one join after optimization. In order to do that, this PR 1. add a very general `CustomShuffledRowRDD` which support all kind of partition arrangement. 2. move the logic of coalescing shuffle partitions to a util function, and call it during skew join optimization, to totally decouple with the `ReduceNumShufflePartitions` rule. It's too complicated to interfere skew join with `ReduceNumShufflePartitions`, as you need to consider the size of split partitions which don't respect target size already. ### Why are the changes needed? <!-- Please clarify why the changes are needed. For instance, 1. If you propose a new API, clarify the use case for a new API. 2. If you fix a bug, you can clarify why it is a bug. --> The current skew join optimization has a serious performance issue: the size of the query plan depends on the number and size of skewed partitions. ### Does this PR introduce any user-facing change? <!-- If yes, please clarify the previous behavior and the change this PR proposes - provide the console output, description and/or an example to show the behavior difference if possible. If no, write 'No'. --> no ### How was this patch tested? <!-- If tests were added, say they were added here. Please make sure to add some test cases that check the changes thoroughly including negative and positive cases if possible. If it was tested in a way different from regular unit tests, please clarify how you tested step by step, ideally copy and paste-able, so that other reviewers can test and check, and descendants can verify in the future. If tests were not added, please describe why they were not added and/or why it was difficult to add. --> existing tests test UI manually:  explain output ``` AdaptiveSparkPlan(isFinalPlan=true) +- OverwriteByExpression org.apache.spark.sql.execution.datasources.noop.NoopTable$403a2ed5, [AlwaysTrue()], org.apache.spark.sql.util.CaseInsensitiveStringMap1f +- *(5) SortMergeJoin(skew=true) [key1#2L], [key2#6L], Inner :- *(3) Sort [key1#2L ASC NULLS FIRST], false, 0 : +- SkewJoinShuffleReader 2 skewed partitions with size(max=5 KB, min=5 KB, avg=5 KB) : +- ShuffleQueryStage 0 : +- Exchange hashpartitioning(key1#2L, 200), true, [id=#53] : +- *(1) Project [(id#0L % 2) AS key1#2L] : +- *(1) Filter isnotnull((id#0L % 2)) : +- *(1) Range (0, 100000, step=1, splits=6) +- *(4) Sort [key2#6L ASC NULLS FIRST], false, 0 +- SkewJoinShuffleReader 2 skewed partitions with size(max=5 KB, min=5 KB, avg=5 KB) +- ShuffleQueryStage 1 +- Exchange hashpartitioning(key2#6L, 200), true, [id=#64] +- *(2) Project [((id#4L % 2) + 1) AS key2#6L] +- *(2) Filter isnotnull(((id#4L % 2) + 1)) +- *(2) Range (0, 100000, step=1, splits=6) ``` Closes apache#27493 from cloud-fan/aqe. Authored-by: Wenchen Fan <wenchen@databricks.com> Signed-off-by: herman <herman@databricks.com> (cherry picked from commit a4ceea6) Signed-off-by: herman <herman@databricks.com>
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It resolves DCOS-51636.
What changes were proposed in this pull request?
Changes the name of the configuration from
spark.mesos.executor.memoryOverheadtospark.executor.memoryOverheadto make it consistent withspark.driver.memoryOverhead.How was this patch tested?
It is tested by running unit test.