Removed accidentally checked in comment #61

kayousterhout · 2014-03-03T03:35:19Z

It looks like this comment was added a while ago by @mridulm as part of a merge and was accidentally checked in. We should remove it.

mridulm · 2014-03-03T04:19:31Z

Yeah, this was an internal review comment :-)
Thanks !

AmplabJenkins · 2014-03-03T04:20:58Z

Merged build triggered.

AmplabJenkins · 2014-03-03T04:20:59Z

Merged build started.

AmplabJenkins · 2014-03-03T05:20:45Z

Merged build finished.

AmplabJenkins · 2014-03-03T05:20:46Z

All automated tests passed.
Refer to this link for build results: https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/12960/

shivaram · 2014-03-03T22:39:08Z

LGTM

rxin · 2014-03-03T22:39:53Z

I merged this. Thanks!

@mateiz

Unified daemon thread pools As requested by @mateiz in an earlier pull request, this refactors various daemon thread pools to use a set of methods in utils.scala, and also changes the thread-pool-creation methods in utils.scala to use named thread pools for improved debugging. (cherry picked from commit 983b83f) Signed-off-by: Reynold Xin <rxin@apache.org>

Don't shade the test jar in Spark Streaming

…r-fix-2 Kevincox hanging no executor fix 2

* reverted kms download * Update DockerfileDispatcher * Update Jenkinsfile

test runner

* auto calculate the initial partition number * update style * update style and add ut * use Math.ceil to handle the not divisible situation * add configuration for this feature and calculate the statistics info of needed column not the table * update the statistics of partitioned table * rename parameters * collect all the leaves node when calculate the initial partition num and some small udate * small update

We have so many scenarios about Kubernetes and OpenStack integration, An unified name format of Ansible jobs is necessary. Add empty directories for known scenario, and the ansible jobs name should follow the format. Partial-issue: theopenlab#27

…join can be planned as broadcast join ### What changes were proposed in this pull request? Should not pushdown LeftSemi/LeftAnti over Aggregate for some cases. ```scala spark.range(50000000L).selectExpr("id % 10000 as a", "id % 10000 as b").write.saveAsTable("t1") spark.range(40000000L).selectExpr("id % 8000 as c", "id % 8000 as d").write.saveAsTable("t2") spark.sql("SELECT distinct a, b FROM t1 INTERSECT SELECT distinct c, d FROM t2").explain ``` Before this pr: ``` == Physical Plan == AdaptiveSparkPlan isFinalPlan=false +- HashAggregate(keys=[a#16L, b#17L], functions=[]) +- HashAggregate(keys=[a#16L, b#17L], functions=[]) +- HashAggregate(keys=[a#16L, b#17L], functions=[]) +- Exchange hashpartitioning(a#16L, b#17L, 5), ENSURE_REQUIREMENTS, [id=#72] +- HashAggregate(keys=[a#16L, b#17L], functions=[]) +- SortMergeJoin [coalesce(a#16L, 0), isnull(a#16L), coalesce(b#17L, 0), isnull(b#17L)], [coalesce(c#18L, 0), isnull(c#18L), coalesce(d#19L, 0), isnull(d#19L)], LeftSemi :- Sort [coalesce(a#16L, 0) ASC NULLS FIRST, isnull(a#16L) ASC NULLS FIRST, coalesce(b#17L, 0) ASC NULLS FIRST, isnull(b#17L) ASC NULLS FIRST], false, 0 : +- Exchange hashpartitioning(coalesce(a#16L, 0), isnull(a#16L), coalesce(b#17L, 0), isnull(b#17L), 5), ENSURE_REQUIREMENTS, [id=#65] : +- FileScan parquet default.t1[a#16L,b#17L] Batched: true, DataFilters: [], Format: Parquet, Location: InMemoryFileIndex[file:/Users/yumwang/spark/spark-warehouse/org.apache.spark.sql.Data..., PartitionFilters: [], PushedFilters: [], ReadSchema: struct<a:bigint,b:bigint> +- Sort [coalesce(c#18L, 0) ASC NULLS FIRST, isnull(c#18L) ASC NULLS FIRST, coalesce(d#19L, 0) ASC NULLS FIRST, isnull(d#19L) ASC NULLS FIRST], false, 0 +- Exchange hashpartitioning(coalesce(c#18L, 0), isnull(c#18L), coalesce(d#19L, 0), isnull(d#19L), 5), ENSURE_REQUIREMENTS, [id=#66] +- HashAggregate(keys=[c#18L, d#19L], functions=[]) +- Exchange hashpartitioning(c#18L, d#19L, 5), ENSURE_REQUIREMENTS, [id=#61] +- HashAggregate(keys=[c#18L, d#19L], functions=[]) +- FileScan parquet default.t2[c#18L,d#19L] Batched: true, DataFilters: [], Format: Parquet, Location: InMemoryFileIndex[file:/Users/yumwang/spark/spark-warehouse/org.apache.spark.sql.Data..., PartitionFilters: [], PushedFilters: [], ReadSchema: struct<c:bigint,d:bigint> ``` After this pr: ``` == Physical Plan == AdaptiveSparkPlan isFinalPlan=false +- HashAggregate(keys=[a#16L, b#17L], functions=[]) +- Exchange hashpartitioning(a#16L, b#17L, 5), ENSURE_REQUIREMENTS, [id=#74] +- HashAggregate(keys=[a#16L, b#17L], functions=[]) +- SortMergeJoin [coalesce(a#16L, 0), isnull(a#16L), coalesce(b#17L, 0), isnull(b#17L)], [coalesce(c#18L, 0), isnull(c#18L), coalesce(d#19L, 0), isnull(d#19L)], LeftSemi :- Sort [coalesce(a#16L, 0) ASC NULLS FIRST, isnull(a#16L) ASC NULLS FIRST, coalesce(b#17L, 0) ASC NULLS FIRST, isnull(b#17L) ASC NULLS FIRST], false, 0 : +- Exchange hashpartitioning(coalesce(a#16L, 0), isnull(a#16L), coalesce(b#17L, 0), isnull(b#17L), 5), ENSURE_REQUIREMENTS, [id=#67] : +- HashAggregate(keys=[a#16L, b#17L], functions=[]) : +- Exchange hashpartitioning(a#16L, b#17L, 5), ENSURE_REQUIREMENTS, [id=#61] : +- HashAggregate(keys=[a#16L, b#17L], functions=[]) : +- FileScan parquet default.t1[a#16L,b#17L] Batched: true, DataFilters: [], Format: Parquet, Location: InMemoryFileIndex[file:/Users/yumwang/spark/spark-warehouse/org.apache.spark.sql.Data..., PartitionFilters: [], PushedFilters: [], ReadSchema: struct<a:bigint,b:bigint> +- Sort [coalesce(c#18L, 0) ASC NULLS FIRST, isnull(c#18L) ASC NULLS FIRST, coalesce(d#19L, 0) ASC NULLS FIRST, isnull(d#19L) ASC NULLS FIRST], false, 0 +- Exchange hashpartitioning(coalesce(c#18L, 0), isnull(c#18L), coalesce(d#19L, 0), isnull(d#19L), 5), ENSURE_REQUIREMENTS, [id=#68] +- HashAggregate(keys=[c#18L, d#19L], functions=[]) +- Exchange hashpartitioning(c#18L, d#19L, 5), ENSURE_REQUIREMENTS, [id=#63] +- HashAggregate(keys=[c#18L, d#19L], functions=[]) +- FileScan parquet default.t2[c#18L,d#19L] Batched: true, DataFilters: [], Format: Parquet, Location: InMemoryFileIndex[file:/Users/yumwang/spark/spark-warehouse/org.apache.spark.sql.Data..., PartitionFilters: [], PushedFilters: [], ReadSchema: struct<c:bigint,d:bigint> ``` ### Why are the changes needed? 1. Pushdown LeftSemi/LeftAnti over Aggregate will affect performance. 2. It will remove user added DISTINCT operator, e.g.: [q38](https://github.com/apache/spark/blob/master/sql/core/src/test/resources/tpcds/q38.sql), [q87](https://github.com/apache/spark/blob/master/sql/core/src/test/resources/tpcds/q87.sql). ### Does this PR introduce _any_ user-facing change? No. ### How was this patch tested? Unit test and benchmark test. SQL | Before this PR(Seconds) | After this PR(Seconds) -- | -- | -- q14a | 660 | 594 q14b | 660 | 600 q38 | 55 | 29 q87 | 66 | 35 Before this pr: ![image](https://user-images.githubusercontent.com/5399861/104452849-8789fc80-55de-11eb-88da-44059899f9a9.png) After this pr: ![image](https://user-images.githubusercontent.com/5399861/104452899-9a043600-55de-11eb-9286-d8f3a23ca3b8.png) Closes #31145 from wangyum/SPARK-34081. Authored-by: Yuming Wang <yumwang@ebay.com> Signed-off-by: Wenchen Fan <wenchen@databricks.com>

…le (#61)

…Anti over Aggregate if join can be planned as broadcast join ### What changes were proposed in this pull request? Should not pushdown LeftSemi/LeftAnti over Aggregate for some cases. ```scala spark.range(50000000L).selectExpr("id % 10000 as a", "id % 10000 as b").write.saveAsTable("t1") spark.range(40000000L).selectExpr("id % 8000 as c", "id % 8000 as d").write.saveAsTable("t2") spark.sql("SELECT distinct a, b FROM t1 INTERSECT SELECT distinct c, d FROM t2").explain ``` Before this pr: ``` == Physical Plan == AdaptiveSparkPlan isFinalPlan=false +- HashAggregate(keys=[a#16L, b#17L], functions=[]) +- HashAggregate(keys=[a#16L, b#17L], functions=[]) +- HashAggregate(keys=[a#16L, b#17L], functions=[]) +- Exchange hashpartitioning(a#16L, b#17L, 5), ENSURE_REQUIREMENTS, [id=#72] +- HashAggregate(keys=[a#16L, b#17L], functions=[]) +- SortMergeJoin [coalesce(a#16L, 0), isnull(a#16L), coalesce(b#17L, 0), isnull(b#17L)], [coalesce(c#18L, 0), isnull(c#18L), coalesce(d#19L, 0), isnull(d#19L)], LeftSemi :- Sort [coalesce(a#16L, 0) ASC NULLS FIRST, isnull(a#16L) ASC NULLS FIRST, coalesce(b#17L, 0) ASC NULLS FIRST, isnull(b#17L) ASC NULLS FIRST], false, 0 : +- Exchange hashpartitioning(coalesce(a#16L, 0), isnull(a#16L), coalesce(b#17L, 0), isnull(b#17L), 5), ENSURE_REQUIREMENTS, [id=#65] : +- FileScan parquet default.t1[a#16L,b#17L] Batched: true, DataFilters: [], Format: Parquet, Location: InMemoryFileIndex[file:/Users/yumwang/spark/spark-warehouse/org.apache.spark.sql.Data..., PartitionFilters: [], PushedFilters: [], ReadSchema: struct<a:bigint,b:bigint> +- Sort [coalesce(c#18L, 0) ASC NULLS FIRST, isnull(c#18L) ASC NULLS FIRST, coalesce(d#19L, 0) ASC NULLS FIRST, isnull(d#19L) ASC NULLS FIRST], false, 0 +- Exchange hashpartitioning(coalesce(c#18L, 0), isnull(c#18L), coalesce(d#19L, 0), isnull(d#19L), 5), ENSURE_REQUIREMENTS, [id=#66] +- HashAggregate(keys=[c#18L, d#19L], functions=[]) +- Exchange hashpartitioning(c#18L, d#19L, 5), ENSURE_REQUIREMENTS, [id=#61] +- HashAggregate(keys=[c#18L, d#19L], functions=[]) +- FileScan parquet default.t2[c#18L,d#19L] Batched: true, DataFilters: [], Format: Parquet, Location: InMemoryFileIndex[file:/Users/yumwang/spark/spark-warehouse/org.apache.spark.sql.Data..., PartitionFilters: [], PushedFilters: [], ReadSchema: struct<c:bigint,d:bigint> ``` After this pr: ``` == Physical Plan == AdaptiveSparkPlan isFinalPlan=false +- HashAggregate(keys=[a#16L, b#17L], functions=[]) +- Exchange hashpartitioning(a#16L, b#17L, 5), ENSURE_REQUIREMENTS, [id=#74] +- HashAggregate(keys=[a#16L, b#17L], functions=[]) +- SortMergeJoin [coalesce(a#16L, 0), isnull(a#16L), coalesce(b#17L, 0), isnull(b#17L)], [coalesce(c#18L, 0), isnull(c#18L), coalesce(d#19L, 0), isnull(d#19L)], LeftSemi :- Sort [coalesce(a#16L, 0) ASC NULLS FIRST, isnull(a#16L) ASC NULLS FIRST, coalesce(b#17L, 0) ASC NULLS FIRST, isnull(b#17L) ASC NULLS FIRST], false, 0 : +- Exchange hashpartitioning(coalesce(a#16L, 0), isnull(a#16L), coalesce(b#17L, 0), isnull(b#17L), 5), ENSURE_REQUIREMENTS, [id=#67] : +- HashAggregate(keys=[a#16L, b#17L], functions=[]) : +- Exchange hashpartitioning(a#16L, b#17L, 5), ENSURE_REQUIREMENTS, [id=#61] : +- HashAggregate(keys=[a#16L, b#17L], functions=[]) : +- FileScan parquet default.t1[a#16L,b#17L] Batched: true, DataFilters: [], Format: Parquet, Location: InMemoryFileIndex[file:/Users/yumwang/spark/spark-warehouse/org.apache.spark.sql.Data..., PartitionFilters: [], PushedFilters: [], ReadSchema: struct<a:bigint,b:bigint> +- Sort [coalesce(c#18L, 0) ASC NULLS FIRST, isnull(c#18L) ASC NULLS FIRST, coalesce(d#19L, 0) ASC NULLS FIRST, isnull(d#19L) ASC NULLS FIRST], false, 0 +- Exchange hashpartitioning(coalesce(c#18L, 0), isnull(c#18L), coalesce(d#19L, 0), isnull(d#19L), 5), ENSURE_REQUIREMENTS, [id=#68] +- HashAggregate(keys=[c#18L, d#19L], functions=[]) +- Exchange hashpartitioning(c#18L, d#19L, 5), ENSURE_REQUIREMENTS, [id=#63] +- HashAggregate(keys=[c#18L, d#19L], functions=[]) +- FileScan parquet default.t2[c#18L,d#19L] Batched: true, DataFilters: [], Format: Parquet, Location: InMemoryFileIndex[file:/Users/yumwang/spark/spark-warehouse/org.apache.spark.sql.Data..., PartitionFilters: [], PushedFilters: [], ReadSchema: struct<c:bigint,d:bigint> ``` ### Why are the changes needed? 1. Pushdown LeftSemi/LeftAnti over Aggregate will affect performance. 2. It will remove user added DISTINCT operator, e.g.: [q38](https://github.com/apache/spark/blob/master/sql/core/src/test/resources/tpcds/q38.sql), [q87](https://github.com/apache/spark/blob/master/sql/core/src/test/resources/tpcds/q87.sql). ### Does this PR introduce _any_ user-facing change? No. ### How was this patch tested? Unit test and benchmark test. SQL | Before this PR(Seconds) | After this PR(Seconds) -- | -- | -- q14a | 660 | 594 q14b | 660 | 600 q38 | 55 | 29 q87 | 66 | 35 Before this pr: ![image](https://user-images.githubusercontent.com/5399861/104452849-8789fc80-55de-11eb-88da-44059899f9a9.png) After this pr: ![image](https://user-images.githubusercontent.com/5399861/104452899-9a043600-55de-11eb-9286-d8f3a23ca3b8.png) Closes #31145 from wangyum/SPARK-34081. Authored-by: Yuming Wang <yumwang@ebay.com> Signed-off-by: Wenchen Fan <wenchen@databricks.com> (cherry picked from commit d3ea308)

…ead pool ### What changes were proposed in this pull request? This PR aims to use a meaningful class name prefix for REST Submission API thread pool instead of the default value of Jetty QueuedThreadPool, `"qtp"+super.hashCode()`. https://github.com/dekellum/jetty/blob/3dc0120d573816de7d6a83e2d6a97035288bdd4a/jetty-util/src/main/java/org/eclipse/jetty/util/thread/QueuedThreadPool.java#L64 ### Why are the changes needed? This is helpful during JVM investigation. **BEFORE (4.0.0-preview2)** ``` $ SPARK_MASTER_OPTS='-Dspark.master.rest.enabled=true' sbin/start-master.sh $ jstack 28217 | grep qtp "qtp1925630411-52" #52 daemon prio=5 os_prio=31 cpu=0.07ms elapsed=19.06s tid=0x0000000134906c10 nid=0xde03 runnable [0x0000000314592000] "qtp1925630411-53" #53 daemon prio=5 os_prio=31 cpu=0.05ms elapsed=19.06s tid=0x0000000134ac6810 nid=0xc603 runnable [0x000000031479e000] "qtp1925630411-54" #54 daemon prio=5 os_prio=31 cpu=0.06ms elapsed=19.06s tid=0x000000013491ae10 nid=0xdc03 runnable [0x00000003149aa000] "qtp1925630411-55" #55 daemon prio=5 os_prio=31 cpu=0.08ms elapsed=19.06s tid=0x0000000134ac9810 nid=0xc803 runnable [0x0000000314bb6000] "qtp1925630411-56" #56 daemon prio=5 os_prio=31 cpu=0.04ms elapsed=19.06s tid=0x0000000134ac9e10 nid=0xda03 runnable [0x0000000314dc2000] "qtp1925630411-57" #57 daemon prio=5 os_prio=31 cpu=0.05ms elapsed=19.06s tid=0x0000000134aca410 nid=0xca03 runnable [0x0000000314fce000] "qtp1925630411-58" #58 daemon prio=5 os_prio=31 cpu=0.04ms elapsed=19.06s tid=0x0000000134acaa10 nid=0xcb03 runnable [0x00000003151da000] "qtp1925630411-59" #59 daemon prio=5 os_prio=31 cpu=0.06ms elapsed=19.06s tid=0x0000000134acb010 nid=0xcc03 runnable [0x00000003153e6000] "qtp1925630411-60-acceptor-0108e9815-ServerConnector1e497474{HTTP/1.1, (http/1.1)}{M3-Max.local:6066}" #60 daemon prio=3 os_prio=31 cpu=0.11ms elapsed=19.06s tid=0x00000001317ffa10 nid=0xcd03 runnable [0x00000003155f2000] "qtp1925630411-61-acceptor-11d90f2aa-ServerConnector1e497474{HTTP/1.1, (http/1.1)}{M3-Max.local:6066}" #61 daemon prio=3 os_prio=31 cpu=0.10ms elapsed=19.06s tid=0x00000001314ed610 nid=0xcf03 waiting on condition [0x00000003157fe000] ``` **AFTER** ``` $ SPARK_MASTER_OPTS='-Dspark.master.rest.enabled=true' sbin/start-master.sh $ jstack 28317 | grep StandaloneRestServer "StandaloneRestServer-52" #52 daemon prio=5 os_prio=31 cpu=0.09ms elapsed=60.06s tid=0x00000001284a8e10 nid=0xdb03 runnable [0x000000032cfce000] "StandaloneRestServer-53" #53 daemon prio=5 os_prio=31 cpu=0.06ms elapsed=60.06s tid=0x00000001284acc10 nid=0xda03 runnable [0x000000032d1da000] "StandaloneRestServer-54" #54 daemon prio=5 os_prio=31 cpu=0.05ms elapsed=60.06s tid=0x00000001284ae610 nid=0xd803 runnable [0x000000032d3e6000] "StandaloneRestServer-55" #55 daemon prio=5 os_prio=31 cpu=0.09ms elapsed=60.06s tid=0x00000001284aec10 nid=0xd703 runnable [0x000000032d5f2000] "StandaloneRestServer-56" #56 daemon prio=5 os_prio=31 cpu=0.06ms elapsed=60.06s tid=0x00000001284af210 nid=0xc803 runnable [0x000000032d7fe000] "StandaloneRestServer-57" #57 daemon prio=5 os_prio=31 cpu=0.05ms elapsed=60.06s tid=0x00000001284af810 nid=0xc903 runnable [0x000000032da0a000] "StandaloneRestServer-58" #58 daemon prio=5 os_prio=31 cpu=0.06ms elapsed=60.06s tid=0x00000001284afe10 nid=0xcb03 runnable [0x000000032dc16000] "StandaloneRestServer-59" #59 daemon prio=5 os_prio=31 cpu=0.05ms elapsed=60.06s tid=0x00000001284b0410 nid=0xcc03 runnable [0x000000032de22000] "StandaloneRestServer-60-acceptor-04aefbaa8-ServerConnector44284d85{HTTP/1.1, (http/1.1)}{M3-Max.local:6066}" #60 daemon prio=3 os_prio=31 cpu=0.13ms elapsed=60.05s tid=0x000000015cda1a10 nid=0xcd03 runnable [0x000000032e02e000] "StandaloneRestServer-61-acceptor-148976251-ServerConnector44284d85{HTTP/1.1, (http/1.1)}{M3-Max.local:6066}" #61 daemon prio=3 os_prio=31 cpu=0.12ms elapsed=60.05s tid=0x000000015cd1c810 nid=0xce03 waiting on condition [0x000000032e23a000] ``` ### Does this PR introduce _any_ user-facing change? No, the thread names are accessed during the debugging. ### How was this patch tested? Manual review. ### Was this patch authored or co-authored using generative AI tooling? No. Closes #48924 from dongjoon-hyun/SPARK-50385. Authored-by: Dongjoon Hyun <dongjoon@apache.org> Signed-off-by: panbingkun <panbingkun@apache.org>

…rade ORC to 1.6.11"" (apache#61) This reverts commit aa80c27.

Removed accidentally checked in comment

0b2b3f2

asfgit closed this in 369aad6 Mar 3, 2014

wli600 pushed a commit to wli600/spark that referenced this pull request Jul 29, 2015

Merge pull request apache#61 from mbautin/csd-1.4_dont_shade_test_jar

cfc79a7

Don't shade the test jar in Spark Streaming

JasonMWhite pushed a commit to JasonMWhite/spark that referenced this pull request Dec 2, 2015

Merge pull request apache#61 from Shopify/kevincox-hanging-no-executo…

f80a269

…r-fix-2 Kevincox hanging no executor fix 2

jlopezmalla pushed a commit to jlopezmalla/spark that referenced this pull request Sep 18, 2017

reverted kms download (apache#61)

ea56e7d

* reverted kms download * Update DockerfileDispatcher * Update Jenkinsfile

Igosuki pushed a commit to Adikteev/spark that referenced this pull request Jul 31, 2018

Merge pull request apache#61 from mesosphere/migrate-test-runner

a0e2126

test runner

luzhonghao pushed a commit to luzhonghao/spark that referenced this pull request Dec 11, 2018

auto calculate the initial partition number with ae (apache#61)

84394e8

luzhonghao pushed a commit to luzhonghao/spark that referenced this pull request Dec 11, 2018

auto calculate the initial partition number with ae (apache#61)

7f83c9c

XinDongSh pushed a commit to XinDongSh/spark that referenced this pull request Jan 20, 2021

Plasma Block Object Writer implementation (apache#61)

7df2c46

wangyum pushed a commit that referenced this pull request May 26, 2023

[CARMEL-3535] Create temporary table like and analyze a temporary tab…

7c460f1

…le (#61)

panbingkun mentioned this pull request Jun 2, 2023

[SPARK-43945][SQL][TESTS] Fix bug for SQLQueryTestSuite when run on local env #41431

Closed

peter-toth pushed a commit to peter-toth/spark that referenced this pull request Nov 26, 2024

CDPD-71817. Revert "CDPD-56374. Revert "[SPARK-36732][SQL][BUILD] Upg…

2206687

…rade ORC to 1.6.11"" (apache#61) This reverts commit aa80c27.

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Removed accidentally checked in comment #61

Removed accidentally checked in comment #61

kayousterhout commented Mar 3, 2014

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rxin commented Mar 3, 2014

Removed accidentally checked in comment #61

Removed accidentally checked in comment #61

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