update proportion of memory #66
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the default value of "spark.storage.memoryFraction" has been change from 0.66 to 0.6 . So it should be 60% of the memory to cache while 40% used for task execution.
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Can one of the admins verify this patch? |
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Thanks. I've merged this. |
wli600
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SKIPME merging Apache branch-1.4 bug fixes
JasonMWhite
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add spark streaming requirements to pomfile
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* revert change hosts * Update Jenkinsfile
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[SPARK-21414] Refine SlidingWindowFunctionFrame to avoid OOM Refine SlidingWindowFunctionFrame to avoid OOM resolve apache#66 See merge request !59
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Feb 22, 2018
[SPARK-22683][CORE] Allow tuning the number of dynamically allocated executors
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Signed-off-by: Rostyslav Sotnychenko <rsotnychenko@maprtech.com> (cherry picked from commit de237dc)
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[SPARK-300] fix docs for HDFS
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[SPARK-22683][CORE] Allow tuning the number of dynamically allocated executors
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UT: dims/openstack-cloud-controller-manager + devstack [in vm]
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apache#39 performance issue in fuction getAliasedConstraints of LogicalPlan
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cloud-fan
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…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:
After this pr:
Closes #31145 from wangyum/SPARK-34081.
Authored-by: Yuming Wang <yumwang@ebay.com>
Signed-off-by: Wenchen Fan <wenchen@databricks.com>
dongjoon-hyun
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Sep 12, 2024
…r `postgreSQL/float4.sql` and `postgreSQL/int8.sql` ### What changes were proposed in this pull request? This pr regenerate Java 21 golden file for `postgreSQL/float4.sql` and `postgreSQL/int8.sql` to fix Java 21 daily test. ### Why are the changes needed? Fix Java 21 daily test: - https://github.com/apache/spark/actions/runs/10823897095/job/30030200710 ``` [info] - postgreSQL/float4.sql *** FAILED *** (1 second, 100 milliseconds) [info] postgreSQL/float4.sql [info] Expected "...arameters" : { [info] "[ansiConfig" : "\"spark.sql.ansi.enabled\"", [info] "]expression" : "'N A ...", but got "...arameters" : { [info] "[]expression" : "'N A ..." Result did not match for query #11 [info] SELECT float('N A N') (SQLQueryTestSuite.scala:663) ... [info] - postgreSQL/int8.sql *** FAILED *** (2 seconds, 474 milliseconds) [info] postgreSQL/int8.sql [info] Expected "...arameters" : { [info] "[ansiConfig" : "\"spark.sql.ansi.enabled\"", [info] "]sourceType" : "\"BIG...", but got "...arameters" : { [info] "[]sourceType" : "\"BIG..." Result did not match for query #66 [info] SELECT CAST(q1 AS int) FROM int8_tbl WHERE q2 <> 456 (SQLQueryTestSuite.scala:663) ... [info] *** 2 TESTS FAILED *** [error] Failed: Total 3559, Failed 2, Errors 0, Passed 3557, Ignored 4 [error] Failed tests: [error] org.apache.spark.sql.SQLQueryTestSuite [error] (sql / Test / test) sbt.TestsFailedException: Tests unsuccessful ``` ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? - Pass Github Acitons - Manual checked: `build/sbt "sql/testOnly org.apache.spark.sql.SQLQueryTestSuite" with Java 21, all test passed ` ### Was this patch authored or co-authored using generative AI tooling? No Closes #48089 from LuciferYang/SPARK-49578-FOLLOWUP. Authored-by: yangjie01 <yangjie01@baidu.com> Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>
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The default value of "spark.storage.memoryFraction" has been changed from 0.66 to 0.6 . So it should be 60% of the memory to cache while 40% used for task execution.