-
Notifications
You must be signed in to change notification settings - Fork 28.5k
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
[SPARK-2030] Bump SparkBuild.scala version number of branch-1.0 to 1.0.1-SNAPSHOT. #975
Closed
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Merged build triggered. |
Merged build started. |
Merged build finished. All automated tests passed. |
All automated tests passed. |
asfgit
pushed a commit
that referenced
this pull request
Jun 5, 2014
…0.1-SNAPSHOT. Author: Takuya UESHIN <[email protected]> Closes #975 from ueshin/issues/SPARK-2030 and squashes the following commits: aae1044 [Takuya UESHIN] Bump version number to 1.0.1-SNAPSHOT.
LGTM - thanks |
@ueshin mind closing this? Our "auto close" feature doesn't work for things merged into non-master branches. |
Thanks! |
cloud-fan
pushed a commit
that referenced
this pull request
Jun 21, 2021
…subquery reuse ### What changes were proposed in this pull request? This PR: 1. Fixes an issue in `ReuseExchange` rule that can result a `ReusedExchange` node pointing to an invalid exchange. This can happen due to the 2 separate traversals in `ReuseExchange` when the 2nd traversal modifies an exchange that has already been referenced (reused) in the 1st traversal. Consider the following query: ``` WITH t AS ( SELECT df1.id, df2.k FROM df1 JOIN df2 ON df1.k = df2.k WHERE df2.id < 2 ) SELECT * FROM t AS a JOIN t AS b ON a.id = b.id ``` Before this PR the plan of the query was (note the `<== this reuse node points to a non-existing node` marker): ``` == Physical Plan == *(7) SortMergeJoin [id#14L], [id#18L], Inner :- *(3) Sort [id#14L ASC NULLS FIRST], false, 0 : +- Exchange hashpartitioning(id#14L, 5), true, [id=#298] : +- *(2) Project [id#14L, k#17L] : +- *(2) BroadcastHashJoin [k#15L], [k#17L], Inner, BuildRight : :- *(2) Project [id#14L, k#15L] : : +- *(2) Filter isnotnull(id#14L) : : +- *(2) ColumnarToRow : : +- FileScan parquet default.df1[id#14L,k#15L] Batched: true, DataFilters: [isnotnull(id#14L)], Format: Parquet, Location: InMemoryFileIndex[file:/Users/petertoth/git/apache/spark/sql/core/spark-warehouse/org.apache.spar..., PartitionFilters: [isnotnull(k#15L), dynamicpruningexpression(k#15L IN dynamicpruning#26)], PushedFilters: [IsNotNull(id)], ReadSchema: struct<id:bigint> : : +- SubqueryBroadcast dynamicpruning#26, 0, [k#17L], [id=#289] : : +- ReusedExchange [k#17L], BroadcastExchange HashedRelationBroadcastMode(List(input[0, bigint, true])), [id=#179] : +- BroadcastExchange HashedRelationBroadcastMode(List(input[0, bigint, true])), [id=#179] : +- *(1) Project [k#17L] : +- *(1) Filter ((isnotnull(id#16L) AND (id#16L < 2)) AND isnotnull(k#17L)) : +- *(1) ColumnarToRow : +- FileScan parquet default.df2[id#16L,k#17L] Batched: true, DataFilters: [isnotnull(id#16L), (id#16L < 2), isnotnull(k#17L)], Format: Parquet, Location: InMemoryFileIndex[file:/Users/petertoth/git/apache/spark/sql/core/spark-warehouse/org.apache.spar..., PartitionFilters: [], PushedFilters: [IsNotNull(id), LessThan(id,2), IsNotNull(k)], ReadSchema: struct<id:bigint,k:bigint> +- *(6) Sort [id#18L ASC NULLS FIRST], false, 0 +- ReusedExchange [id#18L, k#21L], Exchange hashpartitioning(id#14L, 5), true, [id=#184] <== this reuse node points to a non-existing node ``` After this PR: ``` == Physical Plan == *(7) SortMergeJoin [id#14L], [id#18L], Inner :- *(3) Sort [id#14L ASC NULLS FIRST], false, 0 : +- Exchange hashpartitioning(id#14L, 5), true, [id=#231] : +- *(2) Project [id#14L, k#17L] : +- *(2) BroadcastHashJoin [k#15L], [k#17L], Inner, BuildRight : :- *(2) Project [id#14L, k#15L] : : +- *(2) Filter isnotnull(id#14L) : : +- *(2) ColumnarToRow : : +- FileScan parquet default.df1[id#14L,k#15L] Batched: true, DataFilters: [isnotnull(id#14L)], Format: Parquet, Location: InMemoryFileIndex[file:/Users/petertoth/git/apache/spark/sql/core/spark-warehouse/org.apache.spar..., PartitionFilters: [isnotnull(k#15L), dynamicpruningexpression(k#15L IN dynamicpruning#26)], PushedFilters: [IsNotNull(id)], ReadSchema: struct<id:bigint> : : +- SubqueryBroadcast dynamicpruning#26, 0, [k#17L], [id=#103] : : +- BroadcastExchange HashedRelationBroadcastMode(List(input[0, bigint, true])), [id=#102] : : +- *(1) Project [k#17L] : : +- *(1) Filter ((isnotnull(id#16L) AND (id#16L < 2)) AND isnotnull(k#17L)) : : +- *(1) ColumnarToRow : : +- FileScan parquet default.df2[id#16L,k#17L] Batched: true, DataFilters: [isnotnull(id#16L), (id#16L < 2), isnotnull(k#17L)], Format: Parquet, Location: InMemoryFileIndex[file:/Users/petertoth/git/apache/spark/sql/core/spark-warehouse/org.apache.spar..., PartitionFilters: [], PushedFilters: [IsNotNull(id), LessThan(id,2), IsNotNull(k)], ReadSchema: struct<id:bigint,k:bigint> : +- ReusedExchange [k#17L], BroadcastExchange HashedRelationBroadcastMode(List(input[0, bigint, true])), [id=#102] +- *(6) Sort [id#18L ASC NULLS FIRST], false, 0 +- ReusedExchange [id#18L, k#21L], Exchange hashpartitioning(id#14L, 5), true, [id=#231] ``` 2. Fixes an issue with separate consecutive `ReuseExchange` and `ReuseSubquery` rules that can result a `ReusedExchange` node pointing to an invalid exchange. This can happen due to the 2 separate rules when `ReuseSubquery` rule modifies an exchange that has already been referenced (reused) in `ReuseExchange` rule. Consider the following query: ``` WITH t AS ( SELECT df1.id, df2.k FROM df1 JOIN df2 ON df1.k = df2.k WHERE df2.id < 2 ), t2 AS ( SELECT * FROM t UNION SELECT * FROM t ) SELECT * FROM t2 AS a JOIN t2 AS b ON a.id = b.id ``` Before this PR the plan of the query was (note the `<== this reuse node points to a non-existing node` marker): ``` == Physical Plan == *(15) SortMergeJoin [id#46L], [id#58L], Inner :- *(7) Sort [id#46L ASC NULLS FIRST], false, 0 : +- Exchange hashpartitioning(id#46L, 5), true, [id=#979] : +- *(6) HashAggregate(keys=[id#46L, k#49L], functions=[]) : +- Exchange hashpartitioning(id#46L, k#49L, 5), true, [id=#975] : +- *(5) HashAggregate(keys=[id#46L, k#49L], functions=[]) : +- Union : :- *(2) Project [id#46L, k#49L] : : +- *(2) BroadcastHashJoin [k#47L], [k#49L], Inner, BuildRight : : :- *(2) Project [id#46L, k#47L] : : : +- *(2) Filter isnotnull(id#46L) : : : +- *(2) ColumnarToRow : : : +- FileScan parquet default.df1[id#46L,k#47L] Batched: true, DataFilters: [isnotnull(id#46L)], Format: Parquet, Location: InMemoryFileIndex[file:/Users/petertoth/git/apache/spark/sql/core/spark-warehouse/org.apache.spar..., PartitionFilters: [isnotnull(k#47L), dynamicpruningexpression(k#47L IN dynamicpruning#66)], PushedFilters: [IsNotNull(id)], ReadSchema: struct<id:bigint> : : : +- SubqueryBroadcast dynamicpruning#66, 0, [k#49L], [id=#926] : : : +- ReusedExchange [k#49L], BroadcastExchange HashedRelationBroadcastMode(List(input[0, bigint, true])), [id=#656] : : +- BroadcastExchange HashedRelationBroadcastMode(List(input[0, bigint, true])), [id=#656] : : +- *(1) Project [k#49L] : : +- *(1) Filter ((isnotnull(id#48L) AND (id#48L < 2)) AND isnotnull(k#49L)) : : +- *(1) ColumnarToRow : : +- FileScan parquet default.df2[id#48L,k#49L] Batched: true, DataFilters: [isnotnull(id#48L), (id#48L < 2), isnotnull(k#49L)], Format: Parquet, Location: InMemoryFileIndex[file:/Users/petertoth/git/apache/spark/sql/core/spark-warehouse/org.apache.spar..., PartitionFilters: [], PushedFilters: [IsNotNull(id), LessThan(id,2), IsNotNull(k)], ReadSchema: struct<id:bigint,k:bigint> : +- *(4) Project [id#46L, k#49L] : +- *(4) BroadcastHashJoin [k#47L], [k#49L], Inner, BuildRight : :- *(4) Project [id#46L, k#47L] : : +- *(4) Filter isnotnull(id#46L) : : +- *(4) ColumnarToRow : : +- FileScan parquet default.df1[id#46L,k#47L] Batched: true, DataFilters: [isnotnull(id#46L)], Format: Parquet, Location: InMemoryFileIndex[file:/Users/petertoth/git/apache/spark/sql/core/spark-warehouse/org.apache.spar..., PartitionFilters: [isnotnull(k#47L), dynamicpruningexpression(k#47L IN dynamicpruning#66)], PushedFilters: [IsNotNull(id)], ReadSchema: struct<id:bigint> : : +- ReusedSubquery SubqueryBroadcast dynamicpruning#66, 0, [k#49L], [id=#926] : +- ReusedExchange [k#49L], BroadcastExchange HashedRelationBroadcastMode(List(input[0, bigint, true])), [id=#656] +- *(14) Sort [id#58L ASC NULLS FIRST], false, 0 +- ReusedExchange [id#58L, k#61L], Exchange hashpartitioning(id#46L, 5), true, [id=#761] <== this reuse node points to a non-existing node ``` After this PR: ``` == Physical Plan == *(15) SortMergeJoin [id#46L], [id#58L], Inner :- *(7) Sort [id#46L ASC NULLS FIRST], false, 0 : +- Exchange hashpartitioning(id#46L, 5), true, [id=#793] : +- *(6) HashAggregate(keys=[id#46L, k#49L], functions=[]) : +- Exchange hashpartitioning(id#46L, k#49L, 5), true, [id=#789] : +- *(5) HashAggregate(keys=[id#46L, k#49L], functions=[]) : +- Union : :- *(2) Project [id#46L, k#49L] : : +- *(2) BroadcastHashJoin [k#47L], [k#49L], Inner, BuildRight : : :- *(2) Project [id#46L, k#47L] : : : +- *(2) Filter isnotnull(id#46L) : : : +- *(2) ColumnarToRow : : : +- FileScan parquet default.df1[id#46L,k#47L] Batched: true, DataFilters: [isnotnull(id#46L)], Format: Parquet, Location: InMemoryFileIndex[file:/Users/petertoth/git/apache/spark/sql/core/spark-warehouse/org.apache.spar..., PartitionFilters: [isnotnull(k#47L), dynamicpruningexpression(k#47L IN dynamicpruning#66)], PushedFilters: [IsNotNull(id)], ReadSchema: struct<id:bigint> : : : +- SubqueryBroadcast dynamicpruning#66, 0, [k#49L], [id=#485] : : : +- BroadcastExchange HashedRelationBroadcastMode(List(input[0, bigint, true])), [id=#484] : : : +- *(1) Project [k#49L] : : : +- *(1) Filter ((isnotnull(id#48L) AND (id#48L < 2)) AND isnotnull(k#49L)) : : : +- *(1) ColumnarToRow : : : +- FileScan parquet default.df2[id#48L,k#49L] Batched: true, DataFilters: [isnotnull(id#48L), (id#48L < 2), isnotnull(k#49L)], Format: Parquet, Location: InMemoryFileIndex[file:/Users/petertoth/git/apache/spark/sql/core/spark-warehouse/org.apache.spar..., PartitionFilters: [], PushedFilters: [IsNotNull(id), LessThan(id,2), IsNotNull(k)], ReadSchema: struct<id:bigint,k:bigint> : : +- ReusedExchange [k#49L], BroadcastExchange HashedRelationBroadcastMode(List(input[0, bigint, true])), [id=#484] : +- *(4) Project [id#46L, k#49L] : +- *(4) BroadcastHashJoin [k#47L], [k#49L], Inner, BuildRight : :- *(4) Project [id#46L, k#47L] : : +- *(4) Filter isnotnull(id#46L) : : +- *(4) ColumnarToRow : : +- FileScan parquet default.df1[id#46L,k#47L] Batched: true, DataFilters: [isnotnull(id#46L)], Format: Parquet, Location: InMemoryFileIndex[file:/Users/petertoth/git/apache/spark/sql/core/spark-warehouse/org.apache.spar..., PartitionFilters: [isnotnull(k#47L), dynamicpruningexpression(k#47L IN dynamicpruning#66)], PushedFilters: [IsNotNull(id)], ReadSchema: struct<id:bigint> : : +- ReusedSubquery SubqueryBroadcast dynamicpruning#66, 0, [k#49L], [id=#485] : +- ReusedExchange [k#49L], BroadcastExchange HashedRelationBroadcastMode(List(input[0, bigint, true])), [id=#484] +- *(14) Sort [id#58L ASC NULLS FIRST], false, 0 +- ReusedExchange [id#58L, k#61L], Exchange hashpartitioning(id#46L, 5), true, [id=#793] ``` (This example contains issue 1 as well.) 3. Improves the reuse of exchanges and subqueries by enabling reuse across the whole plan. This means that the new combined rule utilizes the reuse opportunities between parent and subqueries by traversing the whole plan. The traversal is started on the top level query only. 4. Due to the order of traversal this PR does while adding reuse nodes, the reuse nodes appear in parent queries if reuse is possible between different levels of queries (typical for DPP). This is not an issue from execution perspective, but this also means "forward references" in explain formatted output where parent queries come first. The changes I made to `ExplainUtils` are to handle these references properly. This PR fixes the above 3 issues by unifying the separate rules into a `ReuseExchangeAndSubquery` rule that does a 1 pass, whole-plan, bottom-up traversal. ### Why are the changes needed? Performance improvement. ### How was this patch tested? - New UTs in `ReuseExchangeAndSubquerySuite` to cover 1. and 2. - New UTs in `DynamicPartitionPruningSuite`, `SubquerySuite` and `ExchangeSuite` to cover 3. - New `ReuseMapSuite` to test `ReuseMap`. - Checked new golden files of `PlanStabilitySuite`s for invalid reuse references. - TPCDS benchmarks. Closes #28885 from peter-toth/SPARK-29375-SPARK-28940-whole-plan-reuse. Authored-by: Peter Toth <[email protected]> Signed-off-by: Wenchen Fan <[email protected]>
wangyum
pushed a commit
that referenced
this pull request
May 26, 2023
…namically (#975) * [CARMEL-5997] Support more sql patterns for deciding bucketed scan dynamically * Fix ut
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
No description provided.