c21 opened a new pull request #34581:
URL: https://github.com/apache/spark/pull/34581
<!--
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.
7. If you want to add a new configuration, please read the guideline first
for naming configurations in
'core/src/main/scala/org/apache/spark/internal/config/ConfigEntry.scala'.
8. If you want to add or modify an error type or message, please read the
guideline first in
'core/src/main/resources/error/README.md'.
-->
### 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 PR is to add code-gen for FULL OUTER sort merge join. The change is in
`SortMergeJoinExec.scala:codegenFullOuter()`. Followed the same algorithm in
iterator mode - `SortMergeFullOuterJoinScanner`: maintain buffer for join left
and right sides, and iterate over matched rows in buffers.
Example query:
```
val df1 = spark.range(5).select($"id".as("k1"))
val df2 = spark.range(10).select($"id".as("k2"))
df1.join(df2.hint(hint), $"k1" === $"k2" % 3 && $"k1" + 3 =!= $"k2",
"full_outer")
```
Example generated code:
https://gist.github.com/c21/5cab9751f24ae448d77a259d28cb77d7
### 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.
-->
Improve the run-time/CPU performance of FULL OUTER sort merge join.
Micro benchmark (same query in `JoinBenchmark.scala`):
```
def sortMergeJoin(): Unit = {
val N = 2 << 20
codegenBenchmark("sort merge join", N) {
val df1 = spark.range(N).selectExpr(s"id * 2 as k1")
val df2 = spark.range(N).selectExpr(s"id * 3 as k2")
val df = df1.join(df2, col("k1") === col("k2"), "full_outer")
assert(df.queryExecution.sparkPlan.find(_.isInstanceOf[SortMergeJoinExec]).isDefined)
df.noop()
}
}
def sortMergeJoinWithDuplicates(): Unit = {
val N = 2 << 20
codegenBenchmark("sort merge join with duplicates", N) {
val df1 = spark.range(N)
.selectExpr(s"(id * 15485863) % ${N*10} as k1")
val df2 = spark.range(N)
.selectExpr(s"(id * 15485867) % ${N*10} as k2")
val df = df1.join(df2, col("k1") === col("k2"), "full_outer")
assert(df.queryExecution.sparkPlan.find(_.isInstanceOf[SortMergeJoinExec]).isDefined)
df.noop()
}
}
```
Seeing 20-30% of run-time improvement:
```
Running benchmark: sort merge join
Running case: sort merge join wholestage off
Stopped after 2 iterations, 2979 ms
Running case: sort merge join wholestage on
Stopped after 5 iterations, 5849 ms
Java HotSpot(TM) 64-Bit Server VM 1.8.0_181-b13 on Mac OS X 10.16
Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
sort merge join: Best Time(ms) Avg Time(ms)
Stdev(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------------------------------
sort merge join wholestage off 1453 1490
52 1.4 693.0 1.0X
sort merge join wholestage on 1115 1170
43 1.9 531.6 1.3X
Running benchmark: sort merge join with duplicates
Running case: sort merge join with duplicates wholestage off
Stopped after 2 iterations, 3236 ms
Running case: sort merge join with duplicates wholestage on
Stopped after 5 iterations, 6768 ms
Java HotSpot(TM) 64-Bit Server VM 1.8.0_181-b13 on Mac OS X 10.16
Intel(R) Core(TM) i9-9980HK CPU @ 2.40GHz
sort merge join with duplicates: Best Time(ms) Avg Time(ms)
Stdev(ms) Rate(M/s) Per Row(ns) Relative
------------------------------------------------------------------------------------------------------------------------------
sort merge join with duplicates wholestage off 1609 1618
13 1.3 767.2 1.0X
sort merge join with duplicates wholestage on 1330 1354
24 1.6 634.4 1.2X
```
### Does this PR introduce _any_ user-facing change?
<!--
Note that it means *any* user-facing change including all aspects such as
the documentation fix.
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 possible, please also clarify if this is a user-facing change compared to
the released Spark versions or within the unreleased branches such as master.
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.
If benchmark tests were added, please run the benchmarks in GitHub Actions
for the consistent environment, and the instructions could accord to:
https://spark.apache.org/developer-tools.html#github-workflow-benchmarks.
-->
* Added unit test in `WholeStageCodegenSuite.scala`.
* Existing unit test in `OuterJoinSuite.scala`.
--
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
To unsubscribe, e-mail: [email protected]
For queries about this service, please contact Infrastructure at:
[email protected]
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
