Last-remote11 opened a new pull request, #52388:
URL: https://github.com/apache/spark/pull/52388
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### What changes were proposed in this pull request?
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Improve test `SPARK-37753: Inhibit broadcast in left outer join when there
are many empty partitions on outer/left side` of `AdaptiveQueryExecSuite`
### Why are the changes needed?
This test appears to always succeed in the Apache GitHub Action runner
environment, But some environments, test does not seem to proceed as intended.
On my environment:
`4.18.0-553.8.1.el8_10.x86_64`
`Intel(R) Xeon(R) Silver 4210 CPU @ 2.20GHz`
`64G Mem`
And ran test in master branch following the guide of official documentation
```
./build/sbt
testOnly org.apache.spark.sql.execution.adaptive.AdaptiveQueryExecSuite
...
- SPARK-37753: Inhibit broadcast in left outer join when there are many
empty partitions on outer/left side *** FAILED ***
The code passed to eventually never returned normally. Attempted 25 times
over 15.040156205999999 seconds. Last failure message:
```
even increasing the test's timeout to 1500 seconds results to failure after
lots of retries.
```
SPARK-37753: Inhibit broadcast in left outer join when there are many empty
partitions on outer/left side *** FAILED ***
The code passed to failAfter did not complete within 20 minutes.
(AdaptiveQueryExecSuite.scala:743)
```
---
The test says
```scala
// if the right side is completed first and the left side is still being
executed,
// the right side does not know whether there are many empty partitions
on the left side,
// so there is no demote, and then the right side is broadcast in the
planning stage.
// so retry several times here to avoid unit test failure.
eventually(timeout(15.seconds), interval(500.milliseconds)) {
...
```
It seems test failure occurs with very high probability by loading the
‘right side’ completes first.
While the reason is unclear, I believe it would be better to regulate the
subquery loading speed in a predictable manner via applying simple udf rather
than retrying until both sides load in the desired order.
### Does this PR introduce _any_ user-facing change?
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No
### How was this patch tested?
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Rerun the test.
### Was this patch authored or co-authored using generative AI tooling?
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No.
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