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Posted to reviews@spark.apache.org by "itholic (via GitHub)" <gi...@apache.org> on 2023/09/16 09:07:55 UTC
[GitHub] [spark] itholic opened a new pull request, #42955: [SPARK-43628][SPARK-43629][CONNECT][PS][TESTS] Clear message for JVM dependent tests.
itholic opened a new pull request, #42955:
URL: https://github.com/apache/spark/pull/42955
### What changes were proposed in this pull request?
This PR proposes to correct the message for JVM only tests from Spark Connect, and enable the tests when possible to workaround without JVM features.
### 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.
-->
Among JVM-dependent tests, there are tests that can be replaced without using JVM features, while there are some edge tests that can only be tested using JVM features. We need to be clearer about why these cannot be tested.
### Does this PR introduce _any_ user-facing change?
<!--
Note that it means *any* user-facing change including all aspects such as the documentation fix.
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If no, write 'No'.
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No. it's test-only
### How was this patch tested?
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Updated the existing tests.
### Was this patch authored or co-authored using generative AI tooling?
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No.
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[GitHub] [spark] itholic commented on a diff in pull request #42955: [SPARK-43628][SPARK-43629][CONNECT][PS][TESTS] Clear message for JVM dependent tests.
Posted by "itholic (via GitHub)" <gi...@apache.org>.
itholic commented on code in PR #42955:
URL: https://github.com/apache/spark/pull/42955#discussion_r1328183416
##########
python/pyspark/pandas/tests/computation/test_compute.py:
##########
@@ -101,16 +101,10 @@ def test_mode(self):
with self.assertRaises(ValueError):
psdf.mode(axis=2)
- def f(index, iterator):
- return ["3", "3", "3", "3", "4"] if index == 3 else ["0", "1", "2", "3", "4"]
-
- rdd = self.spark.sparkContext.parallelize(
- [
- 1,
- ],
- 4,
- ).mapPartitionsWithIndex(f)
- df = self.spark.createDataFrame(rdd, schema="string")
+ data = [(i,) for i in ["3", "3", "3", "3", "4"]] + [
+ (i,) for i in ["0", "1", "2", "3", "4"]
+ ] * 3
+ df = self.spark.createDataFrame(data)
Review Comment:
I see. Then just let me revert this changes.
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[GitHub] [spark] dongjoon-hyun commented on pull request #42955: [SPARK-43628][SPARK-43629][CONNECT][PS][TESTS] Clear message for JVM dependent tests.
Posted by "dongjoon-hyun (via GitHub)" <gi...@apache.org>.
dongjoon-hyun commented on PR #42955:
URL: https://github.com/apache/spark/pull/42955#issuecomment-1723812163
Merged to master for Apache Spark 4.0.0.
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[GitHub] [spark] zhengruifeng commented on a diff in pull request #42955: [SPARK-43628][SPARK-43629][CONNECT][PS][TESTS] Clear message for JVM dependent tests.
Posted by "zhengruifeng (via GitHub)" <gi...@apache.org>.
zhengruifeng commented on code in PR #42955:
URL: https://github.com/apache/spark/pull/42955#discussion_r1328181845
##########
python/pyspark/pandas/tests/computation/test_compute.py:
##########
@@ -101,16 +101,10 @@ def test_mode(self):
with self.assertRaises(ValueError):
psdf.mode(axis=2)
- def f(index, iterator):
- return ["3", "3", "3", "3", "4"] if index == 3 else ["0", "1", "2", "3", "4"]
-
- rdd = self.spark.sparkContext.parallelize(
- [
- 1,
- ],
- 4,
- ).mapPartitionsWithIndex(f)
- df = self.spark.createDataFrame(rdd, schema="string")
+ data = [(i,) for i in ["3", "3", "3", "3", "4"]] + [
+ (i,) for i in ["0", "1", "2", "3", "4"]
+ ] * 3
+ df = self.spark.createDataFrame(data)
Review Comment:
I don't think the new test can generate the expected partitioning
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[GitHub] [spark] dongjoon-hyun closed pull request #42955: [SPARK-43628][SPARK-43629][CONNECT][PS][TESTS] Clear message for JVM dependent tests.
Posted by "dongjoon-hyun (via GitHub)" <gi...@apache.org>.
dongjoon-hyun closed pull request #42955: [SPARK-43628][SPARK-43629][CONNECT][PS][TESTS] Clear message for JVM dependent tests.
URL: https://github.com/apache/spark/pull/42955
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[GitHub] [spark] itholic commented on a diff in pull request #42955: [SPARK-43628][SPARK-43629][CONNECT][PS][TESTS] Clear message for JVM dependent tests.
Posted by "itholic (via GitHub)" <gi...@apache.org>.
itholic commented on code in PR #42955:
URL: https://github.com/apache/spark/pull/42955#discussion_r1327935904
##########
python/pyspark/pandas/tests/computation/test_compute.py:
##########
@@ -101,16 +101,10 @@ def test_mode(self):
with self.assertRaises(ValueError):
psdf.mode(axis=2)
- def f(index, iterator):
- return ["3", "3", "3", "3", "4"] if index == 3 else ["0", "1", "2", "3", "4"]
-
- rdd = self.spark.sparkContext.parallelize(
- [
- 1,
- ],
- 4,
- ).mapPartitionsWithIndex(f)
- df = self.spark.createDataFrame(rdd, schema="string")
+ data = [(i,) for i in ["3", "3", "3", "3", "4"]] + [
+ (i,) for i in ["0", "1", "2", "3", "4"]
+ ] * 3
+ df = self.spark.createDataFrame(data)
Review Comment:
cc @zhengruifeng FYI
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[GitHub] [spark] dongjoon-hyun commented on pull request #42955: [SPARK-43628][SPARK-43629][CONNECT][PS][TESTS] Clear message for JVM dependent tests.
Posted by "dongjoon-hyun (via GitHub)" <gi...@apache.org>.
dongjoon-hyun commented on PR #42955:
URL: https://github.com/apache/spark/pull/42955#issuecomment-1722434698
Could you re-trigger the failed pipelines?
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