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Posted to reviews@spark.apache.org by "sarutak (via GitHub)" <gi...@apache.org> on 2025/07/29 22:58:26 UTC

[PR] [SPARK-53001][TESTS] Fix test_df_unpivot to pass with Spark 4.0 [spark-connect-rust]

sarutak opened a new pull request, #4:
URL: https://github.com/apache/spark-connect-rust/pull/4

   # Description
   
   This PR proposes to fix the issue that `test_df_unpivot` doesn't  pass with Spark 4.0.
   ```
   ---- dataframe::tests::test_df_unpivot stdout ----
   SparkSession Setup
   
   thread 'dataframe::tests::test_df_unpivot' panicked at crates/connect/src/dataframe.rs:2463:9:
   assertion `left == right` failed
     left: RecordBatch { schema: Schema { fields: [Field { name: "id", data_type: Int64, nullable: false, dict_id: 0, dict_is_ordered: false, metadata: {} }, Field { name: "var", data_type: Utf8, nullable: false, dict_id: 0, dict_is_ordered: false, metadata: {} }, Field { name: "val", data_type: Float32, nullable: false, dict_id: 0, dict_is_ordered: false, metadata: {} }], metadata: {} }, columns: [PrimitiveArray<Int64>
   [
     1,
     1,
     2,
     2,
   ], StringArray
   [
     "int",
     "float",
     "int",
     "float",
   ], PrimitiveArray<Float32>
   [
     11.0,
     1.1,
     12.0,
     1.2,
   ]], row_count: 4 }
    right: RecordBatch { schema: Schema { fields: [Field { name: "id", data_type: Int64, nullable: false, dict_id: 0, dict_is_ordered: false, metadata: {} }, Field { name: "var", data_type: Utf8, nullable: false, dict_id: 0, dict_is_ordered: false, metadata: {} }, Field { name: "val", data_type: Float64, nullable: false, dict_id: 0, dict_is_ordered: false, metadata: {} }], metadata: {} }, columns: [PrimitiveArray<Int64>
   [
     1,
     1,
     2,
     2,
   ], StringArray
   [
     "int",
     "float",
     "int",
     "float",
   ], PrimitiveArray<Float64>
   [
     11.0,
     1.100000023841858,
     12.0,
     1.2000000476837158,
   ]], row_count: 4 }
   ```
   
   As of Spark 4.0, ANSI mode is enabled by default but this test doesn't consider  it.
   To fix this issue, I tweaked the test so that the test pass in both ANSI mode is enabled or not.
   
   ## Related Issue(s)
   SPARK-53001


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Re: [PR] [SPARK-53001][TESTS] Fix test_df_unpivot to pass with Spark 4.0 [spark-connect-rust]

Posted by "sarutak (via GitHub)" <gi...@apache.org>.
sarutak commented on PR #4:
URL: https://github.com/apache/spark-connect-rust/pull/4#issuecomment-3166340562

   Now that the we have a merge script am I OK to merge this by myself?


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Re: [PR] [SPARK-53001][TESTS] Fix test_df_unpivot to pass with Spark 4.0 [spark-connect-rust]

Posted by "xuanyuanking (via GitHub)" <gi...@apache.org>.
xuanyuanking commented on PR #4:
URL: https://github.com/apache/spark-connect-rust/pull/4#issuecomment-3161282975

   LGTM, will merge after we have the merge script!


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Re: [PR] [SPARK-53001][TESTS] Fix test_df_unpivot to pass with Spark 4.0 [spark-connect-rust]

Posted by "sarutak (via GitHub)" <gi...@apache.org>.
sarutak closed pull request #4: [SPARK-53001][TESTS] Fix test_df_unpivot to pass with Spark 4.0
URL: https://github.com/apache/spark-connect-rust/pull/4


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Re: [PR] [SPARK-53011][TESTS] Fix test_df_unpivot to pass with Spark 4.0 [spark-connect-rust]

Posted by "sarutak (via GitHub)" <gi...@apache.org>.
sarutak commented on PR #4:
URL: https://github.com/apache/spark-connect-rust/pull/4#issuecomment-3177523452

   I noticed the PR title has a wrong JIRA ID.
   I changed it from SPARK-53001 to SPARK-53011.


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Re: [PR] [SPARK-53001][TESTS] Fix test_df_unpivot to pass with Spark 4.0 [spark-connect-rust]

Posted by "sarutak (via GitHub)" <gi...@apache.org>.
sarutak commented on PR #4:
URL: https://github.com/apache/spark-connect-rust/pull/4#issuecomment-3177516694

   Merged to `master`. 
   @xuanyuanking Thanks for the review!


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Re: [PR] [SPARK-53001][TESTS] Fix test_df_unpivot to pass with Spark 4.0 [spark-connect-rust]

Posted by "xuanyuanking (via GitHub)" <gi...@apache.org>.
xuanyuanking commented on PR #4:
URL: https://github.com/apache/spark-connect-rust/pull/4#issuecomment-3166621726

   Yep, just go ahead for straightforward fixes! Thanks Sarutak!


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