beliefer opened a new pull request, #44398: URL: https://github.com/apache/spark/pull/44398
### What changes were proposed in this pull request? This PR fix a but by make JDBC dialect decide the decimal precision and scale. **How to reproduce the bug?** https://github.com/apache/spark/pull/44397 proposed DS V2 push down `PERCENTILE_CONT` and `PERCENTILE_DISC`. The bug fired when pushdown the below SQL to H2 JDBC. `SELECT "DEPT",PERCENTILE_CONT(0.5) WITHIN GROUP (ORDER BY "SALARY" ASC NULLS FIRST) FROM "test"."employee" WHERE 1=0 GROUP BY "DEPT"` **The root cause** `getQueryOutputSchema` used to get the output schema of query by call `JdbcUtils.getSchema`. The query for database H2 show below. `SELECT "DEPT",PERCENTILE_CONT(0.5) WITHIN GROUP (ORDER BY "SALARY" ASC NULLS FIRST) FROM "test"."employee" WHERE 1=0 GROUP BY "DEPT"` We can get the five variables from `ResultSetMetaData`, please refer: ``` columnName = "PERCENTILE_CONT(0.5) WITHIN GROUP (ORDER BY SALARY NULLS FIRST)" dataType = 2 typeName = "NUMERIC" fieldSize = 100000 fieldScale = 50000 ``` Then we get the catalyst schema with `JdbcUtils.getCatalystType`, it calls `DecimalType.bounded(precision, scale)` actually. The `DecimalType.bounded(100000, 50000)` returns `DecimalType(38, 38)`. At finally, `makeGetter` throws exception. ``` Caused by: org.apache.spark.SparkArithmeticException: [DECIMAL_PRECISION_EXCEEDS_MAX_PRECISION] Decimal precision 42 exceeds max precision 38. SQLSTATE: 22003 at org.apache.spark.sql.errors.DataTypeErrors$.decimalPrecisionExceedsMaxPrecisionError(DataTypeErrors.scala:48) at org.apache.spark.sql.types.Decimal.set(Decimal.scala:124) at org.apache.spark.sql.types.Decimal$.apply(Decimal.scala:577) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$makeGetter$4(JdbcUtils.scala:408) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.nullSafeConvert(JdbcUtils.scala:552) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$makeGetter$3(JdbcUtils.scala:408) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$makeGetter$3$adapted(JdbcUtils.scala:406) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anon$1.getNext(JdbcUtils.scala:358) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anon$1.getNext(JdbcUtils.scala:339) ``` ### Why are the changes needed? This PR fix the bug that `JdbcUtils` can't get the correct decimal type. ### 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'. --> ### 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. --> ### Was this patch authored or co-authored using generative AI tooling? <!-- If generative AI tooling has been used in the process of authoring this patch, please include the phrase: 'Generated-by: ' followed by the name of the tool and its version. If no, write 'No'. Please refer to the [ASF Generative Tooling Guidance](https://www.apache.org/legal/generative-tooling.html) for details. --> -- 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]
