[SPARK-40876][SQL][TESTS][FOLLOWUP] Fix failed test in ParquetTypeWideningSuite when SPARK_ANSI_SQL_MODE is set to true

[LuciferYang]

What changes were proposed in this pull request?

This pr aims to change the test inputs in ParquetTypeWideningSuite to valid int to fix failed test in ParquetTypeWideningSuite when SPARK_ANSI_SQL_MODE` is set to true

Why are the changes needed?

Fix the day test failure when SPARK_ANSI_SQL_MODE is set to true.

• https://github.com/apache/spark/actions/runs/7318074558/job/19934321639
• https://github.com/apache/spark/actions/runs/7305312703/job/19908735746
• https://github.com/apache/spark/actions/runs/7311683968/job/19921532402

[info] - unsupported parquet conversion IntegerType -> TimestampType *** FAILED *** (68 milliseconds)
[info]   org.apache.spark.SparkException: Job aborted due to stage failure: Task 1 in stage 261.0 failed 1 times, most recent failure: Lost task 1.0 in stage 261.0 (TID 523) (localhost executor driver): org.apache.spark.SparkNumberFormatException: [CAST_INVALID_INPUT] The value '1.23' of the type "STRING" cannot be cast to "INT" because it is malformed. Correct the value as per the syntax, or change its target type. Use `try_cast` to tolerate malformed input and return NULL instead. If necessary set "spark.sql.ansi.enabled" to "false" to bypass this error. SQLSTATE: 22018
[info] == DataFrame ==
[info] "cast" was called from
[info] org.apache.spark.sql.execution.datasources.parquet.ParquetTypeWideningSuite.writeParquetFiles(ParquetTypeWideningSuite.scala:113)
[info] 
[info] 	at org.apache.spark.sql.errors.QueryExecutionErrors$.invalidInputInCastToNumberError(QueryExecutionErrors.scala:145)
[info] 	at org.apache.spark.sql.catalyst.util.UTF8StringUtils$.withException(UTF8StringUtils.scala:51)
[info] 	at org.apache.spark.sql.catalyst.util.UTF8StringUtils$.toIntExact(UTF8StringUtils.scala:34)
[info] 	at org.apache.spark.sql.catalyst.util.UTF8StringUtils.toIntExact(UTF8StringUtils.scala)
[info] 	at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
[info] 	at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
[info] 	at org.apache.spark.sql.execution.WholeStageCodegenEvaluatorFactory$WholeStageCodegenPartitionEvaluator$$anon$1.hasNext(WholeStageCodegenEvaluatorFactory.scala:43)
[info] 	at org.apache.spark.sql.execution.datasources.FileFormatWriter$.executeTask(FileFormatWriter.scala:388)
[info] 	at org.apache.spark.sql.execution.datasources.WriteFilesExec.$anonfun$doExecuteWrite$1(WriteFiles.scala:101)
[info] 	at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:891)
[info] 	at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:891)
[info] 	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
[info] 	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:365)
[info] 	at org.apache.spark.rdd.RDD.iterator(RDD.scala:329)
[info] 	at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:93)
[info] 	at org.apache.spark.TaskContext.runTaskWithListeners(TaskContext.scala:171)
[info] 	at org.apache.spark.scheduler.Task.run(Task.scala:141)
[info] 	at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$4(Executor.scala:628)
[info] 	at org.apache.spark.util.SparkErrorUtils.tryWithSafeFinally(SparkErrorUtils.scala:64)
[info] 	at org.apache.spark.util.SparkErrorUtils.tryWithSafeFinally$(SparkErrorUtils.scala:61)
[info] 	at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:96)
[info] 	at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:631)
[info] 	at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1136)
[info] 	at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:635)
[info] 	at java.base/java.lang.Thread.run(Thread.java:840)

Does this PR introduce any user-facing change?

No

How was this patch tested?

• Pass GitHub Actions
• Manual check

SPARK_ANSI_SQL_MODE=true build/sbt "sql/testOnly org.apache.spark.sql.execution.datasources.parquet.ParquetTypeWideningSuite"

Before

[info] Run completed in 27 seconds, 432 milliseconds.
[info] Total number of tests run: 34
[info] Suites: completed 1, aborted 0
[info] Tests: succeeded 31, failed 3, canceled 0, ignored 0, pending 0
[info] *** 3 TESTS FAILED ***
[error] Failed tests:
[error]         org.apache.spark.sql.execution.datasources.parquet.ParquetTypeWideningSuite

After

[info] Run completed in 28 seconds, 880 milliseconds.
[info] Total number of tests run: 31
[info] Suites: completed 1, aborted 0
[info] Tests: succeeded 31, failed 0, canceled 0, ignored 0, pending 0
[info] All tests passed.

Was this patch authored or co-authored using generative AI tooling?

No

[LuciferYang]

It seems that only the test cases used the input test data that would fail to type conversion when ANSI MODE is set to true when constructing test cases that would throw errors when read. In this PR, To quickly fix , I have skipped these three test inputs

@cloud-fan @zhengruifeng FYI

[cloud-fan]

shall we just use valid int values?

[LuciferYang]

should be ok

[LuciferYang]

d95098c change to use 1 and 10 as input

[dongjoon-hyun]

+1, LGTM. Thank you, @LuciferYang and @cloud-fan .
Merged to master.

[LuciferYang]

Thanks @dongjoon-hyun and @cloud-fan ~