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[SPARK-37196][SQL] HiveDecimal enforcePrecisionScale failed return null #34519

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[SPARK-37196][SQL] HiveDecimal enforcePrecisionScale failed return null #34519

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[SPARK-37196][SQL] HiveDecimal enforcePrecisionScala failed return null
AngersZhuuuu Nov 8, 2021
2da2b49
update
AngersZhuuuu Nov 8, 2021
20048fb
Update SQLQuerySuite.scala
AngersZhuuuu Nov 8, 2021
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15 changes: 12 additions & 3 deletions sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveShim.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -101,10 +101,19 @@ private[hive] object HiveShim {

def toCatalystDecimal(hdoi: HiveDecimalObjectInspector, data: Any): Decimal = {
if (hdoi.preferWritable()) {
Decimal(hdoi.getPrimitiveWritableObject(data).getHiveDecimal().bigDecimalValue,
hdoi.precision(), hdoi.scale())
val value = hdoi.getPrimitiveWritableObject(data)
if (value == null) {
null
} else {
Decimal(value.getHiveDecimal().bigDecimalValue, hdoi.precision(), hdoi.scale())
}
} else {
Decimal(hdoi.getPrimitiveJavaObject(data).bigDecimalValue(), hdoi.precision(), hdoi.scale())
val value = hdoi.getPrimitiveJavaObject(data)
if (value == null) {
null
} else {
Decimal(value.bigDecimalValue(), hdoi.precision(), hdoi.scale())
}
}
}

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17 changes: 17 additions & 0 deletions sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala
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Expand Up @@ -2642,6 +2642,23 @@ abstract class SQLQuerySuiteBase extends QueryTest with SQLTestUtils with TestHi
}
}
}

test("SPARK-37196: HiveDecimal Precision Scale match failed should return null") {
withTempDir { dir =>
withSQLConf(HiveUtils.CONVERT_METASTORE_PARQUET.key -> "false") {
withTable("test_precision") {
val df = sql("SELECT 'dummy' AS name, 1000000000000000000010.7000000000000010 AS value")
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@cloud-fan cloud-fan Nov 8, 2021

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can we use CAST(1.2 AS DECIMAL(38, 16)) instead of writing a long decimal literal?

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@AngersZhuuuu AngersZhuuuu Nov 8, 2021 •
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CAST(1.2 AS DECIMAL(38, 16))

Can't, it's an enforce convert.

df.write.mode("Overwrite").parquet(dir.getAbsolutePath)
sql(
s"""
|CREATE EXTERNAL TABLE test_precision(name STRING, value DECIMAL(18,6))
|STORED AS PARQUET LOCATION '${dir.getAbsolutePath}'
|""".stripMargin)
checkAnswer(sql("SELECT * FROM test_precision"), Row("dummy", null))
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what's the behavior of builtin file source tables? do we also return null?

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@cloud-fan cloud-fan Nov 8, 2021 •
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and what's the behavior if we do it purely in Hive?

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@AngersZhuuuu AngersZhuuuu Nov 8, 2021

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what's the behavior of builtin file source tables? do we also return null?

Hmmm, non vectorized parquet reader return null as well, vectorized reader throw below exception

[info]   Cause: org.apache.spark.sql.execution.QueryExecutionException: Parquet column cannot be converted in file file:///Users/yi.zhu/Documents/project/Angerszhuuuu/spark/sql/hive/target/tmp/hive_execution_test_group/spark-628e3c21-15ee-4473-b207-60a530ced804/part-00000-3f384838-d11f-4c3b-83a1-396efad6df79-c000.snappy.parquet. Column: [value], Expected: decimal(18,6), Found: FIXED_LEN_BYTE_ARRAY
[info]   at org.apache.spark.sql.errors.QueryExecutionErrors$.unsupportedSchemaColumnConvertError(QueryExecutionErrors.scala:635)
[info]   at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.nextIterator(FileScanRDD.scala:195)
[info]   at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.hasNext(FileScanRDD.scala:104)
[info]   at org.apache.spark.sql.execution.FileSourceScanExec$$anon$1.hasNext(DataSourceScanExec.scala:531)
[info]   at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.columnartorow_nextBatch_0$(generated.java:29)
[info]   at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(generated.java:42)
[info]   at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
[info]   at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:759)
[info]   at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)
[info]   at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)
[info]   at org.apache.spark.util.Utils$.getIteratorSize(Utils.scala:1895)
[info]   at org.apache.spark.rdd.RDD.$anonfun$count$1(RDD.scala:1274)
[info]   at org.apache.spark.rdd.RDD.$anonfun$count$1$adapted(RDD.scala:1274)
[info]   at org.apache.spark.SparkContext.$anonfun$runJob$5(SparkContext.scala:2267)
[info]   at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
[info]   at org.apache.spark.scheduler.Task.run(Task.scala:136)
[info]   at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:507)
[info]   at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1468)
[info]   at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:510)
[info]   at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
[info]   at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
[info]   at java.lang.Thread.run(Thread.java:748)
[info]   Cause: org.apache.spark.sql.execution.datasources.SchemaColumnConvertNotSupportedException:
[info]   at org.apache.spark.sql.execution.datasources.parquet.ParquetVectorUpdaterFactory.constructConvertNotSupportedException(ParquetVectorUpdaterFactory.java:1079)
[info]   at org.apache.spark.sql.execution.datasources.parquet.ParquetVectorUpdaterFactory.getUpdater(ParquetVectorUpdaterFactory.java:174)
[info]   at org.apache.spark.sql.execution.datasources.parquet.VectorizedColumnReader.readBatch(VectorizedColumnReader.java:154)
[info]   at org.apache.spark.sql.execution.datasources.parquet.VectorizedParquetRecordReader.nextBatch(VectorizedParquetRecordReader.java:296)
[info]   at org.apache.spark.sql.execution.datasources.parquet.VectorizedParquetRecordReader.nextKeyValue(VectorizedParquetRecordReader.java:194)
[info]   at org.apache.spark.sql.execution.datasources.RecordReaderIterator.hasNext(RecordReaderIterator.scala:39)
[info]   at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.hasNext(FileScanRDD.scala:104)
[info]   at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.nextIterator(FileScanRDD.scala:191)
[info]   at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.hasNext(FileScanRDD.scala:104)
[info]   at org.apache.spark.sql.execution.FileSourceScanExec$$anon$1.hasNext(DataSourceScanExec.scala:531)
[info]   at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.columnartorow_nextBatch_0$(generated.java:29)
[info]   at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(generated.java:42)
[info]   at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
[info]   at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:759)
[info]   at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)
[info]   at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)
[info]   at org.apache.spark.util.Utils$.getIteratorSize(Utils.scala:1895)
[info]   at org.apache.spark.rdd.RDD.$anonfun$count$1(RDD.scala:1274)
[info]   at org.apache.spark.rdd.RDD.$anonfun$count$1$adapted(RDD.scala:1274)
[info]   at org.apache.spark.SparkContext.$anonfun$runJob$5(SparkContext.scala:2267)
[info]   at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
[info]   at org.apache.spark.scheduler.Task.run(Task.scala:136)
[info]   at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:507)
[info]   at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1468)
[info]   at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:510)
[info]   at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
[info]   at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
[info]   at java.lang.Thread.run(Thread.java:748)

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@AngersZhuuuu AngersZhuuuu Nov 8, 2021

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Hive return NULL too

image

}
}
}
}
}

@SlowHiveTest
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