johanl-db commented on code in PR #44803:
URL: https://github.com/apache/spark/pull/44803#discussion_r1464709783
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sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetTypeWideningSuite.scala:
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@@ -201,17 +290,17 @@ class ParquetTypeWideningSuite
Seq(5 -> 7, 5 -> 10, 5 -> 20, 10 -> 12, 10 -> 20, 20 -> 22) ++
Seq(7 -> 5, 10 -> 5, 20 -> 5, 12 -> 10, 20 -> 10, 22 -> 20)
}
- test(
- s"parquet decimal precision change Decimal($fromPrecision, 2) ->
Decimal($toPrecision, 2)") {
- checkAllParquetReaders(
- values = Seq("1.23", "10.34"),
- fromType = DecimalType(fromPrecision, 2),
- toType = DecimalType(toPrecision, 2),
- expectError = fromPrecision > toPrecision &&
- // parquet-mr allows reading decimals into a smaller precision
decimal type without
- // checking for overflows. See test below checking for the overflow
case in parquet-mr.
-
spark.conf.get(SQLConf.PARQUET_VECTORIZED_READER_ENABLED.key).toBoolean)
- }
+ test(
+ s"parquet decimal precision change Decimal($fromPrecision, 2) ->
Decimal($toPrecision, 2)") {
+ checkAllParquetReaders(
+ values = Seq("1.23", "10.34"),
+ fromType = DecimalType(fromPrecision, 2),
+ toType = DecimalType(toPrecision, 2),
+ expectError = fromPrecision > toPrecision &&
+ // parquet-mr allows reading decimals into a smaller precision decimal
type without
+ // checking for overflows. See test below checking for the overflow
case in parquet-mr.
Review Comment:
Yes the vectorized reader throws an exception which this test is checking
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