ashokraminedi commented on code in PR #20130:
URL: https://github.com/apache/hudi/pull/20130#discussion_r4137835132
##########
hudi-client/hudi-spark-client/src/main/java/org/apache/hudi/client/utils/SparkInternalSchemaConverter.java:
##########
@@ -349,9 +349,13 @@ private static boolean
convertIntLongType(WritableColumnVector oldV, WritableCol
} else if (newType instanceof StringType) {
newV.putByteArray(i, getUTF8Bytes((isInt ? oldV.getInt(i) :
oldV.getLong(i)) + ""));
} else if (newType instanceof DecimalType) {
+ DecimalType decimalType = (DecimalType) newType;
Review Comment:
Agreed, this is useful to pin the converter behavior independently of Spark
SQL.
Added `testDecimalPrecisionOverflow` in `TestSparkInternalSchemaConverter`
in `889b09ac6c27`. It calls `convertColumnVectorType` directly with
`OnHeapColumnVector`s and covers INT, LONG, FLOAT, DOUBLE, and STRING ->
`DECIMAL(4, 2)` overflow, asserting that each produces NULL with ANSI disabled.
This gives the affected conversion paths direct coverage without a Spark SQL
or version guard.
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