panbingkun commented on code in PR #36169:
URL: https://github.com/apache/spark/pull/36169#discussion_r850075349
##########
sql/core/src/test/scala/org/apache/spark/sql/errors/QueryExecutionErrorsSuite.scala:
##########
@@ -278,4 +284,35 @@ class QueryExecutionErrorsSuite extends QueryTest
assert(e.getMessage ===
"Datetime operation overflow: add 1000000 YEAR to TIMESTAMP '2022-03-09
01:02:03'.")
}
+
+ test("CANNOT_PARSE_DECIMAL: unparseable decimal") {
+ val e1 = intercept[SparkException] {
+ val schema = new StructType().add("money", DecimalType.DoubleDecimal)
+ spark
+ .read
+ .schema(schema)
+ .format("csv")
+ .option("header", "true")
+ .option("locale", Locale.ROOT.toLanguageTag)
+ .option("multiLine", "true")
+ .option("inferSchema", "false")
+ .option("mode", "FAILFAST")
Review Comment:
### from_csv don't support FailFastMode, code as folllow:
#### In CsvToStructs.parser
if (mode != PermissiveMode && mode != FailFastMode) {
throw QueryCompilationErrors.parseModeUnsupportedError("from_csv",
mode)
}
##
### if Mode is not FailFastMode, the deep exception: CANNOT_PARSE_DECIMAL,
can't throw。
#### In FailureSafeParser:
def parse(input: IN): Iterator[InternalRow] = {
try {
rawParser.apply(input).iterator.map(row => toResultRow(Some(row), ()
=> null))
} catch {
case e: BadRecordException => mode match {
case PermissiveMode =>
Iterator(toResultRow(e.partialResult(), e.record))
case DropMalformedMode =>
Iterator.empty
case FailFastMode =>
throw
QueryExecutionErrors.malformedRecordsDetectedInRecordParsingError(e)
}
}
}
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