vladanvasi-db commented on code in PR #47906:
URL: https://github.com/apache/spark/pull/47906#discussion_r1775214133
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sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/csv/UnivocityParserSuite.scala:
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@@ -323,6 +323,41 @@ class UnivocityParserSuite extends SparkFunSuite with
SQLHelper {
parameters = Map("fieldName" -> "`i`", "fields" -> ""))
}
+ test("Bad records test in permissive mode") {
+ def checkBadRecord(
+ input: String = "1,a",
+ dataSchema: StructType = StructType.fromDDL("i INTEGER, s STRING, d
DOUBLE"),
+ requiredSchema: StructType = StructType.fromDDL("i INTEGER, s STRING"),
+ options: Map[String, String] = Map("mode" -> "PERMISSIVE")):
BadRecordException = {
+ val csvOptions = new CSVOptions(options, false, "UTC")
+ val parser = new UnivocityParser(dataSchema, requiredSchema, csvOptions,
Seq())
+ intercept[BadRecordException] {
+ parser.parse(input)
+ }
+ }
+
+ // Bad record exception caused by conversion error
Review Comment:
The `PERMISSIVE` mode will "Fill the row in a best-effort manner", so if it
throws the exception, also the `FAILFAST` mode will throw the exception as
well, so we do not need to check that one additionally. On the other hand,
`DROPMALFORMED` mode will just drop the row and not throw the exception, so it
is not applicable here when checking `BadRecordException`.
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