Github user HyukjinKwon commented on the issue: https://github.com/apache/spark/pull/16928 @maropu, I just ran some similar tests with JSON datasource. What do you think about matching it to JSON's behaviour by introducing `columnNameOfCorruptRecord`? I ran with the data and schema as below: ```scala Seq("""{"a": "a", "b" : 1}""").toDF().write.text("/tmp/path") val schema = StructType(StructField("a", IntegerType, true) :: StructField("b", StringType, true) :: StructField("_corrupt_record", StringType, true) :: Nil) ``` **`FAILFAST`** ```scala scala> spark.read.schema(schema).option("mode", "FAILFAST").json("/tmp/path").show() org.apache.spark.sql.catalyst.json.SparkSQLJsonProcessingException: Malformed line in FAILFAST mode: {"a": "a", "b" : 1} ``` **`DROPMALFORMED`** ```scala scala> spark.read.schema(schema).option("mode", "DROPMALFORMED").json("/tmp/path").show() +---+---+---------------+ | a| b|_corrupt_record| +---+---+---------------+ +---+---+---------------+ ``` **`PERMISSIVE`** ```scala scala> spark.read.schema(schema).option("mode", "PERMISSIVE").json("/tmp/path").show() +----+----+-------------------+ | a| b| _corrupt_record| +----+----+-------------------+ |null|null|{"a": "a", "b" : 1}| +----+----+-------------------+ ```
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