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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