Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/18200
@maropu, I think it is fine. It only happens when the malformed column is
selected. For example,
The case below is fine
```scala
scala> import org.apache.spark.sql.types._
import org.apache.spark.sql.types._
scala> spark.read.schema(new StructType().add("a", IntegerType).add("b",
IntegerType)).csv("test.csv").show
+---+----+
| a| b|
+---+----+
| 1| 3|
| 1|null|
+---+----+
```
but it only happens when malformed column is selected:
```scala
scala> import org.apache.spark.sql.types._
import org.apache.spark.sql.types._
scala> spark.read.schema(new StructType().add("a", IntegerType).add("b",
IntegerType).add("_corrupt_record", StringType)).csv("test.csv").show
17/06/07 05:54:55 ERROR Executor: Exception in task 0.0 in stage 1.0 (TID 1)
java.lang.NullPointerException
at
scala.collection.immutable.StringLike$class.stripLineEnd(StringLike.scala:89)
at scala.collection.immutable.StringOps.stripLineEnd(StringOps.scala:29)
at
org.apache.spark.sql.execution.datasources.csv.UnivocityParser.org$apache$spark$sql$execution$datasources$csv$UnivocityParser$$getCurrentInput(UnivocityParser.scala:56)
at
org.apache.spark.sql.execution.datasources.csv.UnivocityParser$$anonfun$org$apache$spark$sql$execution$datasources$csv$UnivocityParser$$convert$1.apply(UnivocityParser.scala:211)
at
org.apache.spark.sql.execution.datasources.csv.UnivocityParser$$anonfun$org$apache$spark$sql$execution$datasources$csv$UnivocityParser$$convert$1.apply(UnivocityParser.scala:211)
at
org.apache.spark.sql.execution.datasources.FailureSafeParser$$anonfun$2.apply(FailureSafeParser.scala:50)
at
org.apache.spark.sql.execution.datasources.FailureSafeParser$$anonfun$2.apply(FailureSafeParser.scala:43)
at
org.apache.spark.sql.execution.datasources.FailureSafeParser.parse(FailureSafeParser.scala:64)
```
I think we introduced `columnNameOfCorruptRecord` option in CSV in 2.2.0 -
https://issues.apache.org/jira/browse/SPARK-18699. So, I guess this is not a
regression (but a bug we should definitely fix).
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