Major Description
Currently, if the number of tokens is less than the given schema, CSV datasource throws an NPE as below:
scala> spark.read.schema("a string, b string, unparsed string").option("columnNameOfCorruptRecord", "unparsed").csv(Seq("a").toDS).show() 17/06/05 13:59:26 ERROR Executor: Exception in task 0.0 in stage 3.0 (TID 3) 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$$anonfun$2.apply(FailureSafeParser.scala:43) at org.apache.spark.sql.execution.datasources.FailureSafeParser.parse(FailureSafeParser.scala:64) at org.apache.spark.sql.DataFrameReader$$anonfun$11$$anonfun$apply$4.apply(DataFrameReader.scala:471) at org.apache.spark.sql.DataFrameReader$$anonfun$11$$anonfun$apply$4.apply(DataFrameReader.scala:471) at scala.collection.Iterator$$anon$12.nextCur(Iterator.scala:434) at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:440) at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
If this is not given, it works as below:
scala> spark.read.schema("a string, b string, unparsed string").csv(Seq("a").toDS).show() +---+----+--------+ | a| b|unparsed| +---+----+--------+ | a|null| null| +---+----+--------+
