Jork Zijlstra created SPARK-18269:
-------------------------------------
Summary: NumberFormatException when reading csv for a nullable
column
Key: SPARK-18269
URL: https://issues.apache.org/jira/browse/SPARK-18269
Project: Spark
Issue Type: Bug
Components: SQL
Affects Versions: 2.0.1
Reporter: Jork Zijlstra
Having a schema with a nullable column thrown an
java.lang.NumberFormatException: null when the data + delimeter isn't specified
in the csv.
Specifying the schema:
StructType(Array(
StructField("id", IntegerType, nullable = false),
StructField("underlyingId", IntegerType, true)
))
Data (without trailing delimeter to specify the second column):
1
Read the data:
sparkSession.read
.schema(sourceSchema)
.option("header", "false")
.option("delimiter", """\t""")
.csv(files(dates): _*)
.rdd
Actual Result:
java.lang.NumberFormatException: null
at java.lang.Integer.parseInt(Integer.java:542)
at java.lang.Integer.parseInt(Integer.java:615)
at
scala.collection.immutable.StringLike$class.toInt(StringLike.scala:272)
at scala.collection.immutable.StringOps.toInt(StringOps.scala:29)
at
org.apache.spark.sql.execution.datasources.csv.CSVTypeCast$.castTo(CSVInferSchema.scala:244)
Reason:
The csv line is parsed into a Map (indexSafeTokens), which is short of one
value. So indexSafeTokens(index) throws a NullpointerException reading the
optional value which isn't in the Map.
The NullpointerException is then given to the CSVTypeCast.castTo(datum: String,
.....) as the datum value.
The subsequent NumberFormatException is thrown due to the fact that a
NullpointerException cannot be cast into the Type.
Possible fix:
- Use the provided schema to parse the line with the correct number of columns
- Since its nullable implement a try catch on CSVRelation.csvParser
indexSafeTokens(index)
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