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) -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org