Github user HyukjinKwon commented on a diff in the pull request:
https://github.com/apache/spark/pull/16928#discussion_r102366629
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/csv/UnivocityParser.scala
---
@@ -45,24 +46,41 @@ private[csv] class UnivocityParser(
// A `ValueConverter` is responsible for converting the given value to a
desired type.
private type ValueConverter = String => Any
+ private val corruptFieldIndex =
schema.getFieldIndex(options.columnNameOfCorruptRecord)
+ corruptFieldIndex.foreach { corrFieldIndex =>
+ require(schema(corrFieldIndex).dataType == StringType,
+ "A field for corrupt records must have a string type")
+ require(schema(corrFieldIndex).nullable, "A field for corrupt must be
nullable")
+ }
+
+ private val inputSchema = StructType(schema.filter(_.name !=
options.columnNameOfCorruptRecord))
+ CSVUtils.verifySchema(inputSchema)
+
private val valueConverters =
- schema.map(f => makeConverter(f.name, f.dataType, f.nullable,
options)).toArray
+ inputSchema.map(f => makeConverter(f.name, f.dataType, f.nullable,
options)).toArray
private val parser = new CsvParser(options.asParserSettings)
private var numMalformedRecords = 0
private val row = new GenericInternalRow(requiredSchema.length)
- private val indexArr: Array[Int] = {
+ private val indexArr: Array[(Int, Int)] = {
--- End diff --
Actually, it seems we don't need both? It seems second one is not used.
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