Github user maropu commented on a diff in the pull request: https://github.com/apache/spark/pull/16928#discussion_r102648114 --- Diff: sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/csv/UnivocityParser.scala --- @@ -45,24 +45,41 @@ 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) + require(schema(corrFieldIndex).nullable) + } + + private val inputSchema = StructType(schema.filter(_.name != options.columnNameOfCorruptRecord)) + 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] = { + // This parser loads an `indexArr._1`-th position value in input tokens, + // then put the value in `row(indexArr._2)`. + private val indexArr: Array[(Int, Int)] = { val fields = if (options.dropMalformed) { // If `dropMalformed` is enabled, then it needs to parse all the values // so that we can decide which row is malformed. requiredSchema ++ schema.filterNot(requiredSchema.contains(_)) } else { requiredSchema } - fields.map(schema.indexOf(_: StructField)).toArray + val fieldsWithIndexes = fields.zipWithIndex + corruptFieldIndex.map { case corrFieldIndex => + fieldsWithIndexes.filter { case (_, i) => i != corrFieldIndex } + }.getOrElse { + fieldsWithIndexes + }.map { case (f, i) => + (inputSchema.indexOf(f), i) + }.toArray --- End diff -- okay, I'll update
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