Github user HyukjinKwon commented on a diff in the pull request:
https://github.com/apache/spark/pull/13912#discussion_r71120468
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/csv/CSVRelation.scala
---
@@ -195,18 +202,40 @@ private[sql] class CsvOutputWriter(
private var records: Long = 0L
private val csvWriter = new LineCsvWriter(params,
dataSchema.fieldNames.toSeq)
- private def rowToString(row: Seq[Any]): Seq[String] = row.map { field =>
- if (field != null) {
- field.toString
- } else {
- params.nullValue
+ private def rowToString(row: InternalRow): Seq[String] = {
+ var i = 0
+ val values = new Array[String](row.numFields)
+ while (i < row.numFields) {
+ if (!row.isNullAt(i)) {
+ values(i) = fieldsConverters(i).apply(row, i)
+ } else {
+ values(i) = params.nullValue
+ }
+ i += 1
}
+ values
+ }
+
+ private def makeConverter(dataType: DataType): ValueConverter = dataType
match {
+ case DateType if params.dateFormat != null =>
+ (row: InternalRow, ordinal: Int) =>
+
params.dateFormat.format(DateTimeUtils.toJavaDate(row.getInt(ordinal)))
+
+ case TimestampType if params.dateFormat != null =>
+ (row: InternalRow, ordinal: Int) =>
+
params.dateFormat.format(DateTimeUtils.toJavaTimestamp(row.getLong(ordinal)))
--- End diff --
@srowen Maybe you are looking for this case. I had to do it like this to
avoid per-record type dispatch.
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