Github user lw-lin commented on a diff in the pull request:
https://github.com/apache/spark/pull/14118#discussion_r70182426
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/csv/CSVInferSchema.scala
---
@@ -238,59 +238,55 @@ private[csv] object CSVTypeCast {
nullable: Boolean = true,
options: CSVOptions = CSVOptions()): Any = {
- castType match {
- case _: ByteType => if (datum == options.nullValue && nullable) null
else datum.toByte
- case _: ShortType => if (datum == options.nullValue && nullable)
null else datum.toShort
- case _: IntegerType => if (datum == options.nullValue && nullable)
null else datum.toInt
- case _: LongType => if (datum == options.nullValue && nullable) null
else datum.toLong
- case _: FloatType =>
- if (datum == options.nullValue && nullable) {
- null
- } else if (datum == options.nanValue) {
- Float.NaN
- } else if (datum == options.negativeInf) {
- Float.NegativeInfinity
- } else if (datum == options.positiveInf) {
- Float.PositiveInfinity
- } else {
- Try(datum.toFloat)
-
.getOrElse(NumberFormat.getInstance(Locale.getDefault).parse(datum).floatValue())
- }
- case _: DoubleType =>
- if (datum == options.nullValue && nullable) {
- null
- } else if (datum == options.nanValue) {
- Double.NaN
- } else if (datum == options.negativeInf) {
- Double.NegativeInfinity
- } else if (datum == options.positiveInf) {
- Double.PositiveInfinity
- } else {
- Try(datum.toDouble)
-
.getOrElse(NumberFormat.getInstance(Locale.getDefault).parse(datum).doubleValue())
- }
- case _: BooleanType => datum.toBoolean
- case dt: DecimalType =>
- if (datum == options.nullValue && nullable) {
- null
- } else {
+ if (datum == options.nullValue && nullable &&
(!castType.isInstanceOf[StringType])) {
--- End diff --
> ... why StringType is excluded?
Hi @HyukjinKwon, it's just to keep consistency with we did in `spark-csv`
for 1.6. Actually I don't have strong preference here -- maybe we should not
ignore `StringType`? @rxin could you share some thoughts? Thanks!
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