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From srowen <...@git.apache.org>
Subject [GitHub] spark pull request #14118: [SPARK-16462][SPARK-16460][SPARK-15144][SQL] Make...
Date Thu, 15 Sep 2016 08:35:51 GMT
Github user srowen commented on a diff in the pull request:

    https://github.com/apache/spark/pull/14118#discussion_r78913816
  
    --- Diff: sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/csv/CSVInferSchema.scala
---
    @@ -232,66 +232,62 @@ 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 {
    -          val value = new BigDecimal(datum.replaceAll(",", ""))
    -          Decimal(value, dt.precision, dt.scale)
    -        }
    -      case _: TimestampType =>
    -        // This one will lose microseconds parts.
    -        // See https://issues.apache.org/jira/browse/SPARK-10681.
    -        Try(options.timestampFormat.parse(datum).getTime * 1000L)
    -          .getOrElse {
    -            // If it fails to parse, then tries the way used in 2.0 and 1.x for backwards
    -            // compatibility.
    -            DateTimeUtils.stringToTime(datum).getTime  * 1000L
    +    if (datum == options.nullValue && nullable) {
    +      null
    +    } else {
    +      castType match {
    +        case _: ByteType => datum.toByte
    +        case _: ShortType => datum.toShort
    +        case _: IntegerType => datum.toInt
    +        case _: LongType => datum.toLong
    +        case _: FloatType =>
    +          if (datum == options.nanValue) {
    --- End diff --
    
    Can these nested if-else statements be a match statement? or is there some overhead to
it that is too significant?


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