[GitHub] spark pull request #14947: [WIP][SPARK-17388][SQL] Support for inferring typ...

[HyukjinKwon <gi...@git.apache.org>]

Github user HyukjinKwon commented on a diff in the pull request:

    https://github.com/apache/spark/pull/14947#discussion_r78304894
  
    --- Diff: sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/PartitioningUtils.scala ---
    @@ -307,20 +308,34 @@ object PartitioningUtils {
     
       /**
        * Converts a string to a [[Literal]] with automatic type inference.  Currently only supports
    -   * [[IntegerType]], [[LongType]], [[DoubleType]], [[DecimalType.SYSTEM_DEFAULT]], and
    -   * [[StringType]].
    +   * [[IntegerType]], [[LongType]], [[DoubleType]], [[DecimalType.SYSTEM_DEFAULT]], [[DateType]]
    +   * [[TimestampType]], and [[StringType]].
        */
       private[datasources] def inferPartitionColumnValue(
           raw: String,
           defaultPartitionName: String,
           typeInference: Boolean): Literal = {
    +    val decimalTry = Try {
    +      // `BigDecimal` conversion can fail when the `field` is not a form of number.
    +      val bigDecimal = new JBigDecimal(raw)
    +      // It reduces the cases for decimals by disallowing values having scale (eg. `1.1`).
    +      require(bigDecimal.scale <= 0)
    +      // `DecimalType` conversion can fail when
    +      //   1. The precision is bigger than 38.
    +      //   2. scale is bigger than precision.
    --- End diff --
    
    Ah, I think I should check this requirement. I will update the description soon too.


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