[GitHub] spark pull request: [SPARK-9735][SQL]Respect the user specified sc...

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

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

    https://github.com/apache/spark/pull/8026#discussion_r42445776
  
    --- Diff: sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/PartitioningUtils.scala ---
    @@ -236,15 +241,22 @@ private[sql] object PartitioningUtils {
       }
     
       /**
    -   * Converts a string to a [[Literal]] with automatic type inference.  Currently only supports
    -   * [[IntegerType]], [[LongType]], [[DoubleType]], [[DecimalType.SYSTEM_DEFAULT]], and
    -   * [[StringType]].
    +   * Converts a string to a [[Literal]] with automatic type inference if no field type specified.
    +   * Auto inference only supports [[IntegerType]], [[LongType]], [[DoubleType]],
    +   * [[DecimalType.SYSTEM_DEFAULT]], and [[StringType]].
        */
       private[sql] def inferPartitionColumnValue(
    +      expectedDT: Option[DataType],
           raw: String,
           defaultPartitionName: String,
    -      typeInference: Boolean): Literal = {
    -    if (typeInference) {
    +      typeInference: Boolean): Literal = expectedDT match {
    +    case Some(dt) if raw == defaultPartitionName =>
    +      Literal.create(null, dt)
    +    case Some(dt) if dt == StringType =>
    +      Literal.create(unescapePathName(raw), StringType)
    +    case Some(dt) =>
    +      Literal.create(Cast(Literal.create(unescapePathName(raw), StringType), dt).eval(null), dt)
    --- End diff --
    
    Instead of `eval(null)`, I think this could simply be `eval()`.


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