[GitHub] spark pull request: [SPARK-10562][SQL] support mixed case partitio...

[yang0228 <gi...@git.apache.org>]

Github user yang0228 commented on a diff in the pull request:

    https://github.com/apache/spark/pull/9226#discussion_r54844658
  
    --- Diff: sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala ---
    @@ -218,25 +233,19 @@ private[hive] class HiveMetastoreCatalog(val client: ClientInterface, hive: Hive
           }
         }
     
    -    val metastorePartitionColumns = userSpecifiedSchema.map { schema =>
    -      val fields = partitionColumns.map(col => schema(col))
    -      fields.map { field =>
    -        HiveColumn(
    -          name = field.name,
    -          hiveType = HiveMetastoreTypes.toMetastoreType(field.dataType),
    -          comment = "")
    -      }.toSeq
    -    }.getOrElse {
    -      if (partitionColumns.length > 0) {
    -        // The table does not have a specified schema, which means that the schema will be inferred
    -        // when we load the table. So, we are not expecting partition columns and we will discover
    -        // partitions when we load the table. However, if there are specified partition columns,
    -        // we simply ignore them and provide a warning message.
    -        logWarning(
    -          s"The schema and partitions of table $tableIdent will be inferred when it is loaded. " +
    -            s"Specified partition columns (${partitionColumns.mkString(",")}) will be ignored.")
    +    if (userSpecifiedSchema.isDefined && partitionColumns.length > 0) {
    +      tableProperties.put("spark.sql.sources.schema.numPartCols", partitionColumns.length.toString)
    +      partitionColumns.zipWithIndex.foreach { case (partCol, index) =>
    +        tableProperties.put(s"spark.sql.sources.schema.partCol.$index", partCol)
           }
    -      Seq.empty[HiveColumn]
    +    } else {
    +      // The table does not have a specified schema, which means that the schema will be inferred
    +      // when we load the table. So, we are not expecting partition columns and we will discover
    +      // partitions when we load the table. However, if there are specified partition columns,
    +      // we simply ignore them and provide a warning message.
    +      logWarning(
    +        s"The schema and partitions of table $tableIdent will be inferred when it is loaded. " +
    +          s"Specified partition columns (${partitionColumns.mkString(",")}) will be ignored.")
    --- End diff --
    
    Can you explain the change at line 293 "partitionColumns = Nil"? 
    When running "df.write.partitionBy("X").mode(SaveMode.Overwrite).saveAsTable(tableName) "(df generated with HiveContext) in spark 1.6, what I get in hive is a not-partitioned table. I've seen this line was "partitionColumns = partitionColumns" in spark1.5.2, which assigns the partition column. 


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