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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