[GitHub] [spark] cloud-fan commented on a diff in pull request #37211: [SPARK-39644][SQL] Add RangePartitioning reporting for V2 DataSources

[GitBox <gi...@apache.org>]

cloud-fan commented on code in PR #37211:
URL: https://github.com/apache/spark/pull/37211#discussion_r948663939


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sql/catalyst/src/main/scala/org/apache/spark/sql/execution/datasources/v2/DataSourceV2Relation.scala:
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@@ -119,13 +119,16 @@ case class DataSourceV2Relation(
  * @param output the output attributes of this relation
  * @param keyGroupedPartitioning if set, the partitioning expressions that are used to split the
  *                               rows in the scan across different partitions
- * @param ordering if set, the ordering provided by the scan
+ * @param rangePartitioning if set, the range partitioning expressions that are used to split the
+ *                               rows in the scan across different partitions
+ * @param ordering if set, the in-partition ordering provided by the scan
  */
 case class DataSourceV2ScanRelation(
     relation: DataSourceV2Relation,
     scan: Scan,
     output: Seq[AttributeReference],
     keyGroupedPartitioning: Option[Seq[Expression]] = None,
+    rangePartitioning: Option[Seq[SortOrder]] = None,

Review Comment:
   we need to clearly define the semantics here, as there are two sort orders now. More specially, what if a scan reports both `RangePartitioning` and ordering? There are a few options:
   1. require the reported `RangePartitioning` and ordering to be compatible
   2. let `RangePartitioning` only define cross-partitions ordering, while `SupportsReportOrdering` is for data ordering within each partition.



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