gatorsmile commented on a change in pull request #23249: [SPARK-26297][SQL]
improve the doc of Distribution/Partitioning
URL: https://github.com/apache/spark/pull/23249#discussion_r240347775
##########
File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/physical/partitioning.scala
##########
@@ -22,13 +22,12 @@ import org.apache.spark.sql.types.{DataType, IntegerType}
/**
* Specifies how tuples that share common expressions will be distributed when
a query is executed
- * in parallel on many machines. Distribution can be used to refer to two
distinct physical
- * properties:
- * - Inter-node partitioning of data: In this case the distribution describes
how tuples are
- * partitioned across physical machines in a cluster. Knowing this
property allows some
- * operators (e.g., Aggregate) to perform partition local operations
instead of global ones.
- * - Intra-partition ordering of data: In this case the distribution
describes guarantees made
- * about how tuples are distributed within a single partition.
+ * in parallel on many machines.
+ *
+ * Distribution here refers to inter-node partitioning of data:
+ * - The distribution describes how tuples are partitioned across physical
machines in a cluster.
+ * Knowing this property allows some operators (e.g., Aggregate) to
perform partition local
+ * operations instead of global ones.
Review comment:
How about?
> Distribution here refers to inter-node partitioning of data. That is, it
describes how tuples are partitioned across physical machines in a cluster.
Knowing this property allows some operators (e.g., Aggregate) to perform
partition local operations instead of global ones.
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