sunchao commented on a change in pull request #35657:
URL: https://github.com/apache/spark/pull/35657#discussion_r839888801
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File path:
sql/catalyst/src/main/java/org/apache/spark/sql/connector/read/partitioning/KeyGroupedPartitioning.java
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@@ -18,27 +18,37 @@
package org.apache.spark.sql.connector.read.partitioning;
import org.apache.spark.annotation.Evolving;
-import org.apache.spark.sql.connector.read.PartitionReader;
+import org.apache.spark.sql.connector.expressions.Expression;
/**
- * An interface to represent data distribution requirement, which specifies
how the records should
- * be distributed among the data partitions (one {@link PartitionReader}
outputs data for one
- * partition).
+ * Represents a partitioning where rows are split across partitions based on
the expressions
+ * returned by {@link KeyGroupedPartitioning#clustering}.
* <p>
- * Note that this interface has nothing to do with the data ordering inside one
- * partition(the output records of a single {@link PartitionReader}).
- * <p>
- * The instance of this interface is created and provided by Spark, then
consumed by
- * {@link Partitioning#satisfy(Distribution)}. This means data source
developers don't need to
- * implement this interface, but need to catch as more concrete
implementations of this interface
- * as possible in {@link Partitioning#satisfy(Distribution)}.
- * <p>
- * Concrete implementations until now:
- * <ul>
- * <li>{@link ClusteredDistribution}</li>
- * </ul>
+ * Data source implementations should make sure that all rows where
+ * {@link KeyGroupedPartitioning#clustering} evaluate to the same value should
be in the same
+ * partition.
Review comment:
Oops you are right. I forgot to update this. Will add.
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