[GitHub] [spark] AngersZhuuuu commented on a change in pull request #24973: [SPARK-28169] Fix Partition table partition PushDown failed by "OR" expression

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AngersZhuuuu commented on a change in pull request #24973: [SPARK-28169] Fix Partition table partition  PushDown failed by "OR" expression 
URL: https://github.com/apache/spark/pull/24973#discussion_r298860931
 
 

 ##########
 File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/planning/patterns.scala
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 @@ -310,3 +310,97 @@ object PhysicalWindow {
     case _ => None
   }
 }
+
+/**
+ * Extract partition push down condition from ExpressionSet
+ * Since origin judge condition is
+ *    {
+ *       !expression.references.isEmpty &&
+ *             expression.references.subsetOf(partitionKeyIds)
+ *    }
+ *
+ *  This can only push down simple condition expression.
+ *  Such as table:
+ *   CREATE TABLE DEFAULT.PARTITION_TABLE(
+ *   A STRING,
+ *   B STRING)
+ *   PARTITIONED BY(DT STRING)
+ *
+ * With SQL:
+ *   SELECT A, B
+ *   FROM DEFAULT.PARTITION_TABLE
+ *   WHERE DT = 20190601 OR (DT = 20190602 AND C = "TEST")
+ *
+ * Where condition "DT = 20190601 OR (DT = 20190602 AND C = "TEST")"
 
 Review comment:
   @cloud-fan  
   In this place it will return (DT = 20190601 OR DT = 20190602). 
   But this whole condition will still return to filter.
   What I want to do is purely to avoid  read unnecessary partitions. When this case we only read partition(dt=20190601 + dt=20190602), If we don't push down this, we will read all data.
   
   In  condition " **(DT = 20190602 AND C = "TEST")** ", **DT = 20190602**  is **C = "TEST"**'s precondition. 
   
   If the whole condition is **DT = 20190601 OR (DT = 20190602 OR C = "TEST")**. We should return null, since **DT = 20190602**  is not  **C = "TEST"**'s  constraint. 

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