From 8f26eb5ef6853a6666d7d9481b333de70bc501ed Mon Sep 17 00:00:00 2001
From: gatorsmile <gatorsmile@gmail.com>
Date: Mon, 1 Feb 2016 11:57:13 -0800
Subject: [SPARK-12705][SPARK-10777][SQL] Analyzer Rule ResolveSortReferences

JIRA: https://issues.apache.org/jira/browse/SPARK-12705

**Scope:**
This PR is a general fix for sorting reference resolution when the child's `outputSet` does not have the order-by attributes (called, *missing attributes*):
  - UnaryNode support is limited to `Project`, `Window`, `Aggregate`, `Distinct`, `Filter`, `RepartitionByExpression`.
  - We will not try to resolve the missing references inside a subquery, unless the outputSet of this subquery contains it.

**General Reference Resolution Rules:**
  - Jump over the nodes with the following types: `Distinct`, `Filter`, `RepartitionByExpression`. Do not need to add missing attributes. The reason is their `outputSet` is decided by their `inputSet`, which is the `outputSet` of their children.
  - Group-by expressions in `Aggregate`: missing order-by attributes are not allowed to be added into group-by expressions since it will change the query result. Thus, in RDBMS, it is not allowed.
  - Aggregate expressions in `Aggregate`: if the group-by expressions in `Aggregate` contains the missing attributes but aggregate expressions do not have it, just add them into the aggregate expressions. This can resolve the analysisExceptions thrown by the three TCPDS queries.
  - `Project` and `Window` are special. We just need to add the missing attributes to their `projectList`.

**Implementation:**
  1. Traverse the whole tree in a pre-order manner to find all the resolvable missing order-by attributes.
  2. Traverse the whole tree in a post-order manner to add the found missing order-by attributes to the node if their `inputSet` contains the attributes.
  3. If the origins of the missing order-by attributes are different nodes, each pass only resolves the missing attributes that are from the same node.

**Risk:**
Low. This rule will be trigger iff ```!s.resolved && child.resolved``` is true. Thus, very few cases are affected.

Author: gatorsmile <gatorsmile@gmail.com>

Closes #10678 from gatorsmile/sortWindows.
---
 .../spark/sql/hive/execution/SQLQuerySuite.scala   | 84 +++++++++++++++++++++-
 1 file changed, 83 insertions(+), 1 deletion(-)

(limited to 'sql/hive')

diff --git a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala
index 1ada2e325b..6048b8f5a3 100644
--- a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala
+++ b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/SQLQuerySuite.scala
@@ -736,7 +736,7 @@ class SQLQuerySuite extends QueryTest with SQLTestUtils with TestHiveSingleton {
         """.stripMargin), (2 to 6).map(i => Row(i)))
   }
 
-  test("window function: udaf with aggregate expressin") {
+  test("window function: udaf with aggregate expression") {
     val data = Seq(
       WindowData(1, "a", 5),
       WindowData(2, "a", 6),
@@ -927,6 +927,88 @@ class SQLQuerySuite extends QueryTest with SQLTestUtils with TestHiveSingleton {
       ).map(i => Row(i._1, i._2, i._3, i._4)))
   }
 
+  test("window function: Sorting columns are not in Project") {
+    val data = Seq(
+      WindowData(1, "d", 10),
+      WindowData(2, "a", 6),
+      WindowData(3, "b", 7),
+      WindowData(4, "b", 8),
+      WindowData(5, "c", 9),
+      WindowData(6, "c", 11)
+    )
+    sparkContext.parallelize(data).toDF().registerTempTable("windowData")
+
+    checkAnswer(
+      sql("select month, product, sum(product + 1) over() from windowData order by area"),
+      Seq(
+        (2, 6, 57),
+        (3, 7, 57),
+        (4, 8, 57),
+        (5, 9, 57),
+        (6, 11, 57),
+        (1, 10, 57)
+      ).map(i => Row(i._1, i._2, i._3)))
+
+    checkAnswer(
+      sql(
+        """
+          |select area, rank() over (partition by area order by tmp.month) + tmp.tmp1 as c1
+          |from (select month, area, product as p, 1 as tmp1 from windowData) tmp order by p
+        """.stripMargin),
+      Seq(
+        ("a", 2),
+        ("b", 2),
+        ("b", 3),
+        ("c", 2),
+        ("d", 2),
+        ("c", 3)
+      ).map(i => Row(i._1, i._2)))
+
+    checkAnswer(
+      sql(
+      """
+        |select area, rank() over (partition by area order by month) as c1
+        |from windowData group by product, area, month order by product, area
+      """.stripMargin),
+      Seq(
+        ("a", 1),
+        ("b", 1),
+        ("b", 2),
+        ("c", 1),
+        ("d", 1),
+        ("c", 2)
+      ).map(i => Row(i._1, i._2)))
+  }
+
+  // todo: fix this test case by reimplementing the function ResolveAggregateFunctions
+  ignore("window function: Pushing aggregate Expressions in Sort to Aggregate") {
+    val data = Seq(
+      WindowData(1, "d", 10),
+      WindowData(2, "a", 6),
+      WindowData(3, "b", 7),
+      WindowData(4, "b", 8),
+      WindowData(5, "c", 9),
+      WindowData(6, "c", 11)
+    )
+    sparkContext.parallelize(data).toDF().registerTempTable("windowData")
+
+    checkAnswer(
+      sql(
+        """
+          |select area, sum(product) over () as c from windowData
+          |where product > 3 group by area, product
+          |having avg(month) > 0 order by avg(month), product
+        """.stripMargin),
+      Seq(
+        ("a", 51),
+        ("b", 51),
+        ("b", 51),
+        ("c", 51),
+        ("c", 51),
+        ("d", 51)
+      ).map(i => Row(i._1, i._2)))
+  }
+
   test("window function: multiple window expressions in a single expression") {
     val nums = sparkContext.parallelize(1 to 10).map(x => (x, x % 2)).toDF("x", "y")
     nums.registerTempTable("nums")
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