[SPARK-29708][SQL][2.4] Correct aggregated values when grouping sets …

…are duplicated

### What changes were proposed in this pull request?

This pr intends to fix wrong aggregated values in `GROUPING SETS` when there are duplicated grouping sets in a query (e.g., `GROUPING SETS ((k1),(k1))`).

For example;
```
scala> spark.table("t").show()
+---+---+---+
| k1| k2|  v|
+---+---+---+
|  0|  0|  3|
+---+---+---+

scala> sql("""select grouping_id(), k1, k2, sum(v) from t group by grouping sets ((k1),(k1,k2),(k2,k1),(k1,k2))""").show()
+-------------+---+----+------+
|grouping_id()| k1|  k2|sum(v)|
+-------------+---+----+------+
|            0|  0|   0|     9| <---- wrong aggregate value and the correct answer is `3`
|            1|  0|null|     3|
+-------------+---+----+------+

// PostgreSQL case
postgres=#  select k1, k2, sum(v) from t group by grouping sets ((k1),(k1,k2),(k2,k1),(k1,k2));
 k1 |  k2  | sum
----+------+-----
  0 |    0 |   3
  0 |    0 |   3
  0 |    0 |   3
  0 | NULL |   3
(4 rows)

// Hive case
hive> select GROUPING__ID, k1, k2, sum(v) from t group by k1, k2 grouping sets ((k1),(k1,k2),(k2,k1),(k1,k2));
1	0	NULL	3
0	0	0	3
```
[MS SQL Server has the same behaviour with PostgreSQL](#26961 (comment)). This pr follows the behaviour of PostgreSQL/SQL server; it adds one more virtual attribute in `Expand` for avoiding wrongly grouping rows with the same grouping ID.

This is the #26961 backport  for `branch-2.4`

### Why are the changes needed?

To fix bugs.

### Does this PR introduce any user-facing change?

No.

### How was this patch tested?

The existing tests.

Closes #27229 from maropu/SPARK-29708-BRANCHC2.4.

Authored-by: Takeshi Yamamuro <yamamuro@apache.org>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/basicLogicalOperators.scala

@@ -670,11 +670,14 @@ object Expand {
     child: LogicalPlan): Expand = {
     val attrMap = groupByAttrs.zipWithIndex.toMap
 
+    val hasDuplicateGroupingSets = groupingSetsAttrs.size !=
+      groupingSetsAttrs.map(_.map(_.exprId).toSet).distinct.size
+
     // Create an array of Projections for the child projection, and replace the projections'
     // expressions which equal GroupBy expressions with Literal(null), if those expressions
     // are not set for this grouping set.
-    val projections = groupingSetsAttrs.map { groupingSetAttrs =>
-      child.output ++ groupByAttrs.map { attr =>
+    val projections = groupingSetsAttrs.zipWithIndex.map { case (groupingSetAttrs, i) =>
+      val projAttrs = child.output ++ groupByAttrs.map { attr =>
         if (!groupingSetAttrs.contains(attr)) {
           // if the input attribute in the Invalid Grouping Expression set of for this group
           // replace it with constant null
@@ -684,11 +687,25 @@ object Expand {
         }
       // groupingId is the last output, here we use the bit mask as the concrete value for it.
       } :+ Literal.create(buildBitmask(groupingSetAttrs, attrMap), IntegerType)
+
+      if (hasDuplicateGroupingSets) {
+        // If `groupingSetsAttrs` has duplicate entries (e.g., GROUPING SETS ((key), (key))),
+        // we add one more virtual grouping attribute (`_gen_grouping_pos`) to avoid
+        // wrongly grouping rows with the same grouping ID.
+        projAttrs :+ Literal.create(i, IntegerType)
+      } else {
+        projAttrs
+      }
     }
 
     // the `groupByAttrs` has different meaning in `Expand.output`, it could be the original
     // grouping expression or null, so here we create new instance of it.
-    val output = child.output ++ groupByAttrs.map(_.newInstance) :+ gid
+    val output = if (hasDuplicateGroupingSets) {
+      val gpos = AttributeReference("_gen_grouping_pos", IntegerType, false)()
+      child.output ++ groupByAttrs.map(_.newInstance) :+ gid :+ gpos
+    } else {
+      child.output ++ groupByAttrs.map(_.newInstance) :+ gid
+    }
     Expand(projections, output, Project(child.output ++ groupByAliases, child))
   }
 }

sql/core/src/test/resources/sql-tests/inputs/grouping_set.sql

@@ -51,3 +51,9 @@ SELECT a, b, c, count(d) FROM grouping GROUP BY WITH CUBE;
 
 SELECT c1 FROM (values (1,2), (3,2)) t(c1, c2) GROUP BY GROUPING SETS (());
 
+-- duplicate entries in grouping sets
+SELECT k1, k2, avg(v) FROM (VALUES (1,1,1),(2,2,2)) AS t(k1,k2,v) GROUP BY GROUPING SETS ((k1),(k1,k2),(k2,k1));
+
+SELECT grouping__id, k1, k2, avg(v) FROM (VALUES (1,1,1),(2,2,2)) AS t(k1,k2,v) GROUP BY GROUPING SETS ((k1),(k1,k2),(k2,k1));
+
+SELECT grouping(k1), k1, k2, avg(v) FROM (VALUES (1,1,1),(2,2,2)) AS t(k1,k2,v) GROUP BY GROUPING SETS ((k1),(k1,k2),(k2,k1));

sql/core/src/test/resources/sql-tests/results/grouping_set.sql.out

@@ -1,5 +1,5 @@
 -- Automatically generated by SQLQueryTestSuite
--- Number of queries: 15
+-- Number of queries: 18
 
 
 -- !query 0
@@ -110,8 +110,10 @@ SELECT a + b, b, sum(c) FROM (VALUES (1,1,1),(2,2,2)) AS t(a,b,c) GROUP BY GROUP
 -- !query 10 schema
 struct<(a + b):int,b:int,sum(c):bigint>
 -- !query 10 output
-2	NULL	2
-4	NULL	4
+2	NULL	1
+2	NULL	1
+4	NULL	2
+4	NULL	2
 NULL	1	1
 NULL	2	2
 
@@ -164,3 +166,42 @@ struct<>
 -- !query 14 output
 org.apache.spark.sql.AnalysisException
 expression '`c1`' is neither present in the group by, nor is it an aggregate function. Add to group by or wrap in first() (or first_value) if you don't care which value you get.;
+
+
+-- !query 15
+SELECT k1, k2, avg(v) FROM (VALUES (1,1,1),(2,2,2)) AS t(k1,k2,v) GROUP BY GROUPING SETS ((k1),(k1,k2),(k2,k1))
+-- !query 15 schema
+struct<k1:int,k2:int,avg(v):double>
+-- !query 15 output
+1	1	1.0
+1	1	1.0
+1	NULL	1.0
+2	2	2.0
+2	2	2.0
+2	NULL	2.0
+
+
+-- !query 16
+SELECT grouping__id, k1, k2, avg(v) FROM (VALUES (1,1,1),(2,2,2)) AS t(k1,k2,v) GROUP BY GROUPING SETS ((k1),(k1,k2),(k2,k1))
+-- !query 16 schema
+struct<grouping__id:int,k1:int,k2:int,avg(v):double>
+-- !query 16 output
+0	1	1	1.0
+0	1	1	1.0
+0	2	2	2.0
+0	2	2	2.0
+1	1	NULL	1.0
+1	2	NULL	2.0
+
+
+-- !query 17
+SELECT grouping(k1), k1, k2, avg(v) FROM (VALUES (1,1,1),(2,2,2)) AS t(k1,k2,v) GROUP BY GROUPING SETS ((k1),(k1,k2),(k2,k1))
+-- !query 17 schema
+struct<grouping(k1):tinyint,k1:int,k2:int,avg(v):double>
+-- !query 17 output
+0	1	1	1.0
+0	1	1	1.0
+0	1	NULL	1.0
+0	2	2	2.0
+0	2	2	2.0
+0	2	NULL	2.0