maropu commented on a change in pull request #27233: [SPARK-29701][SQL] Correct 
behaviours of group analytical queries when empty input given
URL: https://github.com/apache/spark/pull/27233#discussion_r370966784
 
 

 ##########
 File path: 
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/RewriteGroupingAnalyticsWithoutKeys.scala
 ##########
 @@ -0,0 +1,142 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql.catalyst.optimizer
+
+import org.apache.spark.sql.catalyst.expressions.{Alias, Attribute, 
AttributeReference, AttributeSet, Literal, NamedExpression, VirtualColumn}
+import org.apache.spark.sql.catalyst.expressions.aggregate.AggregateExpression
+import org.apache.spark.sql.catalyst.plans.logical._
+import org.apache.spark.sql.catalyst.rules.Rule
+
+/**
+ * In grouping analytics (e.g., `GROUPING SETS`) with an empty grouping set, 
we need to follow
+ * the non-key aggregate semantics; it generates a single row having an 
initial aggregated value
+ * (e.g., 0 for `COUNT`) from an empty input.
+ * For example, a query below must return a row (NULL, NULL, 0) from
+ * an empty input (`empty_input`):
+ *
+ * {{{
+ *   SELECT k1, k2, COUNT(v)
+ *     FROM empty_input t(k1, k2, v)
+ *     GROUP BY GROUPING SETS ((), (k1, k2))
+ * }}}
+ *
+ * To comply with the semantics, this rule rewrites the following (pseudo) 
resolved logical plan
+ * as an union query of aggregates with/without keys as follows:
+ *
+ * {{{
+ *   Aggregate(
+ *     groupingExprs = ['k1, 'k2, 'spark_grouping_id],
+ *     aggregateExprs = ['k1, 'k2, COUNT('v)],
+ *     output = ['k1, 'k2, 'cnt],
+ *     child = Expand(
+ *       projections = [('k1, 'k2, 'v, 0), (null, null, 'v, 3)],
+ *       output = ['k1, 'k2, 'v, 'spark_grouping_id]),
+ *       child = LocalTableScan [...]))
+ * }}}
+ *
+ * It is transformed into an union plan below:
+ *
+ * {{{
+ *   Union([
+ *     Aggregate(
+ *       groupingExprs = ['k1, 'k2, 'spark_grouping_id],
+ *       aggregateExprs = ['k1, 'k2, COUNT('v)],
+ *       output = ['k1, 'k2, 'cnt],
+ *       child = Expand(
+ *         projections = [('k1, 'k2, 'v, 0)],
+ *         output = ['k1, 'k2, 'v, 'spark_grouping_id]),
+ *         child = LocalTableScan [...])),
+ *     Aggregate(
+ *       groupingExprs = [],
+ *       aggregateExprs = [null, null, COUNT('v)],
+ *       output = ['k1, 'k2, 'cnt],
+ *       child = Project(
+ *         projectList = ['v],
+ *         child = LocalTableScan [...]))]
 
 Review comment:
   @viirya Yea, currently yes.
   
   > And, that could be a reason to drop this PR and JIRA completely.
   
   
   @dongjoon-hyun Do you think it is ok to keep the current behaviour?

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