Github user yhuai commented on a diff in the pull request:
https://github.com/apache/spark/pull/14723#discussion_r75586776
--- Diff:
sql/core/src/test/scala/org/apache/spark/sql/AggregateWithObjectAggregateBufferSuite.scala
---
@@ -0,0 +1,156 @@
+/*
+ * 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
+
+import
org.apache.spark.sql.AggregateWithObjectAggregateBufferSuite.MaxWithObjectAggregateBuffer
+import org.apache.spark.sql.catalyst.InternalRow
+import org.apache.spark.sql.catalyst.expressions.{AttributeReference,
Expression, GenericMutableRow, MutableRow, UnsafeRow}
+import
org.apache.spark.sql.catalyst.expressions.aggregate.{ImperativeAggregate,
WithObjectAggregateBuffer}
+import org.apache.spark.sql.execution.aggregate.{SortAggregateExec}
+import org.apache.spark.sql.functions._
+import org.apache.spark.sql.test.SharedSQLContext
+import org.apache.spark.sql.types.{AbstractDataType, DataType,
IntegerType, StructType}
+
+class AggregateWithObjectAggregateBufferSuite extends QueryTest with
SharedSQLContext {
+
+ import testImplicits._
+
+ private val data = Seq((1, 0), (3, 1), (2, 0), (6, 3), (3, 1), (4, 1),
(5, 0))
+
+
+ test("aggregate with object aggregate buffer, should not use
HashAggregate") {
+ val df = data.toDF("a", "b")
+ val max = new MaxWithObjectAggregateBuffer($"a".expr)
+
+ // Always use SortAggregateExec instead of HashAggregateExec for
planning even if the aggregate
+ // buffer attributes are mutable fields (every field can be mutated
inline like int, long...)
+ val allFieldsMutable =
max.aggBufferSchema.map(_.dataType).forall(UnsafeRow.isMutable)
+ val sparkPlan =
df.select(Column(max.toAggregateExpression())).queryExecution.sparkPlan
+ assert(allFieldsMutable == true &&
sparkPlan.isInstanceOf[SortAggregateExec])
+ }
+
+ test("aggregate with object aggregate buffer, no group by") {
+ val df = data.toDF("a", "b").coalesce(2)
+ checkAnswer(
+ df.select(objectAggregateMax($"a"), count($"a"),
objectAggregateMax($"b"), count($"b")),
+ Seq(Row(6, 7, 3, 7))
+ )
+ }
+
+ test("aggregate with object aggregate buffer, with group by") {
+ val df = data.toDF("a", "b").coalesce(2)
+ checkAnswer(
+ df.groupBy($"b").agg(objectAggregateMax($"a"), count($"a"),
objectAggregateMax($"a")),
+ Seq(
+ Row(0, 5, 3, 5),
+ Row(1, 4, 3, 4),
+ Row(3, 6, 1, 6)
+ )
+ )
+ }
+
+ test("aggregate with object aggregate buffer, empty inputs, no group
by") {
+ val empty = Seq.empty[(Int, Int)].toDF("a", "b")
+ checkAnswer(
+ empty.select(objectAggregateMax($"a"), count($"a"),
objectAggregateMax($"b"), count($"b")),
+ Seq(Row(Int.MinValue, 0, Int.MinValue, 0)))
+ }
+
+ test("aggregate with object aggregate buffer, empty inputs, with group
by") {
+ val empty = Seq.empty[(Int, Int)].toDF("a", "b")
+ checkAnswer(
+ empty.groupBy($"b").agg(objectAggregateMax($"a"), count($"a"),
objectAggregateMax($"a")),
+ Seq.empty[Row])
+ }
+
+ private def objectAggregateMax(column: Column): Column = {
+ val max = MaxWithObjectAggregateBuffer(column.expr)
+ Column(max.toAggregateExpression())
+ }
+}
+
+object AggregateWithObjectAggregateBufferSuite {
--- End diff --
(we do not need to put the example class inside this object.)
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