bart-samwel commented on a change in pull request #23388: [SPARK-26448][SQL] 
retain the difference between 0.0 and -0.0
URL: https://github.com/apache/spark/pull/23388#discussion_r245771144
 
 

 ##########
 File path: 
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/NormalizeFloatingNumbers.scala
 ##########
 @@ -0,0 +1,184 @@
+/*
+ * 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, And, ArrayTransform, 
CreateArray, CreateMap, CreateNamedStruct, CreateNamedStructUnsafe, 
CreateStruct, EqualTo, ExpectsInputTypes, Expression, GetStructField, 
LambdaFunction, NamedLambdaVariable, UnaryExpression}
+import org.apache.spark.sql.catalyst.expressions.codegen.{CodegenContext, 
ExprCode}
+import org.apache.spark.sql.catalyst.planning.ExtractEquiJoinKeys
+import org.apache.spark.sql.catalyst.plans.logical.{LogicalPlan, Subquery, 
Window}
+import org.apache.spark.sql.catalyst.rules.Rule
+import org.apache.spark.sql.types._
+
+/**
+ * We need to take care of special floating numbers (NaN and -0.0) in several 
places:
+ *   1. When compare values, different NaNs should be treated as same, `-0.0` 
and `0.0` should be
+ *      treated as same.
+ *   2. In GROUP BY, different NaNs should belong to the same group, -0.0 and 
0.0 should belong
+ *      to the same group.
+ *   3. In join keys, different NaNs should be treated as same, `-0.0` and 
`0.0` should be
+ *      treated as same.
+ *   4. In window partition keys, different NaNs should be treated as same, 
`-0.0` and `0.0`
+ *      should be treated as same.
+ *
+ * Case 1 is fine, as we handle NaN and -0.0 well during comparison. For 
complex types, we
+ * recursively compare the fields/elements, so it's also fine.
+ *
+ * Case 2, 3 and 4 are problematic, as they compare `UnsafeRow` binary 
directly, and different
+ * NaNs have different binary representation, and the same thing happens for 
-0.0 and 0.0.
+ *
+ * This rule normalizes NaN and -0.0 in Window partition keys, Join keys and 
Aggregate grouping
+ * expressions.
+ *
+ * Note that, this rule should be an analyzer rule, as it must be applied to 
make the query result
 
 Review comment:
   This reads as if the code is wrong. But it is not. The fact that we have to 
do this normalization for joins at least is not something that needs to be an 
analyzer rule for query correctness. Without the normalization the join query 
is perfectly fine if we execute it as a cross product with a filter applied as 
a post-join condition. In this case the requirement for normalization is an 
artifact of the fact that we use a shortcut for executing the join (binary 
comparison, sometimes hashing) which doesn't have the correct semantics for 
comparison. On the other hand for aggregation and window function partitioning 
the normalization is required for correctness.

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