sigmod commented on a change in pull request #34053:
URL: https://github.com/apache/spark/pull/34053#discussion_r714443723
##########
File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/Optimizer.scala
##########
@@ -2122,6 +2125,68 @@ object RewriteIntersectAll extends Rule[LogicalPlan] {
}
}
+/**
+ * Replaces logical [[AsOfJoin]] operator using a combination of Join and
Aggregate operator.
+ *
+ * Input Pseudo-Query:
+ * {{{
+ * SELECT * FROM left ASOF JOIN right ON (condition, as_of on(left.t,
right.t), tolerance)
+ * }}}
+ *
+ * Rewritten Query:
+ * {{{
+ * SELECT left.*, __right__.*
+ * FROM (
+ * SELECT
+ * left.*,
+ * (
+ * SELECT MIN_BY(STRUCT(right.*), left.t - right.t)
+ * FROM right
+ * WHERE condition AND left.t >= right.t AND right.t >=
left.t - tolerance
+ * ) as __right__
+ * FROM left
+ * )
+ * }}}
+ */
+object RewriteAsOfJoin extends Rule[LogicalPlan] {
+ def apply(plan: LogicalPlan): LogicalPlan = plan.transformWithPruning(
+ _.containsPattern(AS_OF_JOIN), ruleId) {
+ case AsOfJoin(left, right, asOfCondition, condition, orderExpression,
joinType) =>
+ val conditionWithOuterReference =
+ condition.map(And(_,
asOfCondition)).getOrElse(asOfCondition).transformUp {
+ case a: AttributeReference if left.outputSet.contains(a) =>
+ OuterReference(a)
+ }
+ val filtered = Filter(conditionWithOuterReference, right)
+
+ val orderExpressionWithOuterReference = orderExpression.transformUp {
+ case a: AttributeReference if left.outputSet.contains(a) =>
+ OuterReference(a)
+ }
+ val rightStruct = CreateStruct(right.output)
+ val nearestRight = MinBy(rightStruct, orderExpressionWithOuterReference)
+ .toAggregateExpression()
+ val aggExpr = Alias(nearestRight, "__nearest_right__")()
+ val aggregate = Aggregate(Seq.empty, Seq(aggExpr), filtered)
+
+ val scalarSubquery = Project(
Review comment:
Nit: projectWithScalarSubquery ?
##########
File path:
sql/core/src/test/scala/org/apache/spark/sql/DataFrameAsOfJoinSuite.scala
##########
@@ -0,0 +1,153 @@
+/*
+ * 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 scala.collection.JavaConverters._
+
+import org.apache.spark.sql.execution.adaptive.AdaptiveSparkPlanHelper
+import org.apache.spark.sql.functions._
+import org.apache.spark.sql.test.SharedSparkSession
+import org.apache.spark.sql.types._
+
+class DataFrameAsOfJoinSuite extends QueryTest
+ with SharedSparkSession
+ with AdaptiveSparkPlanHelper {
+
+ def prepareForAsOfJoin(): (DataFrame, DataFrame) = {
+ val schema1 = StructType(
+ StructField("a", IntegerType, false) ::
+ StructField("b", StringType, false) ::
+ StructField("left_val", StringType, false) :: Nil)
+ val rowSeq1: List[Row] = List(Row(1, "x", "a"), Row(5, "y", "b"), Row(10,
"z", "c"))
+ val df1 = spark.createDataFrame(rowSeq1.asJava, schema1)
+
+ val schema2 = StructType(
+ StructField("a", IntegerType) ::
+ StructField("b", StringType) ::
+ StructField("right_val", IntegerType) :: Nil)
+ val rowSeq2: List[Row] = List(Row(1, "v", 1), Row(2, "w", 2), Row(3, "x",
3),
+ Row(6, "y", 6), Row(7, "z", 7))
+ val df2 = spark.createDataFrame(rowSeq2.asJava, schema2)
+
+ (df1, df2)
+ }
+
+ test("as-of join - simple") {
+ val (df1, df2) = prepareForAsOfJoin()
+ checkAnswer(
+ df1.joinAsOf(
+ df2, df1.col("a"), df2.col("a"), usingColumns = Seq.empty,
+ joinType = "left", tolerance = null, allowExactMatches = true,
direction = "backward"),
+ Seq(
+ Row(1, "x", "a", 1, "v", 1),
+ Row(5, "y", "b", 3, "x", 3),
+ Row(10, "z", "c", 7, "z", 7)
+ )
+ )
+ }
+
+ test("as-of join - usingColumns") {
+ val (df1, df2) = prepareForAsOfJoin()
+ checkAnswer(
+ df1.joinAsOf(df2, df1.col("a"), df2.col("a"), usingColumns = Seq("b"),
+ joinType = "left", tolerance = null, allowExactMatches = true,
direction = "backward"),
+ Seq(
+ Row(1, "x", "a", null, null, null),
+ Row(5, "y", "b", null, null, null),
+ Row(10, "z", "c", 7, "z", 7)
+ )
+ )
+ }
+
+ test("as-of join - usingColumns, inner") {
+ val (df1, df2) = prepareForAsOfJoin()
+ checkAnswer(
+ df1.joinAsOf(df2, df1.col("a"), df2.col("a"), usingColumns = Seq("b"),
+ joinType = "inner", tolerance = null, allowExactMatches = true,
direction = "backward"),
+ Seq(
+ Row(10, "z", "c", 7, "z", 7)
+ )
+ )
+ }
+
+ test("as-of join - tolerance = 1") {
+ val (df1, df2) = prepareForAsOfJoin()
+ checkAnswer(
+ df1.joinAsOf(df2, df1.col("a"), df2.col("a"), usingColumns = Seq.empty,
+ joinType = "left", tolerance = lit(1), allowExactMatches = true,
direction = "backward"),
+ Seq(
+ Row(1, "x", "a", 1, "v", 1),
+ Row(5, "y", "b", null, null, null),
+ Row(10, "z", "c", null, null, null)
+ )
+ )
+ }
+
+ test("as-of join - allowExactMatches = false") {
+ val (df1, df2) = prepareForAsOfJoin()
+ checkAnswer(
+ df1.joinAsOf(df2, df1.col("a"), df2.col("a"), usingColumns = Seq.empty,
+ joinType = "left", tolerance = null, allowExactMatches = false,
direction = "backward"),
+ Seq(
+ Row(1, "x", "a", null, null, null),
Review comment:
In the example, non-matches' numeric columns are NaN?
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