yadavay-amzn commented on code in PR #56101:
URL: https://github.com/apache/spark/pull/56101#discussion_r3472001103
##########
sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala:
##########
@@ -2352,6 +2352,16 @@ object SQLConf {
.booleanConf
.createWithDefault(true)
+ val NEAREST_BY_BROADCAST_ENABLED =
+ buildConf("spark.sql.join.nearestBy.broadcast.enabled")
+ .internal()
+ .doc("When true, NearestByJoin uses a streaming heap operator instead of
the " +
+ "cross-product + aggregate rewrite.")
+ .version("5.0.0")
Review Comment:
Done - set to 4.3.0.
##########
sql/core/src/main/scala/org/apache/spark/sql/execution/joins/BroadcastNearestByJoinExec.scala:
##########
@@ -0,0 +1,166 @@
+/*
+ * 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.execution.joins
+
+import java.util.{Comparator, PriorityQueue => JPriorityQueue}
+
+import org.apache.spark.SparkException
+import org.apache.spark.rdd.RDD
+import org.apache.spark.sql.catalyst.InternalRow
+import org.apache.spark.sql.catalyst.expressions._
+import org.apache.spark.sql.catalyst.plans.{InnerLike, JoinType, LeftOuter,
NearestByDirection, NearestByDistance}
+import org.apache.spark.sql.catalyst.plans.physical._
+import org.apache.spark.sql.catalyst.util.TypeUtils
+import org.apache.spark.sql.execution.{ExplainUtils, SparkPlan}
+import org.apache.spark.sql.execution.metric.SQLMetrics
+
+/**
+ * Heap entry storing an index into the broadcast array alongside its ranking
value.
+ * Using a case class with primitive `Int` field avoids boxing that `(Int,
Any)` tuples incur.
+ */
+private[joins] case class HeapEntry(index: Int, rankingValue: Any)
+
+/**
+ * Physical operator for NearestByJoin that avoids materializing the full
cross product.
+ * For each left row, iterates all broadcast right rows maintaining a bounded
priority
+ * queue of size k, then emits the top-k matches directly.
+ *
+ * The right side is fully broadcast to all partitions. This operator only
fires when
+ * the right side fits within [[SQLConf.AUTO_BROADCASTJOIN_THRESHOLD]]. For
right tables
+ * exceeding this threshold, the existing cross-product + aggregate rewrite is
used as
+ * fallback. Tie-breaking among equal ranking values is non-deterministic
(matches the
+ * existing rewrite behavior).
+ */
+case class BroadcastNearestByJoinExec(
+ left: SparkPlan,
+ right: SparkPlan,
+ joinType: JoinType,
+ numResults: Int,
+ rankingExpression: Expression,
+ direction: NearestByDirection) extends BaseJoinExec {
+
+ override def condition: Option[Expression] = None
+ override def leftKeys: Seq[Expression] = Seq.empty
+ override def rightKeys: Seq[Expression] = Seq.empty
+
+ override def simpleStringWithNodeId(): String = {
+ val opId = ExplainUtils.getOpId(this)
+ s"$nodeName $joinType k=$numResults $direction ($opId)".trim
+ }
+
+ override def output: Seq[Attribute] = joinType match {
+ case _: InnerLike | LeftOuter =>
+ left.output.map(_.withNullability(true)) ++
right.output.map(_.withNullability(true))
+ case other =>
+ throw SparkException.internalError(
+ s"$nodeName does not support join type: $other")
+ }
+
+ override lazy val metrics = Map(
+ "numOutputRows" -> SQLMetrics.createMetric(sparkContext, "number of output
rows"),
+ "streamedRows" -> SQLMetrics.createMetric(sparkContext, "number of left
rows processed"))
+
+ override def requiredChildDistribution: Seq[Distribution] =
+ UnspecifiedDistribution :: BroadcastDistribution(IdentityBroadcastMode) ::
Nil
+
+ override def outputPartitioning: Partitioning = left.outputPartitioning
+
+ override def outputOrdering: Seq[SortOrder] = Nil
+
+ protected override def doExecute(): RDD[InternalRow] = {
+ val broadcastedRight = right.executeBroadcast[Array[InternalRow]]()
+ val numOutput = longMetric("numOutputRows")
+ val streamedRowsMetric = longMetric("streamedRows")
+ val localJoinType = joinType
+ val k = numResults
+ val isDistance = direction == NearestByDistance
+ val leftOutput = left.output
+ val rightOutput = right.output
+ val rankExpr = rankingExpression
+ val allOutput = output
+ val ordering = TypeUtils.getInterpretedOrdering(rankExpr.dataType)
+
+ left.execute().mapPartitionsInternal { leftIter =>
+ val rightRows = broadcastedRight.value
+ if (rightRows.isEmpty && localJoinType != LeftOuter) {
+ Iterator.empty
+ } else {
+ val joinedRow = new JoinedRow
+ val rankingProj = UnsafeProjection.create(
+ Seq(rankExpr), leftOutput ++ rightOutput)
+ val resultProj = UnsafeProjection.create(allOutput, allOutput)
+
+ // Hoist heap outside flatMap to reduce GC pressure
+ val heap = if (isDistance) {
+ new JPriorityQueue[HeapEntry](k + 1,
+ new Comparator[HeapEntry] {
+ override def compare(a: HeapEntry, b: HeapEntry): Int =
+ ordering.compare(b.rankingValue, a.rankingValue)
+ })
+ } else {
+ new JPriorityQueue[HeapEntry](k + 1,
+ new Comparator[HeapEntry] {
+ override def compare(a: HeapEntry, b: HeapEntry): Int =
+ ordering.compare(a.rankingValue, b.rankingValue)
+ })
+ }
+
+ leftIter.flatMap { leftRow =>
+ streamedRowsMetric += 1
+ heap.clear()
+
+ var i = 0
+ while (i < rightRows.length) {
+ val rightRow = rightRows(i)
+ joinedRow(leftRow, rightRow)
+ val rankingRow = rankingProj(joinedRow).copy()
Review Comment:
Done. The copy now happens only for variable-length ranking types: gated on
`!UnsafeRow.isFixedLength(rankExpr.dataType)` (precomputed once), so
fixed-width types (numeric, Date/Timestamp, small Decimal) extract an immutable
value with no per-pair copy, while variable-length types
(String/Binary/struct/array/map, and Decimal with precision > 18) copy the
single-column row to detach it from the reused buffer. The String and
Decimal(19) retain tests cover the variable-length path.
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