JingsongLi commented on code in PR #8252:
URL: https://github.com/apache/paimon/pull/8252#discussion_r3457409791
##########
paimon-spark/paimon-spark-common/src/main/scala/org/apache/paimon/spark/execution/PaimonStrategy.scala:
##########
@@ -215,3 +238,262 @@ case class PaimonStrategy(spark: SparkSession)
SparkShimLoader.shim.classicApi.recacheByPlan(spark, v2Relation)
}
}
+
+case class LateralVectorSearchExec(
+ innerTable: InnerTable,
+ columnName: String,
+ queryVectorExpr: Expression,
+ limit: Int,
+ options: Map[String, String],
+ vectorSearchOutput: Seq[Attribute],
+ projectList: Seq[NamedExpression],
+ projectOutput: Seq[Attribute],
+ child: SparkPlan)
+ extends SparkPlan {
+
+ override def children: Seq[SparkPlan] = Seq(child)
+
+ override def output: Seq[Attribute] = child.output ++ projectOutput
+
+ @transient override lazy val producedAttributes: AttributeSet =
AttributeSet(vectorSearchOutput)
+
+ @transient
+ override lazy val references: AttributeSet = {
+ AttributeSet.fromAttributeSets(expressions.map(_.references)) --
producedAttributes
+ }
+
+ override protected def withNewChildrenInternal(newChildren:
IndexedSeq[SparkPlan]): SparkPlan = {
+ copy(child = newChildren.head)
+ }
+
+ override protected def doExecute(): RDD[InternalRow] = {
+ child.execute().mapPartitions {
+ outerRows =>
+ val strippedQueryExpr = queryVectorExpr.transform {
+ case OuterReference(namedExpression) => namedExpression.toAttribute
+ }
+ val queryVectorProjection =
UnsafeProjection.create(Seq(strippedQueryExpr), child.output)
+ val rightProjection = UnsafeProjection.create(projectList,
vectorSearchOutput)
+ val joinedRow = new JoinedRow
+ lazy val searchContext = createSearchContext(rightProjection)
+ val batchSize = searchContext.batchSize
+
+ outerRows.map(_.copy()).grouped(batchSize).flatMap {
+ outerRowBatch =>
+ val searchBatch = ArrayBuffer[LateralVectorSearchQuery]()
+ outerRowBatch.foreach {
+ outerRow =>
+ toFloatArray(queryVectorProjection(outerRow).get(0,
strippedQueryExpr.dataType))
+ .foreach(
+ queryVector => searchBatch +=
LateralVectorSearchQuery(outerRow, queryVector))
+ }
+
+ if (searchBatch.isEmpty) {
+ Iterator.empty
+ } else {
+ search(searchBatch.toVector, searchContext).map {
+ case (outerRow, rightRow) =>
+ joinedRow(outerRow, rightRow)
+ joinedRow.copy()
+ }
+ }
+ }
+ }
+ }
+
+ private def createSearchContext(rightProjection: UnsafeProjection):
LateralVectorSearchContext = {
+ val rowType = innerTable.rowType()
+ val readFieldNames = vectorSearchOutput
+ .filterNot(_.name == PaimonMetadataColumn.SEARCH_SCORE_COLUMN)
+ .map(_.name)
+ val readFieldNamesWithRowId =
+ if (readFieldNames.contains(SpecialFields.ROW_ID.name())) {
+ readFieldNames
+ } else {
+ readFieldNames :+ SpecialFields.ROW_ID.name()
+ }
+ val rowTypeWithRowId = SpecialFields.rowTypeWithRowId(rowType)
+ val readRowType = rowType.project(readFieldNames.asJava)
+ val readRowTypeWithRowId = SpecialFields.rowTypeWithRowId(readRowType)
+ val readBuilder = innerTable
+ .newReadBuilder()
+ .withReadType(rowTypeWithRowId.project(readFieldNamesWithRowId.asJava))
+ val scoreMetadataColumns =
+ if (vectorSearchOutput.exists(_.name ==
PaimonMetadataColumn.SEARCH_SCORE_COLUMN)) {
+ Seq(PaimonMetadataColumn.SEARCH_SCORE)
+ } else {
+ Seq.empty
+ }
+ val resultRowType =
+ if (scoreMetadataColumns.isEmpty) {
+ readRowTypeWithRowId
+ } else {
+ new RowType(
+ (readRowTypeWithRowId.getFields.asScala ++ scoreMetadataColumns.map(
+ _.toPaimonDataField)).asJava)
+ }
+ val sparkRow = SparkInternalRow.create(resultRowType)
+ val vectorSearchBuilder = innerTable
Review Comment:
Normal Spark `vector_search` scans apply pushed partition/data filters
before top-k (`PaimonBaseScan.evalVectorSearch` passes
`pushedPartitionFilters`/`pushedDataFilters` into the builder). This lateral
executor builds the `BatchVectorSearchBuilder` here without carrying predicates
from the search side; `PushDownLateralVectorSearchFilter` only pushes
predicates that reference the left child, so predicates on `r.dt` or other
searched-table columns stay above `LateralVectorSearch`. A query like `... JOIN
LATERAL (...) r WHERE r.dt = '20260420'` will pick topK over all partitions and
then filter the joined rows, which can return fewer or wrong rows compared with
non-lateral `vector_search(...) WHERE dt = ...`. Please preserve search-side
filters and apply them via `withPartitionFilter`/`withFilter` before
`newVectorScan()`/`readBatch()`, or reject such predicates explicitly.
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