dongjoon-hyun commented on code in PR #55518:
URL: https://github.com/apache/spark/pull/55518#discussion_r3192418867
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sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/RewriteUpdateTable.scala:
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@@ -106,38 +104,92 @@ object RewriteUpdateTable extends RewriteRowLevelCommand {
val remainingRowsPlan = addOperationColumn(COPY_OPERATION,
Filter(remainingRowFilter, readRelation))
- // the new state is a union of updated and copied over records
- val query = Union(updatedRowsPlan, remainingRowsPlan)
+ val updatedAndRemainingRowsPlan = Union(updatedRowsPlan, remainingRowsPlan)
- // build a plan to replace read groups in the table
val writeRelation = relation.copy(table = operationTable)
- val projections = buildReplaceDataProjections(query, relation.output,
metadataAttrs)
+ val query = updatedAndRemainingRowsPlan
+ val metadataAttrs = resolveRequiredMetadataAttrs(relation,
operationTable.operation)
+ val projections = buildReplaceDataProjections(query, rowAttrs,
metadataAttrs)
val groupFilterCond = if (groupFilterEnabled) Some(cond) else None
ReplaceData(writeRelation, cond, query, relation, projections,
groupFilterCond)
}
+ // Common read-relation setup shared by both CoW plan builders.
+ //
+ // When the connector supports column updates and declares required data
attributes,
+ // the read relation is narrowed at analysis time so that
+ // GroupBasedRowLevelOperationScanPlanning uses only the needed columns for
the scan.
+ // Otherwise the full relation output is used.
+ private def buildCoWReadSetup(
+ relation: DataSourceV2Relation,
+ operationTable: RowLevelOperationTable,
+ assignments: Seq[Assignment],
+ cond: Expression): (DataSourceV2Relation, Seq[Attribute]) = {
+
+ val operation = operationTable.operation
+ val metadataAttrs = resolveRequiredMetadataAttrs(relation, operation)
+ val connectorDataAttrs = resolveRequiredDataAttrs(relation, operation)
+ val isNarrow = operation.supportsColumnUpdates() &&
connectorDataAttrs.nonEmpty
+
+ // CoW scan narrowing must be done manually at analysis time.
+ // GroupBasedRowLevelOperationScanPlanning (an optimizer rule that fires
after analysis)
+ // always reads relation.output directly when building the physical scan
-- it does not
+ // observe Project nodes above the relation, so optimizer-driven column
pruning has no
+ // effect on CoW scans. We narrow DataSourceV2Relation.output here so
that rule picks
+ // up the narrow set.
+ val readRelation = if (isNarrow) {
+ val allRequired = (connectorDataAttrs ++
computeAssignedAttrs(assignments)).distinct
+ buildRelationWithAttrs(relation, operationTable, metadataAttrs,
dataAttrs = allRequired,
+ cond = cond)
+ } else {
+ buildRelationWithAttrs(relation, operationTable, metadataAttrs)
+ }
+
+ // CoW write schema (two paths only, no heuristic for CoW):
+ // - Narrow path (connectorDataAttrs declared): exactly connector-declared
cols in declared
+ // order. The connector must declare ALL columns it wants to receive.
+ // - Full path (connectorDataAttrs empty OR supportsColumnUpdates=false):
full table output.
+ // Unlike MOR, CoW does not have a heuristic assigned-only path because
+ // GroupBasedRowLevelOperationScanPlanning needs explicit column
declarations to narrow.
+ val rowAttrs: Seq[Attribute] = if (isNarrow) connectorDataAttrs else
relation.output
+
+ (readRelation, rowAttrs)
+ }
+
// this method assumes the assignments have been already aligned before
+ //
+ // Works for both the full-scan and narrow-scan CoW paths. In the narrow
case,
+ // readRelation.output is already restricted by buildCoWReadSetup, so
projecting
+ // all plan.output gives the correct narrow write schema.
Review Comment:
Use function description style.
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