aokolnychyi commented on a change in pull request #4047:
URL: https://github.com/apache/iceberg/pull/4047#discussion_r807302964
##########
File path:
spark/v3.2/spark-extensions/src/main/scala/org/apache/spark/sql/catalyst/analysis/RewriteMergeIntoTable.scala
##########
@@ -226,6 +231,82 @@ object RewriteMergeIntoTable extends
RewriteRowLevelCommand {
ReplaceData(writeRelation, mergeRows, relation)
}
+ // build a rewrite plan for sources that support row deltas
+ private def buildWriteDeltaPlan(
+ relation: DataSourceV2Relation,
+ operationTable: RowLevelOperationTable,
+ source: LogicalPlan,
+ cond: Expression,
+ matchedActions: Seq[MergeAction],
+ notMatchedActions: Seq[MergeAction]): WriteDelta = {
+
+ // resolve all needed attrs (e.g. row ID and any required metadata attrs)
+ val rowAttrs = relation.output
+ val rowIdAttrs = resolveRowIdAttrs(relation, operationTable.operation)
+ val metadataAttrs = resolveRequiredMetadataAttrs(relation,
operationTable.operation)
+
+ // construct a scan relation and include all required metadata columns
+ val readRelation = buildReadRelation(relation, operationTable,
metadataAttrs, rowIdAttrs)
+ val readAttrs = readRelation.output
+
+ // project an extra column to check if a target row exists after the join
+ val targetTableProjExprs = readAttrs :+ Alias(TrueLiteral,
ROW_FROM_TARGET)()
+ val targetTableProj = Project(targetTableProjExprs, readRelation)
+
+ // project an extra column to check if a source row exists after the join
+ val sourceTableProjExprs = source.output :+ Alias(TrueLiteral,
ROW_FROM_SOURCE)()
+ val sourceTableProj = Project(sourceTableProjExprs, source)
+
+ // use inner join if there is no NOT MATCHED action, unmatched source rows
can be discarded
+ // use right outer join in all other cases, unmatched source rows may be
needed
+ // also disable broadcasts for the target table to perform the cardinality
check later
Review comment:
Removed "later" for consistency in comments. The comments in
copy-on-write and merge-on-read are slightly different as different join type
are used. I'll take a look at what extra methods we can introduce to simplify
this. I did that in a few places already.
##########
File path:
spark/v3.2/spark/src/test/java/org/apache/iceberg/spark/TestSparkDistributionAndOrderingUtil.java
##########
@@ -1567,6 +1567,370 @@ public void
testRangePositionDeltaUpdatePartitionedTable() {
table, UPDATE, expectedDistribution,
SPEC_ID_PARTITION_FILE_POSITION_ORDERING);
}
+ //
==================================================================================
+ // Distribution and ordering for merge-on-read MERGE operations with
position deletes
+ //
==================================================================================
+ //
+ // UNPARTITIONED UNORDERED
+ // -------------------------------------------------------------------------
+ // merge mode is NOT SET -> rely on write distribution and ordering as a
basis
+ // merge mode is NONE -> unspecified distribution + LOCALLY ORDER BY
_spec_id, _partition, _file, _pos
+ // merge mode is HASH -> unspecified distribution + LOCALLY ORDER BY
_spec_id, _partition, _file, _pos
+ // merge mode is RANGE -> unspecified distribution + LOCALLY ORDER BY
_spec_id, _partition, _file, _pos
+ //
+ // UNPARTITIONED ORDERED BY id, data
+ // -------------------------------------------------------------------------
+ // merge mode is NOT SET -> rely on write distribution and ordering as a
basis
+ // merge mode is NONE -> unspecified distribution +
+ // LOCALLY ORDER BY _spec_id, _partition, _file, _pos,
id, data
Review comment:
Added a comment.
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