peter-toth commented on code in PR #5331:
URL: https://github.com/apache/datafusion-comet/pull/5331#discussion_r3786195845
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spark/src/main/scala/org/apache/comet/serde/operator/CometIcebergNativeScan.scala:
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@@ -859,6 +859,49 @@ object CometIcebergNativeScan extends
CometOperatorSerde[CometBatchScanExec] wit
Some(builder.setIcebergScan(icebergScanBuilder).build())
}
+ /**
+ * The part of an Iceberg-reported sort order that the native per-partition
merge can honour, or
+ * Nil when the merge must stay off. Two callers use this one gate: the
proto serialization
+ * (which turns on the native SortPreservingMergeExec) and
+ * CometIcebergNativeScanExec.outputOrdering (which tells Spark the scan is
sorted). Sharing the
+ * gate means the two always agree.
+ *
+ * v1 accepts only identity sort fields on top-level columns that are in the
projection. Each
+ * SortOrder child must be an AttributeReference in `output`, and must
serialize to proto.
+ * Transform sort fields (bucket/truncate/...) are not AttributeReferences,
so they fall through
+ * to Nil and we read unordered. Checking exprToProto here, not just in the
proto path, keeps
+ * the two callers in step: outputOrdering never advertises an order the
proto path would drop.
+ *
+ * We trust Iceberg on file-level sortedness. If it reports an ordering,
SortOrderAnalyzer has
+ * already checked each file's sort_order_id matches the table order, so
every file is sorted.
+ *
+ * We read scanExec.ordering (the raw reported order), not
scanExec.outputOrdering. Spark blanks
+ * outputOrdering when a partition holds more than one file -- the case this
merge handles.
Review Comment:
Seems good to me, `scanExec.ordering` is the reported by the source and
that's what we need to keep k-way merge if possible, and return as
`scanExec.outputOrdering` so as Spark can use it to elimiate sorts.
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