omkenge commented on code in PR #1693:
URL: https://github.com/apache/iceberg-python/pull/1693#discussion_r1965130816
##########
pyiceberg/table/upsert_util.py:
##########
@@ -36,7 +37,17 @@ def create_match_filter(df: pyarrow_table, join_cols:
list[str]) -> BooleanExpre
if len(join_cols) == 1:
return In(join_cols[0], unique_keys[0].to_pylist())
else:
- return Or(*[And(*[EqualTo(col, row[col]) for col in join_cols]) for
row in unique_keys.to_pylist()])
+ filters: List[BooleanExpression] = [
+ cast(BooleanExpression, And(*[EqualTo(col, row[col]) for col in
join_cols])) for row in unique_keys.to_pylist()
+ ]
+
+ if not filters:
+ return In(join_cols[0], [])
+
+ if len(filters) == 1:
+ return filters[0]
+
+ return functools.reduce(lambda a, b: Or(a, b), filters)
Review Comment:
I think , Returning In(join_cols[0], []) is correct because it results in a
predicate that is always false, so no target row matches the update condition.
Returning AlwaysTrue() would be wrong because it would match every row in
the target, causing an unintended update of all rows.
What do you thing?
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