mdwint commented on code in PR #2429:
URL: https://github.com/apache/iceberg-python/pull/2429#discussion_r2375985658
##########
pyiceberg/table/upsert_util.py:
##########
@@ -14,38 +14,61 @@
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
-import functools
-import operator
+from math import isnan
+from typing import Any
import pyarrow as pa
from pyarrow import Table as pyarrow_table
from pyarrow import compute as pc
from pyiceberg.expressions import (
AlwaysFalse,
+ And,
BooleanExpression,
EqualTo,
In,
+ IsNaN,
+ IsNull,
Or,
)
def create_match_filter(df: pyarrow_table, join_cols: list[str]) ->
BooleanExpression:
Review Comment:
Thinking through this some more, I ask myself: What _should_ the semantics
of `upsert` be? Should it use `=` or `<=>` to test equality? For my use case
`<=>` is right, and I also find it most intuitive, but does that mean it should
be the default?
I see several options:
- Make `<=>` the default. Users who don't want to update nulls can filter
them out themselves before calling `upsert`. The status quo is crashing, so
there are no existing users expecting a different behaviour.
- Make `=` the default. This means I can't achieve my goal, and I'll need to
reimplement `upsert` myself. It also means new rows will be inserted for every
row containing null in the join columns. This is unintuitive to me, but who
knows someone might want it?
- Add an argument to `upsert` to select the comparison operator. Maximum
flexibility, more work to implement.
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