mattmartin14 commented on PR #1665:
URL: https://github.com/apache/iceberg-python/pull/1665#issuecomment-2661420332

   > actually this doesnt respect 
[`identifier_field_ids`](https://iceberg.apache.org/spec/#identifier-field-ids) 
columns' uniqueness
   > 
   > 
   > 
   > For example, 
   > 
   > ```python
   > 
   > def test_upsert_with_identifier_fields(catalog: Catalog) -> None:
   > 
   >     identifier = "default.test_upsert_with_identifier_fields"
   > 
   >     _drop_table(catalog, identifier)
   > 
   > 
   > 
   >     schema = Schema(
   > 
   >         NestedField(1, "city", StringType(), required=True),
   > 
   >         NestedField(2, "inhabitants", IntegerType(), required=True),
   > 
   >         # Mark City as the identifier field, also known as the primary-key
   > 
   >         identifier_field_ids=[1],
   > 
   >     )
   > 
   > 
   > 
   >     tbl = catalog.create_table(identifier, schema=schema)
   > 
   > 
   > 
   >     arrow_schema = pa.schema(
   > 
   >         [
   > 
   >             pa.field("city", pa.string(), nullable=False),
   > 
   >             pa.field("inhabitants", pa.int32(), nullable=False),
   > 
   >         ]
   > 
   >     )
   > 
   > 
   > 
   >     # Write some data
   > 
   >     df = pa.Table.from_pylist(
   > 
   >         [
   > 
   >             {"city": "Amsterdam", "inhabitants": 921402},
   > 
   >             {"city": "San Francisco", "inhabitants": 808988},
   > 
   >             {"city": "Drachten", "inhabitants": 45019},
   > 
   >             {"city": "Paris", "inhabitants": 2103000},
   > 
   >         ],
   > 
   >         schema=arrow_schema,
   > 
   >     )
   > 
   >     tbl.append(df)
   > 
   > 
   > 
   >     df = pa.Table.from_pylist(
   > 
   >         [
   > 
   >             {"city": "Paris", "inhabitants": 921402},
   > 
   >         ],
   > 
   >         schema=arrow_schema,
   > 
   >     )
   > 
   >     upd = tbl.upsert(df, join_cols=["inhabitants"], 
when_not_matched_insert_all=True)
   > 
   > 
   > 
   >     print(tbl.scan().to_pandas())
   > 
   > ```
   
   @kevinjqliu ,
   
   Not to sound blunt but the example above seems odd TBH. If I understand 
correctly, inhabitants is analogous to population count for a city. Thus, the 
join column should be city, not inhabitants. City identifies the unique record. 
Inhabitants is just an attribute of that record.
   
   


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