SNOW-1668981: Update is wrong when source is anti-join

Please answer these questions before submitting your issue. Thanks!

1. What version of Python are you using?

   Python 3.11.6 (tags/v3.11.6:8b6ee5b, Oct 2 2023, 14:57:12) [MSC v.1935 64 bit (AMD64)]

2. What operating system and processor architecture are you using?

   Windows-10-10.0.22631-SP0

3. What are the component versions in the environment (pip freeze)?

   pandas==2.2.2
   snowflake-snowpark-python==1.22.1

4. What did you do?

from snowflake.snowpark import Session
from snowflake.snowpark.functions import lit

mock_session = Session.builder.config("local_testing", True).create()
test_data = mock_session.create_dataframe(pd.DataFrame({"a": [1, 2]}))

df1 = mock_session.create_dataframe(pd.DataFrame({"A": [0, 1], "B": ['a', 'b']}))
df2 = mock_session.create_dataframe(pd.DataFrame({"A": [0, 1], "B": ['a', 'c']}))

anti = df1.join(df2, on=["A", "B"], how="anti")
anti.show()  # Has only 1 row

# This update should only update 1 row in df1
result = df1.update(
    assignments={"B": lit("f")},
    condition=(df1["A"] == anti["A"]) & (df1["B"] == anti["B"]),
    source=anti,
)

print(result)  # UpdateResult(rows_updated=2, multi_joined_rows_updated=0)
mock_session.table(df1.table_name).show()  # Two rows are updated

5. What did you expect to see?

   The updated table should have only 1 updated row. Instead, both rows are updated.