Error when upserting and updating dataframes with dictionary encoded columns
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Assessment
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Newbie friendliness
- 50/100
Research direction
Start by reproducing the issue with pyarrow.read_table(read_dictionary=[string_columns]) and a table loaded from catalog.load_table(table_name). Compare table.append(df), table.upsert(df, join_cols=[primary_keys]), and table.update(df, join_cols=[primary_keys]); done means upsert and update handle dictionary-encoded columns without the reported Invalid Type Dictionary error.
Written by the indexing model from the issue text.
Description
Apache Iceberg version
0.9.1
Please describe the bug 🐞
df = pyarrow.read_table(read_dictionary=[string_columns])
table = catalog.load_table(table_name)
table.append(df) -> 'append' casts dictionary columns into large string and table appended without any error
table.upsert(df, join_cols=[primary_keys]) -> Error (Invalid Type Dictionary)
table.update(df, join_cols=[primary_keys]) -> Error (Invalid Type Dictionary)
Willingness to contribute
- I can contribute a fix for this bug independently
- I would be willing to contribute a fix for this bug with guidance from the Iceberg community
- I cannot contribute a fix for this bug at this time
- Dominant language
- Python
- Stars
- 1.1k
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- Avg merge
- 2d 4h
- Merged PRs (30d)
- 72
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