[jira] [Created] (ARROW-13798) [Python] Selective projection of struct fields errors with use_legacy_dataset = False

["Mark Grey (Jira)" <ji...@apache.org>]

Mark Grey created ARROW-13798:
---------------------------------

             Summary: [Python] Selective projection of struct fields errors with use_legacy_dataset = False
                 Key: ARROW-13798
                 URL: https://issues.apache.org/jira/browse/ARROW-13798
             Project: Apache Arrow
          Issue Type: Bug
          Components: Parquet, Python
    Affects Versions: 5.0.0
         Environment: Python 3.6.9

            Reporter: Mark Grey


Selectively projecting fields from within a struct when reading from parquet files triggers an {{ArrowInvalid}} error when using the new dataset api ({{use_legacy_dataset=False}}).  Passing {{use_legacy_dataset=True}} yields the expected behavior: loading only the columns enumerated in the {{columns}} argument, recursing into structs if there is a {{.}} delimeter in the field name.

Using the following test table:
{code:python}
df = pd.DataFrame({
    'user_id': ['abc123', 'qrs456'],
    'interaction': [{'type': 'click', 'element': 'button'}, {'type':'scroll', 'element': 'window'}]
})

table = pa.Table.from_pandas(df)

pq.write_table(table, '/'.join([out_path, 'example.parquet']))
{code}
Using the current default datasets API:
{code:python}
table_latest = pq.read_table('example.parquet', columns = ['user_id', 'interaction.type'])
{code}
yields:
{noformat}
---------------------------------------------------------------------------
ArrowInvalid                              Traceback (most recent call last)
<ipython-input-25-982ca2d96075> in <module>
----> 1 table_latest = pq.read_table('/'.join([out_path, 'example.parquet']), columns = ['user_id', 'interaction.type'], filesystem = fs)
      2 table_latest

/usr/local/share/sciencebox/venv/lib/python3.6/site-packages/pyarrow/parquet.py in read_table(source, columns, use_threads, metadata, use_pandas_metadata, memory_map, read_dictionary, filesystem, filters, buffer_size, partitioning, use_legacy_dataset, ignore_prefixes, pre_buffer, coerce_int96_timestamp_unit)
   1894 
   1895         return dataset.read(columns=columns, use_threads=use_threads,
-> 1896                             use_pandas_metadata=use_pandas_metadata)
   1897 
   1898     if ignore_prefixes is not None:

/usr/local/share/sciencebox/venv/lib/python3.6/site-packages/pyarrow/parquet.py in read(self, columns, use_threads, use_pandas_metadata)
   1744         table = self._dataset.to_table(
   1745             columns=columns, filter=self._filter_expression,
-> 1746             use_threads=use_threads
   1747         )
   1748 

/usr/local/share/sciencebox/venv/lib/python3.6/site-packages/pyarrow/_dataset.pyx in pyarrow._dataset.Dataset.to_table()

/usr/local/share/sciencebox/venv/lib/python3.6/site-packages/pyarrow/_dataset.pyx in pyarrow._dataset.Dataset.scanner()

/usr/local/share/sciencebox/venv/lib/python3.6/site-packages/pyarrow/_dataset.pyx in pyarrow._dataset.Scanner.from_dataset()

/usr/local/share/sciencebox/venv/lib/python3.6/site-packages/pyarrow/_dataset.pyx in pyarrow._dataset._populate_builder()

/usr/local/share/sciencebox/venv/lib/python3.6/site-packages/pyarrow/error.pxi in pyarrow.lib.check_status()

ArrowInvalid: No match for FieldRef.Name(interaction.type) in user_id: string
interaction: struct<element: string, type: string>{noformat}
Whereas: 
{code:python}
table_legacy = pq.read_table('example.parquet', columns = ['user_id', 'interaction.type'], use_legacy_dataset = True)
{code}
Yields:
{noformat}
pyarrow.Table
user_id: string
interaction: struct<type: string>
  child 0, type: string{noformat}



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