feat: add dictionary_columns parameter to Table.scan() for memory-efficient reads#3461
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…icient reads
Columns that contain large or frequently repeated strings (e.g. JSON
blobs, low-cardinality categoricals) can exhaust memory when PyArrow
loads them as plain string arrays. PyArrow's Parquet reader supports
reading such columns as dictionary-encoded arrays, which deduplicates
values and can dramatically reduce memory usage.
Add a dictionary_columns: tuple[str, ...] parameter to Table.scan()
(and the underlying TableScan / ArrowScan classes) that is forwarded
to _get_file_format() as PyArrow's dictionary_columns kwarg. Only
applies to Parquet files; silently ignored for ORC.
Usage:
table.scan(dictionary_columns=("payload",)).to_arrow()
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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Closes #3170
Rationale
Columns that contain large or frequently repeated string values (e.g. JSON blobs, low-cardinality categoricals) can exhaust memory when PyArrow loads them as plain string arrays. PyArrow's Parquet reader natively supports dictionary-encoded reads via its
dictionary_columnskwarg, which deduplicates values and can dramatically reduce peak memory usage.This was previously discussed in #3168 and a prior implementation (#3234) was closed as stale.
Changes
dictionary_columns: tuple[str, ...] = ()toTable.scan(),TableScan.__init__, andStagedTable.scan().DataScan.to_arrow()andto_arrow_batch_reader()→ArrowScan.__init__→_task_to_record_batches→_get_file_format().task.file.file_format == FileFormat.PARQUET; silently ignored for ORC (which does not support this kwarg).Usage
Verification
test_dictionary_columns_produces_dict_encoded_output— confirms the requested column is dict-encoded, non-requested columns are plain, and values are identical.make lint✓pytest tests/table/ tests/io/test_pyarrow.py✓