mars.dataframe.read_parquet

mars.dataframe.read_parquet(path, engine: str = 'auto', columns=None, groups_as_chunks=False, use_arrow_dtype=None, incremental_index=False, storage_options=None, memory_scale=None, **kwargs)[source]

Load a parquet object from the file path, returning a DataFrame.

Parameters

  • path (str, path object or file-like object) – Any valid string path is acceptable. The string could be a URL. For file URLs, a host is expected. A local file could be: file://localhost/path/to/table.parquet. A file URL can also be a path to a directory that contains multiple partitioned parquet files. Both pyarrow and fastparquet support paths to directories as well as file URLs. A directory path could be: file://localhost/path/to/tables. By file-like object, we refer to objects with a read() method, such as a file handler (e.g. via builtin open function) or StringIO.

  • engine ({'auto', 'pyarrow', 'fastparquet'}, default 'auto') – Parquet library to use. The default behavior is to try ‘pyarrow’, falling back to ‘fastparquet’ if ‘pyarrow’ is unavailable.

  • columns (list, default=None) – If not None, only these columns will be read from the file.

  • groups_as_chunks (bool, default False) – if True, each row group correspond to a chunk. if False, each file correspond to a chunk. Only available for ‘pyarrow’ engine.

  • incremental_index (bool, default False) – If index_col not specified, ensure range index incremental, gain a slightly better performance if setting False.

  • use_arrow_dtype (bool, default None) – If True, use arrow dtype to store columns.

  • storage_options (dict, optional) – Options for storage connection.

  • memory_scale (int, optional) – Scale that real memory occupation divided with raw file size.

  • **kwargs – Any additional kwargs are passed to the engine.

Returns

Return type

Mars DataFrame

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