dask.dataframe.read_orc(path, engine='pyarrow', columns=None, index=None, split_stripes=1, aggregate_files=None, storage_options=None)[source]

Read dataframe from ORC file(s)

path: str or list(str)

Location of file(s), which can be a full URL with protocol specifier, and may include glob character if a single string.

engine: ‘pyarrow’ or ORCEngine

Backend ORC engine to use for IO. Default is “pyarrow”.

columns: None or list(str)

Columns to load. If None, loads all.

index: str

Column name to set as index.

split_stripes: int or False

Maximum number of ORC stripes to include in each output-DataFrame partition. Use False to specify a 1-to-1 mapping between files and partitions. Default is 1.

aggregate_filesbool, default False

Whether distinct file paths may be aggregated into the same output partition. A setting of True means that any two file paths may be aggregated into the same output partition, while False means that inter-file aggregation is prohibited.

storage_options: None or dict

Further parameters to pass to the bytes backend.

Dask.DataFrame (even if there is only one column)


>>> df = dd.read_orc('https://github.com/apache/orc/raw/'
...                  'master/examples/demo-11-zlib.orc')