kedro.extras.datasets.dask.ParquetDataSet

class kedro.extras.datasets.dask.ParquetDataSet(filepath, load_args=None, save_args=None, credentials=None, fs_args=None)[source]

ParquetDataSet loads and saves data to parquet file(s). It uses Dask remote data services to handle the corresponding load and save operations: https://docs.dask.org/en/latest/how-to/connect-to-remote-data.html

Example (AWS S3):

from kedro.extras.datasets.dask import ParquetDataSet
import pandas as pd
import dask.dataframe as dd

data = pd.DataFrame({'col1': [1, 2], 'col2': [4, 5],
                     'col3': [5, 6]})
ddf = dd.from_pandas(data, npartitions=2)

data_set = ParquetDataSet(
    filepath="s3://bucket_name/path/to/folder",
    credentials={
        'client_kwargs':{
            'aws_access_key_id': 'YOUR_KEY',
            'aws_secret_access_key': 'YOUR SECRET',
        }
    },
    save_args={"compression": "GZIP"}
)
data_set.save(ddf)
reloaded = data_set.load()

assert ddf.compute().equals(reloaded.compute())

Attributes

DEFAULT_LOAD_ARGS

DEFAULT_SAVE_ARGS

fs_args

Property of optional file system parameters.

Methods

exists()

Checks whether a data set’s output already exists by calling the provided _exists() method.

from_config(name, config[, load_version, …])

Create a data set instance using the configuration provided.

load()

Loads data by delegation to the provided load method.

release()

Release any cached data.

save(data)

Saves data by delegation to the provided save method.

DEFAULT_LOAD_ARGS: Dict[str, Any] = {}
DEFAULT_SAVE_ARGS: Dict[str, Any] = {'write_index': False}
__init__(filepath, load_args=None, save_args=None, credentials=None, fs_args=None)[source]

Creates a new instance of ParquetDataSet pointing to concrete parquet files.

Parameters
exists()

Checks whether a data set’s output already exists by calling the provided _exists() method.

Return type

bool

Returns

Flag indicating whether the output already exists.

Raises

DataSetError – when underlying exists method raises error.

classmethod from_config(name, config, load_version=None, save_version=None)

Create a data set instance using the configuration provided.

Parameters
  • name (str) – Data set name.

  • config (Dict[str, Any]) – Data set config dictionary.

  • load_version (Optional[str]) – Version string to be used for load operation if the data set is versioned. Has no effect on the data set if versioning was not enabled.

  • save_version (Optional[str]) – Version string to be used for save operation if the data set is versioned. Has no effect on the data set if versioning was not enabled.

Return type

AbstractDataSet

Returns

An instance of an AbstractDataSet subclass.

Raises

DataSetError – When the function fails to create the data set from its config.

property fs_args

Property of optional file system parameters.

Return type

Dict[str, Any]

Returns

A dictionary of backend file system parameters, including credentials.

load()

Loads data by delegation to the provided load method.

Return type

Any

Returns

Data returned by the provided load method.

Raises

DataSetError – When underlying load method raises error.

release()

Release any cached data.

Raises

DataSetError – when underlying release method raises error.

Return type

None

save(data)

Saves data by delegation to the provided save method.

Parameters

data (Any) – the value to be saved by provided save method.

Raises
  • DataSetError – when underlying save method raises error.

  • FileNotFoundError – when save method got file instead of dir, on Windows.

  • NotADirectoryError – when save method got file instead of dir, on Unix.

Return type

None