kedro_datasets.spark.DeltaTableDataset

class kedro_datasets.spark.DeltaTableDataset(filepath, metadata=None)[source]

DeltaTableDataset loads data into DeltaTable objects.

Example usage for the YAML API:

weather@spark:
  type: spark.SparkDataset
  filepath: data/02_intermediate/data.parquet
  file_format: "delta"

weather@delta:
  type: spark.DeltaTableDataset
  filepath: data/02_intermediate/data.parquet

Example usage for the Python API:

 from pyspark.sql import SparkSession
 from pyspark.sql.types import (StructField, StringType,
...                                IntegerType, StructType)

 from kedro.extras.datasets.spark import DeltaTableDataset, SparkDataset

 schema = StructType([StructField("name", StringType(), True),
...                      StructField("age", IntegerType(), True)])

 data = [('Alex', 31), ('Bob', 12), ('Clarke', 65), ('Dave', 29)]

 spark_df = SparkSession.builder.getOrCreate().createDataFrame(data, schema)

 dataset = SparkDataset(filepath="test_data", file_format="delta")
 dataset.save(spark_df)
 deltatable_dataset = DeltaTableDataset(filepath="test_data")
 delta_table = deltatable_dataset.load()

 delta_table.update()

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.
__init__(filepath, metadata=None)[source]

Creates a new instance of DeltaTableDataset.

Parameters:

  • filepath (str) – Filepath in POSIX format to a Spark dataframe. When using Databricks and working with data written to mount path points, specify filepath``s for (versioned) ``SparkDataset``s starting with ``/dbfs/mnt.

  • metadata (Optional[Dict[str, Any]]) – Any arbitrary metadata. This is ignored by Kedro, but may be consumed by users or external plugins.

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 – Data set name.

  • config – Data set config dictionary.

  • load_version – 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 – 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.

Returns:

An instance of an AbstractDataset subclass.

Raises:

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

load()

Loads data by delegation to the provided load method.

Return type:

TypeVar(_DO)

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 (TypeVar(_DI)) – 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