kedro_datasets.spark.SparkStreamingDataset

class kedro_datasets.spark.SparkStreamingDataset(*, filepath='', file_format='', save_args=None, load_args=None)

SparkStreamingDataset loads data to Spark Streaming Dataframe objects.

Example usage for the YAML API:

raw.new_inventory:
  type: spark.SparkStreamingDataset
  filepath: data/01_raw/stream/inventory/
  file_format: json
  save_args:
    output_mode: append
    checkpoint: data/04_checkpoint/raw_new_inventory
    header: True
  load_args:
    schema:
        filepath: data/01_raw/schema/inventory_schema.json

Attributes

DEFAULT_LOAD_ARGS
DEFAULT_SAVE_ARGS

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] = {}

__init__(*, filepath='', file_format='', save_args=None, load_args=None)

Creates a new instance of SparkStreamingDataset.

Parameters:

• filepath (str) – Filepath in POSIX format to a Spark dataframe. When using Databricks specify filepath``s starting with ``/dbfs/. For message brokers such as Kafka and all filepath is not required.

• file_format (str) – File format used during load and save operations. These are formats supported by the running SparkContext including parquet, csv, and delta. For a list of supported formats please refer to the Apache Spark documentation at https://spark.apache.org/docs/latest/structured-streaming-programming-guide.html

• load_args (Optional[dict[str, Any]]) – Load args passed to Spark DataFrameReader load method. It is dependent on the selected file format. You can find a list of read options for each selected format in Spark DataFrame read documentation, see https://spark.apache.org/docs/latest/structured-streaming-programming-guide.html. Please note that a schema is mandatory for a streaming DataFrame if schemaInference is not True.

• save_args (Optional[dict[str, Any]]) – Save args passed to Spark DataFrameReader write options. Similar to load_args, this is dependent on the selected file format. You can pass mode and partitionBy to specify your overwrite mode and partitioning respectively. You can find a list of options for each selected format in Spark DataFrame write documentation, see https://spark.apache.org/docs/latest/structured-streaming-programming-guide.html

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 (str | None) – 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 (str | None) – 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.

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