kedro.extras.datasets.spark.SparkDataSet¶
- class kedro.extras.datasets.spark.SparkDataSet(filepath, file_format='parquet', load_args=None, save_args=None, version=None, credentials=None)[source]¶
SparkDataSet
loads and saves Spark dataframes.Example usage for the YAML API:
weather: type: spark.SparkDataSet filepath: s3a://your_bucket/data/01_raw/weather/* file_format: csv load_args: header: True inferSchema: True save_args: sep: '|' header: True weather_with_schema: type: spark.SparkDataSet filepath: s3a://your_bucket/data/01_raw/weather/* file_format: csv load_args: header: True schema: filepath: path/to/schema.json save_args: sep: '|' header: True weather_cleaned: type: spark.SparkDataSet filepath: data/02_intermediate/data.parquet file_format: 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 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) data_set = SparkDataSet(filepath="test_data") data_set.save(spark_df) reloaded = data_set.load() reloaded.take(4)
Attributes
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.
Compute the version the dataset should be loaded with.
Compute the version the dataset should be saved with.
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='parquet', load_args=None, save_args=None, version=None, credentials=None)[source]¶
Creates a new instance of
SparkDataSet
.- Parameters
filepath (
str
) – Filepath in POSIX format to a Spark dataframe. When using Databricks and working with data written to mount path points, specifyfilepath``s for (versioned) ``SparkDataSet``s starting with ``/dbfs/mnt
.file_format (
str
) – File format used during load and save operations. These are formats supported by the running SparkContext include parquet, csv, delta. For a list of supported formats please refer to Apache Spark documentation at https://spark.apache.org/docs/latest/sql-programming-guide.htmlload_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 supported format in Spark DataFrame read documentation: https://spark.apache.org/docs/latest/api/python/getting_started/quickstart_df.htmlsave_args (
Optional
[Dict
[str
,Any
]]) – Save args passed to Spark DataFrame write options. Similar to load_args this is dependent on the selected file format. You can passmode
andpartitionBy
to specify your overwrite mode and partitioning respectively. You can find a list of options for each format in Spark DataFrame write documentation: https://spark.apache.org/docs/latest/api/python/getting_started/quickstart_df.htmlversion (
Optional
[Version
]) – If specified, should be an instance ofkedro.io.core.Version
. If itsload
attribute is None, the latest version will be loaded. If itssave
attribute is None, save version will be autogenerated.credentials (
Optional
[Dict
[str
,Any
]]) – Credentials to access the S3 bucket, such askey
,secret
, iffilepath
prefix iss3a://
ors3n://
. Optional keyword arguments passed tohdfs.client.InsecureClient
iffilepath
prefix ishdfs://
. Ignored otherwise.
- 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
- resolve_load_version()¶
Compute the version the dataset should be loaded with.
- Return type
str | None
- resolve_save_version()¶
Compute the version the dataset should be saved with.
- Return type
str | 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