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 kedro_datasets.spark import DeltaTableDataset, SparkDataset from pyspark.sql import SparkSession from pyspark.sql.types import StructField, StringType, IntegerType, StructType 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=tmp_path / "test_data", file_format="delta") dataset.save(spark_df) deltatable_dataset = DeltaTableDataset(filepath=tmp_path / "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, specifyfilepath``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 (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