"""SparkJDBCDataset to load and save a PySpark DataFrame via JDBC."""
from copy import deepcopy
from typing import Any
from kedro.io.core import AbstractDataset, DatasetError
from pyspark.sql import DataFrame
from kedro_datasets.spark.spark_dataset import _get_spark
[docs]
class SparkJDBCDataset(AbstractDataset[DataFrame, DataFrame]):
"""``SparkJDBCDataset`` loads data from a database table accessible
via JDBC URL url and connection properties and saves the content of
a PySpark DataFrame to an external database table via JDBC. It uses
``pyspark.sql.DataFrameReader`` and ``pyspark.sql.DataFrameWriter``
internally, so it supports all allowed PySpark options on ``jdbc``.
Example usage for the
`YAML API <https://kedro.readthedocs.io/en/stable/data/\
data_catalog_yaml_examples.html>`_:
.. code-block:: yaml
weather:
type: spark.SparkJDBCDataset
table: weather_table
url: jdbc:postgresql://localhost/test
credentials: db_credentials
load_args:
properties:
driver: org.postgresql.Driver
save_args:
properties:
driver: org.postgresql.Driver
Example usage for the
`Python API <https://kedro.readthedocs.io/en/stable/data/\
advanced_data_catalog_usage.html>`_:
.. code-block:: pycon
>>> import pandas as pd
>>> from kedro_datasets.spark import SparkJBDCDataset
>>> from pyspark.sql import SparkSession
>>>
>>> spark = SparkSession.builder.getOrCreate()
>>> data = spark.createDataFrame(
... pd.DataFrame({"col1": [1, 2], "col2": [4, 5], "col3": [5, 6]})
... )
>>> url = "jdbc:postgresql://localhost/test"
>>> table = "table_a"
>>> connection_properties = {"driver": "org.postgresql.Driver"}
>>> dataset = SparkJDBCDataset(
... url=url,
... table=table,
... credentials={"user": "scott", "password": "tiger"},
... load_args={"properties": connection_properties},
... save_args={"properties": connection_properties},
... )
>>>
>>> dataset.save(data)
>>> reloaded = dataset.load()
>>>
>>> assert data.toPandas().equals(reloaded.toPandas())
"""
DEFAULT_LOAD_ARGS: dict[str, Any] = {}
DEFAULT_SAVE_ARGS: dict[str, Any] = {}
[docs]
def __init__( # noqa: PLR0913
self,
*,
url: str,
table: str,
credentials: dict[str, Any] = None,
load_args: dict[str, Any] = None,
save_args: dict[str, Any] = None,
metadata: dict[str, Any] = None,
) -> None:
"""Creates a new ``SparkJDBCDataset``.
Args:
url: A JDBC URL of the form ``jdbc:subprotocol:subname``.
table: The name of the table to load or save data to.
credentials: A dictionary of JDBC database connection arguments.
Normally at least properties ``user`` and ``password`` with
their corresponding values. It updates ``properties``
parameter in ``load_args`` and ``save_args`` in case it is
provided.
load_args: Provided to underlying PySpark ``jdbc`` function along
with the JDBC URL and the name of the table. To find all
supported arguments, see here:
https://spark.apache.org/docs/latest/api/python/reference/pyspark.sql/api/pyspark.sql.DataFrameWriter.jdbc.html
save_args: Provided to underlying PySpark ``jdbc`` function along
with the JDBC URL and the name of the table. To find all
supported arguments, see here:
https://spark.apache.org/docs/latest/api/python/reference/pyspark.sql/api/pyspark.sql.DataFrameWriter.jdbc.html
metadata: Any arbitrary metadata.
This is ignored by Kedro, but may be consumed by users or external plugins.
Raises:
DatasetError: When either ``url`` or ``table`` is empty or
when a property is provided with a None value.
"""
if not url:
raise DatasetError(
"'url' argument cannot be empty. Please "
"provide a JDBC URL of the form "
"'jdbc:subprotocol:subname'."
)
if not table:
raise DatasetError(
"'table' argument cannot be empty. Please "
"provide the name of the table to load or save "
"data to."
)
self._url = url
self._table = table
self.metadata = metadata
# Handle default load and save arguments
self._load_args = deepcopy(self.DEFAULT_LOAD_ARGS)
if load_args is not None:
self._load_args.update(load_args)
self._save_args = deepcopy(self.DEFAULT_SAVE_ARGS)
if save_args is not None:
self._save_args.update(save_args)
# Update properties in load_args and save_args with credentials.
if credentials is not None:
# Check credentials for bad inputs.
for cred_key, cred_value in credentials.items():
if cred_value is None:
raise DatasetError(
f"Credential property '{cred_key}' cannot be None. "
f"Please provide a value."
)
load_properties = self._load_args.get("properties", {})
save_properties = self._save_args.get("properties", {})
self._load_args["properties"] = {**load_properties, **credentials}
self._save_args["properties"] = {**save_properties, **credentials}
def _describe(self) -> dict[str, Any]:
load_args = self._load_args
save_args = self._save_args
# Remove user and password values from load and save properties.
if "properties" in load_args:
load_properties = load_args["properties"].copy()
load_properties.pop("user", None)
load_properties.pop("password", None)
load_args = {**load_args, "properties": load_properties}
if "properties" in save_args:
save_properties = save_args["properties"].copy()
save_properties.pop("user", None)
save_properties.pop("password", None)
save_args = {**save_args, "properties": save_properties}
return {
"url": self._url,
"table": self._table,
"load_args": load_args,
"save_args": save_args,
}
def _load(self) -> DataFrame:
return _get_spark().read.jdbc(self._url, self._table, **self._load_args)
def _save(self, data: DataFrame) -> None:
return data.write.jdbc(self._url, self._table, **self._save_args)
