31a16fbb40
### What changes were proposed in this pull request? This PR proposes migration of [`pyspark-stubs`](https://github.com/zero323/pyspark-stubs) into Spark codebase. ### Why are the changes needed? ### Does this PR introduce _any_ user-facing change? Yes. This PR adds type annotations directly to Spark source. This can impact interaction with development tools for users, which haven't used `pyspark-stubs`. ### How was this patch tested? - [x] MyPy tests of the PySpark source ``` mypy --no-incremental --config python/mypy.ini python/pyspark ``` - [x] MyPy tests of Spark examples ``` MYPYPATH=python/ mypy --no-incremental --config python/mypy.ini examples/src/main/python/ml examples/src/main/python/sql examples/src/main/python/sql/streaming ``` - [x] Existing Flake8 linter - [x] Existing unit tests Tested against: - `mypy==0.790+dev.e959952d9001e9713d329a2f9b196705b028f894` - `mypy==0.782` Closes #29591 from zero323/SPARK-32681. Authored-by: zero323 <mszymkiewicz@gmail.com> Signed-off-by: HyukjinKwon <gurwls223@apache.org>
58 lines
1.9 KiB
Python
58 lines
1.9 KiB
Python
#
|
|
# Licensed to the Apache Software Foundation (ASF) under one
|
|
# or more contributor license agreements. See the NOTICE file
|
|
# distributed with this work for additional information
|
|
# regarding copyright ownership. The ASF licenses this file
|
|
# to you under the Apache License, Version 2.0 (the
|
|
# "License"); you may not use this file except in compliance
|
|
# with the License. You may obtain a copy of the License at
|
|
#
|
|
# http://www.apache.org/licenses/LICENSE-2.0
|
|
#
|
|
# Unless required by applicable law or agreed to in writing,
|
|
# software distributed under the License is distributed on an
|
|
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
|
|
# KIND, either express or implied. See the License for the
|
|
# specific language governing permissions and limitations
|
|
# under the License.
|
|
|
|
from typing import Any, Callable, Optional
|
|
|
|
from pyspark.sql._typing import ColumnOrName, DataTypeOrString
|
|
from pyspark.sql.column import Column
|
|
import pyspark.sql.session
|
|
|
|
class UserDefinedFunction:
|
|
func: Callable[..., Any]
|
|
evalType: int
|
|
deterministic: bool
|
|
def __init__(
|
|
self,
|
|
func: Callable[..., Any],
|
|
returnType: DataTypeOrString = ...,
|
|
name: Optional[str] = ...,
|
|
evalType: int = ...,
|
|
deterministic: bool = ...,
|
|
) -> None: ...
|
|
@property
|
|
def returnType(self): ...
|
|
def __call__(self, *cols: ColumnOrName) -> Column: ...
|
|
def asNondeterministic(self) -> UserDefinedFunction: ...
|
|
|
|
class UDFRegistration:
|
|
sparkSession: pyspark.sql.session.SparkSession
|
|
def __init__(self, sparkSession: pyspark.sql.session.SparkSession) -> None: ...
|
|
def register(
|
|
self,
|
|
name: str,
|
|
f: Callable[..., Any],
|
|
returnType: Optional[DataTypeOrString] = ...,
|
|
): ...
|
|
def registerJavaFunction(
|
|
self,
|
|
name: str,
|
|
javaClassName: str,
|
|
returnType: Optional[DataTypeOrString] = ...,
|
|
) -> None: ...
|
|
def registerJavaUDAF(self, name: str, javaClassName: str) -> None: ...
|