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>
127 lines
3.5 KiB
Python
127 lines
3.5 KiB
Python
#
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# Licensed to the Apache Software Foundation (ASF) under one
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# or more contributor license agreements. See the NOTICE file
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# distributed with this work for additional information
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# regarding copyright ownership. The ASF licenses this file
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# to you under the Apache License, Version 2.0 (the
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# "License"); you may not use this file except in compliance
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# with the License. You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing,
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# software distributed under the License is distributed on an
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# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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# KIND, either express or implied. See the License for the
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# specific language governing permissions and limitations
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# under the License.
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from typing import Optional
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from pyspark.context import SparkContext
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from pyspark.rdd import RDD
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from pyspark.mllib.linalg import Vector
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class RandomRDDs:
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@staticmethod
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def uniformRDD(
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sc: SparkContext,
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size: int,
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numPartitions: Optional[int] = ...,
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seed: Optional[int] = ...,
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) -> RDD[float]: ...
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@staticmethod
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def normalRDD(
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sc: SparkContext,
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size: int,
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numPartitions: Optional[int] = ...,
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seed: Optional[int] = ...,
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) -> RDD[float]: ...
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@staticmethod
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def logNormalRDD(
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sc: SparkContext,
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mean: float,
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std: float,
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size: int,
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numPartitions: Optional[int] = ...,
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seed: Optional[int] = ...,
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) -> RDD[float]: ...
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@staticmethod
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def poissonRDD(
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sc: SparkContext,
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mean: float,
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size: int,
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numPartitions: Optional[int] = ...,
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seed: Optional[int] = ...,
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) -> RDD[float]: ...
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@staticmethod
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def exponentialRDD(
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sc: SparkContext,
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mean: float,
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size: int,
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numPartitions: Optional[int] = ...,
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seed: Optional[int] = ...,
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) -> RDD[float]: ...
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@staticmethod
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def gammaRDD(
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sc: SparkContext,
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shape: float,
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scale: float,
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size: int,
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numPartitions: Optional[int] = ...,
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seed: Optional[int] = ...,
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) -> RDD[float]: ...
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@staticmethod
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def uniformVectorRDD(
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sc: SparkContext,
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numRows: int,
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numCols: int,
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numPartitions: Optional[int] = ...,
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seed: Optional[int] = ...,
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) -> RDD[Vector]: ...
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@staticmethod
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def normalVectorRDD(
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sc: SparkContext,
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numRows: int,
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numCols: int,
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numPartitions: Optional[int] = ...,
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seed: Optional[int] = ...,
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) -> RDD[Vector]: ...
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@staticmethod
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def logNormalVectorRDD(
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sc: SparkContext,
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mean: float,
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std,
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numRows: int,
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numCols: int,
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numPartitions: Optional[int] = ...,
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seed: Optional[int] = ...,
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) -> RDD[Vector]: ...
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@staticmethod
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def poissonVectorRDD(
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sc: SparkContext,
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mean: float,
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numRows: int,
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numCols: int,
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numPartitions: Optional[int] = ...,
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seed: Optional[int] = ...,
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) -> RDD[Vector]: ...
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@staticmethod
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def exponentialVectorRDD(
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sc: SparkContext,
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mean: float,
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numRows: int,
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numCols: int,
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numPartitions: Optional[int] = ...,
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seed: Optional[int] = ...,
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) -> RDD[Vector]: ...
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@staticmethod
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def gammaVectorRDD(
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sc: SparkContext,
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shape: float,
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scale: float,
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numRows: int,
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numCols: int,
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numPartitions: Optional[int] = ...,
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seed: Optional[int] = ...,
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) -> RDD[Vector]: ...
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