58 lines
1.9 KiB
Python
58 lines
1.9 KiB
Python
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#
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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 Any, Callable, Optional
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from pyspark.sql._typing import ColumnOrName, DataTypeOrString
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from pyspark.sql.column import Column
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import pyspark.sql.session
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class UserDefinedFunction:
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func: Callable[..., Any]
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evalType: int
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deterministic: bool
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def __init__(
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self,
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func: Callable[..., Any],
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returnType: DataTypeOrString = ...,
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name: Optional[str] = ...,
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evalType: int = ...,
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deterministic: bool = ...,
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) -> None: ...
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@property
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def returnType(self): ...
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def __call__(self, *cols: ColumnOrName) -> Column: ...
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def asNondeterministic(self) -> UserDefinedFunction: ...
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class UDFRegistration:
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sparkSession: pyspark.sql.session.SparkSession
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def __init__(self, sparkSession: pyspark.sql.session.SparkSession) -> None: ...
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def register(
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self,
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name: str,
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f: Callable[..., Any],
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returnType: Optional[DataTypeOrString] = ...,
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): ...
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def registerJavaFunction(
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self,
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name: str,
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javaClassName: str,
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returnType: Optional[DataTypeOrString] = ...,
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) -> None: ...
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def registerJavaUDAF(self, name: str, javaClassName: str) -> None: ...
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