spark-instrumented-optimizer/python/pyspark/broadcast.pyi

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#
# 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.
import threading
from typing import Any, Generic, Optional, TypeVar
T = TypeVar("T")
class Broadcast(Generic[T]):
def __init__(
self,
sc: Optional[Any] = ...,
value: Optional[T] = ...,
pickle_registry: Optional[Any] = ...,
path: Optional[Any] = ...,
sock_file: Optional[Any] = ...,
) -> None: ...
def dump(self, value: Any, f: Any) -> None: ...
def load_from_path(self, path: Any): ...
def load(self, file: Any): ...
@property
def value(self) -> T: ...
def unpersist(self, blocking: bool = ...) -> None: ...
def destroy(self, blocking: bool = ...) -> None: ...
def __reduce__(self): ...
class BroadcastPickleRegistry(threading.local):
def __init__(self) -> None: ...
def __iter__(self) -> None: ...
def add(self, bcast: Any) -> None: ...
def clear(self) -> None: ...