flink-ml-python/pyflink/ml/common/window.py (67 lines of code) (raw):
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# 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
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# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
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# See the License for the specific language governing permissions and
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from abc import ABC
from pyflink.common.time import Time
class Windows(ABC):
"""
Windowing strategy that determines how to create mini-batches from input data.
"""
pass
class GlobalWindows(Windows):
"""
A windowing strategy that groups all elements into a single global window.
This strategy assumes that the input strategy is bounded.
"""
def __eq__(self, other):
return isinstance(other, GlobalWindows)
class CountTumblingWindows(Windows):
"""
A windowing strategy that groups elements into fixed-size windows based on
the count number of the elements. Windows do not overlap.
"""
def __init__(self, size: int):
super().__init__()
self._size = size
@staticmethod
def of(size: int) -> 'CountTumblingWindows':
return CountTumblingWindows(size)
@property
def size(self) -> int:
return self._size
def __eq__(self, other):
return isinstance(other, CountTumblingWindows) and self._size == other._size
class EventTimeTumblingWindows(Windows):
"""
A windowing strategy that groups elements into fixed-size windows based on
the timestamp of the elements. Windows do not overlap.
"""
def __init__(self, size: Time):
super().__init__()
self._size = size
@staticmethod
def of(size: Time) -> 'EventTimeTumblingWindows':
return EventTimeTumblingWindows(size)
@property
def size(self) -> Time:
return self._size
def __eq__(self, other):
return isinstance(other, EventTimeTumblingWindows) and self._size == other._size
class ProcessingTimeTumblingWindows(Windows):
"""
A windowing strategy that groups elements into fixed-size windows based on
the current system time of the machine the operation is running on. Windows
do not overlap.
"""
def __init__(self, size: Time):
super().__init__()
self._size = size
@staticmethod
def of(size: Time) -> 'ProcessingTimeTumblingWindows':
return ProcessingTimeTumblingWindows(size)
@property
def size(self) -> Time:
return self._size
def __eq__(self, other):
return isinstance(other, ProcessingTimeTumblingWindows) and self._size == other._size
class EventTimeSessionWindows(Windows):
"""
A windowing strategy that groups elements into sessions based on the
timestamp of the elements. Windows do not overlap.
"""
def __init__(self, gap: Time):
super().__init__()
self._gap = gap
@staticmethod
def with_gap(gap: Time) -> 'EventTimeSessionWindows':
return EventTimeSessionWindows(gap)
@property
def gap(self) -> Time:
return self._gap
def __eq__(self, other):
return isinstance(other, EventTimeSessionWindows) and self._gap == other._gap
class ProcessingTimeSessionWindows(Windows):
"""
A windowing strategy that groups elements into sessions based on the current
system time of the machine the operation is running on. Windows do
not overlap.
"""
def __init__(self, gap: Time):
super().__init__()
self._gap = gap
@staticmethod
def with_gap(gap: Time) -> 'ProcessingTimeSessionWindows':
return ProcessingTimeSessionWindows(gap)
@property
def gap(self) -> Time:
return self._gap
def __eq__(self, other):
return isinstance(other, ProcessingTimeSessionWindows) and self._gap == other._gap