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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 sys
from pyspark import since, SparkContext
from pyspark.sql.column import _to_seq, _to_java_column
__all__ = ["Window", "WindowSpec"]
def _to_java_cols(cols):
sc = SparkContext._active_spark_context
if len(cols) == 1 and isinstance(cols[0], list):
cols = cols[0]
return _to_seq(sc, cols, _to_java_column)
class Window(object):
"""
Utility functions for defining window in DataFrames.
For example:
>>> # ORDER BY date ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW
>>> window = Window.orderBy("date").rowsBetween(Window.unboundedPreceding, Window.currentRow)
>>> # PARTITION BY country ORDER BY date RANGE BETWEEN 3 PRECEDING AND 3 FOLLOWING
>>> window = Window.orderBy("date").partitionBy("country").rangeBetween(-3, 3)
.. note:: Experimental
.. versionadded:: 1.4
"""
_JAVA_MIN_LONG = -(1 << 63) # -9223372036854775808
_JAVA_MAX_LONG = (1 << 63) - 1 # 9223372036854775807
_PRECEDING_THRESHOLD = max(-sys.maxsize, _JAVA_MIN_LONG)
_FOLLOWING_THRESHOLD = min(sys.maxsize, _JAVA_MAX_LONG)
unboundedPreceding = _JAVA_MIN_LONG
unboundedFollowing = _JAVA_MAX_LONG
currentRow = 0
@staticmethod
@since(1.4)
def partitionBy(*cols):
"""
Creates a :class:`WindowSpec` with the partitioning defined.
"""
sc = SparkContext._active_spark_context
jspec = sc._jvm.org.apache.spark.sql.expressions.Window.partitionBy(_to_java_cols(cols))
return WindowSpec(jspec)
@staticmethod
@since(1.4)
def orderBy(*cols):
"""
Creates a :class:`WindowSpec` with the ordering defined.
"""
sc = SparkContext._active_spark_context
jspec = sc._jvm.org.apache.spark.sql.expressions.Window.orderBy(_to_java_cols(cols))
return WindowSpec(jspec)
@staticmethod
@since(2.1)
def rowsBetween(start, end):
"""
Creates a :class:`WindowSpec` with the frame boundaries defined,
from `start` (inclusive) to `end` (inclusive).
Both `start` and `end` are relative positions from the current row.
For example, "0" means "current row", while "-1" means the row before
the current row, and "5" means the fifth row after the current row.
We recommend users use ``Window.unboundedPreceding``, ``Window.unboundedFollowing``,
and ``Window.currentRow`` to specify special boundary values, rather than using integral
values directly.
:param start: boundary start, inclusive.
The frame is unbounded if this is ``Window.unboundedPreceding``, or
any value less than or equal to -9223372036854775808.
:param end: boundary end, inclusive.
The frame is unbounded if this is ``Window.unboundedFollowing``, or
any value greater than or equal to 9223372036854775807.
"""
if start <= Window._PRECEDING_THRESHOLD:
start = Window.unboundedPreceding
if end >= Window._FOLLOWING_THRESHOLD:
end = Window.unboundedFollowing
sc = SparkContext._active_spark_context
jspec = sc._jvm.org.apache.spark.sql.expressions.Window.rowsBetween(start, end)
return WindowSpec(jspec)
@staticmethod
@since(2.1)
def rangeBetween(start, end):
"""
Creates a :class:`WindowSpec` with the frame boundaries defined,
from `start` (inclusive) to `end` (inclusive).
Both `start` and `end` are relative from the current row. For example,
"0" means "current row", while "-1" means one off before the current row,
and "5" means the five off after the current row.
We recommend users use ``Window.unboundedPreceding``, ``Window.unboundedFollowing``,
and ``Window.currentRow`` to specify special boundary values, rather than using integral
values directly.
:param start: boundary start, inclusive.
The frame is unbounded if this is ``Window.unboundedPreceding``, or
any value less than or equal to max(-sys.maxsize, -9223372036854775808).
:param end: boundary end, inclusive.
The frame is unbounded if this is ``Window.unboundedFollowing``, or
any value greater than or equal to min(sys.maxsize, 9223372036854775807).
"""
if start <= Window._PRECEDING_THRESHOLD:
start = Window.unboundedPreceding
if end >= Window._FOLLOWING_THRESHOLD:
end = Window.unboundedFollowing
sc = SparkContext._active_spark_context
jspec = sc._jvm.org.apache.spark.sql.expressions.Window.rangeBetween(start, end)
return WindowSpec(jspec)
class WindowSpec(object):
"""
A window specification that defines the partitioning, ordering,
and frame boundaries.
Use the static methods in :class:`Window` to create a :class:`WindowSpec`.
.. note:: Experimental
.. versionadded:: 1.4
"""
def __init__(self, jspec):
self._jspec = jspec
@since(1.4)
def partitionBy(self, *cols):
"""
Defines the partitioning columns in a :class:`WindowSpec`.
:param cols: names of columns or expressions
"""
return WindowSpec(self._jspec.partitionBy(_to_java_cols(cols)))
@since(1.4)
def orderBy(self, *cols):
"""
Defines the ordering columns in a :class:`WindowSpec`.
:param cols: names of columns or expressions
"""
return WindowSpec(self._jspec.orderBy(_to_java_cols(cols)))
@since(1.4)
def rowsBetween(self, start, end):
"""
Defines the frame boundaries, from `start` (inclusive) to `end` (inclusive).
Both `start` and `end` are relative positions from the current row.
For example, "0" means "current row", while "-1" means the row before
the current row, and "5" means the fifth row after the current row.
We recommend users use ``Window.unboundedPreceding``, ``Window.unboundedFollowing``,
and ``Window.currentRow`` to specify special boundary values, rather than using integral
values directly.
:param start: boundary start, inclusive.
The frame is unbounded if this is ``Window.unboundedPreceding``, or
any value less than or equal to max(-sys.maxsize, -9223372036854775808).
:param end: boundary end, inclusive.
The frame is unbounded if this is ``Window.unboundedFollowing``, or
any value greater than or equal to min(sys.maxsize, 9223372036854775807).
"""
if start <= Window._PRECEDING_THRESHOLD:
start = Window.unboundedPreceding
if end >= Window._FOLLOWING_THRESHOLD:
end = Window.unboundedFollowing
return WindowSpec(self._jspec.rowsBetween(start, end))
@since(1.4)
def rangeBetween(self, start, end):
"""
Defines the frame boundaries, from `start` (inclusive) to `end` (inclusive).
Both `start` and `end` are relative from the current row. For example,
"0" means "current row", while "-1" means one off before the current row,
and "5" means the five off after the current row.
We recommend users use ``Window.unboundedPreceding``, ``Window.unboundedFollowing``,
and ``Window.currentRow`` to specify special boundary values, rather than using integral
values directly.
:param start: boundary start, inclusive.
The frame is unbounded if this is ``Window.unboundedPreceding``, or
any value less than or equal to max(-sys.maxsize, -9223372036854775808).
:param end: boundary end, inclusive.
The frame is unbounded if this is ``Window.unboundedFollowing``, or
any value greater than or equal to min(sys.maxsize, 9223372036854775807).
"""
if start <= Window._PRECEDING_THRESHOLD:
start = Window.unboundedPreceding
if end >= Window._FOLLOWING_THRESHOLD:
end = Window.unboundedFollowing
return WindowSpec(self._jspec.rangeBetween(start, end))
def _test():
import doctest
SparkContext('local[4]', 'PythonTest')
(failure_count, test_count) = doctest.testmod()
if failure_count:
exit(-1)
if __name__ == "__main__":
_test()
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