#
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# 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.
from __future__ import absolute_import
import contextlib
import threading
from typing import Any
from typing import Callable
from typing import Iterable
from typing import Optional
from typing import TypeVar
from apache_beam.dataframe import partitionings
[docs]class Session(object):
"""A session represents a mapping of expressions to concrete values.
The bindings typically include required placeholders, but may be any
intermediate expression as well.
"""
def __init__(self, bindings=None):
self._bindings = dict(bindings or {})
[docs] def evaluate(self, expr): # type: (Expression) -> Any
if expr not in self._bindings:
self._bindings[expr] = expr.evaluate_at(self)
return self._bindings[expr]
[docs] def lookup(self, expr): # type: (Expression) -> Any
return self._bindings[expr]
# The return type of an Expression
T = TypeVar('T')
[docs]class Expression(object):
"""An expression is an operation bound to a set of arguments.
An expression represents a deferred tree of operations, which can be
evaluated at a specific bindings of root expressions to values.
"""
def __init__(
self,
name, # type: str
proxy, # type: T
_id=None # type: Optional[str]
):
self._name = name
self._proxy = proxy
# Store for preservation through pickling.
self._id = _id or '%s_%s' % (name, id(self))
[docs] def proxy(self): # type: () -> T
return self._proxy
def __hash__(self):
return hash(self._id)
def __eq__(self, other):
return self._id == other._id
def __ne__(self, other):
return not self == other
def __repr__(self):
return '%s[%s]' % (self.__class__.__name__, self._id)
[docs] def placeholders(self):
"""Returns all the placeholders that self depends on."""
raise NotImplementedError(type(self))
[docs] def evaluate_at(self, session): # type: (Session) -> T
"""Returns the result of self with the bindings given in session."""
raise NotImplementedError(type(self))
[docs] def requires_partition_by(self): # type: () -> partitionings.Partitioning
"""Returns the partitioning, if any, require to evaluate this expression.
Returns partitioning.Nothing() to require no partitioning is required.
"""
raise NotImplementedError(type(self))
[docs] def preserves_partition_by(self): # type: () -> partitionings.Partitioning
"""Returns the partitioning, if any, preserved by this expression.
This gives an upper bound on the partitioning of its ouput. The actual
partitioning of the output may be less strict (e.g. if the input was
less partitioned).
"""
raise NotImplementedError(type(self))
[docs]class PlaceholderExpression(Expression):
"""An expression whose value must be explicitly bound in the session."""
def __init__(
self, # type: PlaceholderExpression
proxy, # type: T
reference=None, # type: Any
):
"""Initialize a placeholder expression.
Args:
proxy: A proxy object with the type expected to be bound to this
expression. Used for type checking at pipeline construction time.
"""
super(PlaceholderExpression, self).__init__('placeholder', proxy)
self._reference = reference
[docs] def placeholders(self):
return frozenset([self])
[docs] def args(self):
return ()
[docs] def evaluate_at(self, session):
return session.lookup(self)
[docs] def requires_partition_by(self):
return partitionings.Nothing()
[docs] def preserves_partition_by(self):
return partitionings.Nothing()
[docs]class ConstantExpression(Expression):
"""An expression whose value is known at pipeline construction time."""
def __init__(
self, # type: ConstantExpression
value, # type: T
proxy=None # type: Optional[T]
):
"""Initialize a constant expression.
Args:
value: The constant value to be produced by this expression.
proxy: (Optional) a proxy object with same type as `value` to use for
rapid type checking at pipeline construction time. If not provided,
`value` will be used directly.
"""
if proxy is None:
proxy = value
super(ConstantExpression, self).__init__('constant', proxy)
self._value = value
[docs] def placeholders(self):
return frozenset()
[docs] def args(self):
return ()
[docs] def evaluate_at(self, session):
return self._value
[docs] def requires_partition_by(self):
return partitionings.Nothing()
[docs] def preserves_partition_by(self):
return partitionings.Nothing()
[docs]class ComputedExpression(Expression):
"""An expression whose value must be computed at pipeline execution time."""
def __init__(
self, # type: ComputedExpression
name, # type: str
func, # type: Callable[...,T]
args, # type: Iterable[Expression]
proxy=None, # type: Optional[T]
_id=None, # type: Optional[str]
requires_partition_by=partitionings.Index(), # type: partitionings.Partitioning
preserves_partition_by=partitionings.Nothing(), # type: partitionings.Partitioning
):
"""Initialize a computed expression.
Args:
name: The name of this expression.
func: The function that will be used to compute the value of this
expression. Should accept arguments of the types returned when
evaluating the `args` expressions.
args: The list of expressions that will be used to produce inputs to
`func`.
proxy: (Optional) a proxy object with same type as the objects that this
ComputedExpression will produce at execution time. If not provided, a
proxy will be generated using `func` and the proxies of `args`.
_id: (Optional) a string to uniquely identify this expression.
requires_partition_by_index: Whether this expression requires its
argument(s) to be partitioned by index.
preserves_partition_by_index: Whether the result of this expression will
be partitioned by index whenever all of its inputs are partitioned by
index.
"""
if (not _get_allow_non_parallel() and
requires_partition_by == partitionings.Singleton()):
raise NonParallelOperation(
"Using non-parallel form of %s "
"outside of allow_non_parallel_operations block." % name)
args = tuple(args)
if proxy is None:
proxy = func(*(arg.proxy() for arg in args))
super(ComputedExpression, self).__init__(name, proxy, _id)
self._func = func
self._args = args
self._requires_partition_by = requires_partition_by
self._preserves_partition_by = preserves_partition_by
[docs] def placeholders(self):
return frozenset.union(
frozenset(), *[arg.placeholders() for arg in self.args()])
[docs] def args(self):
return self._args
[docs] def evaluate_at(self, session):
return self._func(*(session.evaluate(arg) for arg in self._args))
[docs] def requires_partition_by(self):
return self._requires_partition_by
[docs] def preserves_partition_by(self):
return self._preserves_partition_by
[docs]def elementwise_expression(name, func, args):
return ComputedExpression(
name,
func,
args,
requires_partition_by=partitionings.Nothing(),
preserves_partition_by=partitionings.Singleton())
_ALLOW_NON_PARALLEL = threading.local()
_ALLOW_NON_PARALLEL.value = False
def _get_allow_non_parallel():
return _ALLOW_NON_PARALLEL.value
[docs]@contextlib.contextmanager
def allow_non_parallel_operations(allow=True):
old_value, _ALLOW_NON_PARALLEL.value = _ALLOW_NON_PARALLEL.value, allow
yield
_ALLOW_NON_PARALLEL.value = old_value
[docs]class NonParallelOperation(Exception):
pass