Source code for apache_beam.transforms.sideinputs

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"""Internal side input transforms and implementations.

For internal use only; no backwards-compatibility guarantees.

Important: this module is an implementation detail and should not be used
directly by pipeline writers. Instead, users should use the helper methods
AsSingleton, AsIter, AsList and AsDict in apache_beam.pvalue.

from __future__ import absolute_import

from apache_beam.transforms import window

# Top-level function so we can identify it later.
def _global_window_mapping_fn(w, global_window=window.GlobalWindow()):
  return global_window

[docs]def default_window_mapping_fn(target_window_fn): if target_window_fn == window.GlobalWindows(): return _global_window_mapping_fn def map_via_end(source_window): return list(target_window_fn.assign( window.WindowFn.AssignContext(source_window.max_timestamp())))[-1] return map_via_end
[docs]class SideInputMap(object): """Represents a mapping of windows to side input values.""" def __init__(self, view_class, view_options, iterable): self._window_mapping_fn = view_options.get( 'window_mapping_fn', _global_window_mapping_fn) self._view_class = view_class self._view_options = view_options self._iterable = iterable self._cache = {} def __getitem__(self, window): if window not in self._cache: target_window = self._window_mapping_fn(window) self._cache[window] = self._view_class._from_runtime_iterable( _FilteringIterable(self._iterable, target_window), self._view_options) return self._cache[window]
[docs] def is_globally_windowed(self): return self._window_mapping_fn == _global_window_mapping_fn
class _FilteringIterable(object): """An iterable containing only those values in the given window. """ def __init__(self, iterable, target_window): self._iterable = iterable self._target_window = target_window def __iter__(self): for wv in self._iterable: if self._target_window in yield wv.value def __reduce__(self): # Pickle self as an already filtered list. return list, (list(self),)