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link.parallel is a database agnostic query system.
See documentation_ for more informations.
.. _documentation: https://linkparallel.readthedocs.io
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.. code-block:: text
pip install link.parallel
Create your map/reduce functions:
.. code-block:: python
from b3j0f.task import register_task
@register_task('mymap') def mymap(mapper, item): if item['i'] < 5: mapper.emit('i_lt_5', item)
elif item['i'] > 5:
mapper.emit('i_gt_5', item)
else:
mapper.emit('i_eq_5', item)
@register_task('myreduce') def myreduce(key, values): return (key, len(values))
Get input data and pass it to the middleware:
.. code-block:: python
from link.middleware.core import Middleware
mapreduce = Middleware.get_middleware_by_uri( 'mapreduce+ipython:///test/classify?mapcb=mymap&reducecb=myreduce' )
items = # load items result = dict(mapreduce(items))
print(result)
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FAQs
Parallel computing framework
We found that link.parallel demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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