A Python library for prototyping MapReduce jobs
mockr is a Python library for writing MapReduce jobs in an Educational setting. It is intended to be used as a conceptual teaching tool.
mockr provides an interface for defining and running MapReduce locally. Simply define your map and reduce functions, input your data and call the run function. Everything is run sequentially and locally.
pip install mockr
Full documentation available here https://mockr.readthedocs.io/
StreamingJob class which expects the input to be a byte stream of characters. The chunks of data are separated by newline ("\n") characters. Each line is sent to a separate map worker.
Native Python Sequence Jobs
PythonJob class expects input to be a Collections.abc.Sequence type object e.g. Python List. Python Jobs provide two exection methods:
- the sequence is divided into chunks and each chunk is sent to a separate map worker
- each item in the list is individually sent to a dedicated map worker
PandasJob class expects input to be a Pandas DataFrame. The rows of the data frame are equally divided into chunks and each chunk is sent to a separate map worker
import re from mockr import run_stream_job WORD_RE = re.compile(r"[\w']+") def map_fn(chunk): # yield each word in the line for word in WORD_RE.findall(chunk): yield (word.lower(), 1) def reduce_fn(key, values): yield (key, sum(values)) input_str = "Hello!\nThis is a sample string.\nIt is very simple.\nGoodbye!" results = run_stream_job(input_str, map_fn, reduce_fn) print(results)
[('hello', 1), ('this', 1), ('is', 2), ('a', 1), ('sample', 1), ('string', 1), ('it', 1), ('very', 1), ('simple', 1), ('goodbye', 1)]
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