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PyCascading initial commit.

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Gabor Szabo
Gabor Szabo committed Dec 12, 2011
0 parents commit 64c1c4f0e62c425ad5b848b44c9abc936e2eaa66
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+pycascading is a python wrapper for cascading.
+Copyright 2011 Twitter, Inc.
+This software has the follow third party dependencies:
+Jython 2.5.2
+Python Software Foundation License 2.0
+Cascading 1.2.4
+GPL 2.0
+Hadoop 0.20.2
+APL 2.0
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+PyCascading is a Python wrapper for Cascading. You can control the full data
+processing workflow from Python.
+* Pipelines are built with Python operators
+* User-defined functions are written in Python
+* Passing arbitrary contexts to user-defined functions
+* Caching of interim results in pipes for faster replay
+* Uses Jython 2.5.2, easy integration with Java and Python libraries
+There can't be a big data tutorial without counting words. Here it is:
+ @map(produces=['word'])
+ def split_words(tuple):
+ for word in tuple.get(1).split():
+ yield [word]
+ def main():
+ ...
+ input | split_words | GroupBy('word') | Count() | output
+ ...
+Above, the user-defined function that reshapes the stream is annotated with
+a PyCascading decorator, and the workflow is created by chaining operations
+into each other.
+More examples for the different use cases can be found in the examples folder.
+See also the the docstrings in the sources for a complete documentation of the
+PyCascading may be used in one of two modes: in local Hadoop mode or with
+remote Hadoop deployment.
+In *local mode*, the script is executed in Hadoop's local mode. All files
+reside on the local file system, and creating a bundled deployment jar is not
+To run in this mode, use the script, with the first parameter
+being the PyCascading script. Additional command line parameters may be used
+to pass on to the script.
+In *Hadoop mode*, we assume that Hadoop runs on a remote SSH server (or
+localhost). First, a master jar is built and copied to the server. This jar
+contains all the PyCascading classes and other dependencies (but not Hadoop)
+needed to run a job, and may get rather large if there are a few external jars
+included. For this reason it is copied to the Hadoop deployment server only
+once, and whenever a new PyCascading script is run by the user, only the
+Pythn script is copied to the remote server and bundled there for submission
+to Hadoop. The first few variables in the script specify
+the Hadoop server and the folders where the deployment files should be placed.
+* Cascading 1.2.* or 2.0.0 (
+* Jython 2.5.2+ (
+* Hadoop 0.20.2+ (
+PyCascading consists of Java and Python sources. Python sources need no
+compiling, but the Java part needs to be built with Ant. For this, change to
+the 'java' folder, and invoke ant. This should build the sources and create
+a master jar for job submission.
+The locations of the Jython, Cascading, and Hadoop folders on the file system
+are specified in the java/ file. You need to correctly
+specify these before compiling the source.
+Also, check the script and the locations defined in the
+beginning of that file on where to put the jar files on the Hadoop server.
+For transparency and insight into our release cycle, and for striving to
+maintain backwards compatibility, pycascading will be maintained under the
+semantic versioning guidelines as much as possible. Releases will be numbered
+with the follow format:
+And constructed with the following guidelines:
+* Breaking backwards compatibility bumps the major
+* New additions without breaking backwards compatibility bumps the minor
+* Bug fixes and misc changes bump the patch
+For more information on semantic versioning, please visit
+Have a bug or feature request? Please create an issue here on GitHub!
+Mailing list
+Have a question? Ask on our mailing list!
+**Gabor Szabo**
+Copyright 2011 Twitter, Inc.
+Licensed under the Apache License, Version 2.0
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