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Python-Hadoop Tools & How2s

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Add-steps — AWS CLI 1.10.56 Command Reference. Options --cluster-id (string) A unique string that identifies the cluster.

add-steps — AWS CLI 1.10.56 Command Reference

This identifier is returned by create-cluster and can also be obtained from list-clusters . --steps (list) A list of steps to be executed by the cluster. Shorthand Syntax: Name=string,Args=string,string,Jar=string,ActionOnFailure=string,MainClass=string,Type=string,Properties=string ... JSON Syntax: Examples. Mortar Help & Tutorials. Mortar is a powerful, general-purpose platform for high-scale data science.

Mortar Help & Tutorials

It’s built on the Amazon Web Services cloud, using Elastic MapReduce (EMR) to launch Hadoop clusters and process large data sets. Mortar eases the transition from merely having big data to using big data by handling all the mess of launching and managing clusters, while also providing tools to help users track the status of jobs in progress and quickly identify and fix problems. Mortar runs Apache Pig, a data flow language built on top of Hadoop. Pig is easier and faster to use and execute than MapReduce, and it provides a comfortable transition for anyone used to writing SQL. GitHub - mikeaddison93/hadoopy: Python MapReduce library written in Cython. Visit us in #hadoopy on freenode. See the link below for documentation and tutorials. A Guide to Python Frameworks for Hadoop - Cloudera Engineering Blog.

I recently joined Cloudera after working in computational biology/genomics for close to a decade.

A Guide to Python Frameworks for Hadoop - Cloudera Engineering Blog

My analytical work is primarily performed in Python, along with its fantastic scientific stack. It was quite jarring to find out that the Apache Hadoop ecosystem is primarily written in/for Java. So my first order of business was to investigate some of the options that exist for working with Hadoop from Python. In this post, I will provide an unscientific, ad hoc review of my experiences with some of the Python frameworks that exist for working with Hadoop, including: Hadoop Streamingmrjobdumbohadoopypydoopand others Read on for implementation details, performance comparisons, and feature comparisons. Toy Problem Definition To test out the different frameworks, we will not be doing “word count”.

We would like to aggregate the data to count the number of times any pair of words are observed near each other, grouped by year. There is one subtlety that must be addressed. Hardware Implementations #! MRJob : Best way to start algorithm on MapReduce. Except doing queries with Pig or Hive, it’s interesting to understand how to query with Hadoop Map-Reduce job.

MRJob : Best way to start algorithm on MapReduce

Programming it in JAVA can be interested but a more important point is to construct an algorithm under Map-Reduce paradigm. That’s why we focus on algorithms instead of development and we will practice with a python library calls MRJob. What’s Map-Reduce ? Map-Reduce is constrains on programming, implying to develop two mains functions : a map function AND a reduce function. In Hadoop, a Map-Reduce job consists in Three main phases: Map function is here to do work on every chunk of data stored on the cluster. Writing a Multistep MapReduce Job Using the mrjob Python Library: From Data Just Right LiveLessons. Contents — Pydoop 1.2.0 documentation. Pydoop is a Python interface to Hadoop that allows you to write MapReduce applications in pure Python: import pydoop.mapreduce.api as api class Mapper(api.Mapper): def map(self, context): words = context.value.split() for w in words: context.emit(w, 1) class Reducer(api.Reducer): def reduce(self, context): s = sum(context.values) context.emit(context.key, s) Pydoop offers several features not commonly found in other Python libraries for Hadoop: Pydoop enables MapReduce programming via a pure (except for a performance-critical serialization section) Python client for Hadoop Pipes, and HDFS access through an extension module based on libhdfs.

Contents — Pydoop 1.2.0 documentation

To get started, read the tutorial. Full docs, including installation instructions, are listed below. Home · klbostee/dumbo Wiki. Klbostee/dumbo @ GitHub. GitHub - FlyTrapMind/pydoop: A Python MapReduce and HDFS API for Hadoop. GitHub - FlyTrapMind/dumbo: Python module that allows one to easily write and run Hadoop programs. Home · klbostee/dumbo Wiki. Mrjob — mrjob v0.5.3 documentation. Mrjob¶ mrjob lets you write MapReduce jobs in Python 2.6+/3.3+ and run them on several platforms.

mrjob — mrjob v0.5.3 documentation

You can: Write multi-step MapReduce jobs in pure PythonTest on your local machineRun on a Hadoop clusterRun in the cloud using Amazon Elastic MapReduce (EMR)Run in the cloud using Google Cloud Dataproc (Dataproc) mrjob is licensed under the Apache License, Version 2.0. To get started, install with pip: pip install mrjob and begin reading the tutorial below. Appendices Index Module Index Search Page Quick Links Need help?