Hadoop Streaming Applications Using Python

Hadoop Streaming: Every day lots of data is being generated by the advent of the internet of things and digital media. This challenge faces the next generation's tools and technologies data storages needs. To handle this, Hadoop Streaming comes in.

Hadoop Streaming

Python Course is a utility which comes with Hadoop distribution. It is used to execute programs for big data. As well as, it performs in user languages such as Python, Java, PHP, Perl, UNIX etc. It allows to create and run, MapReduce jobs on a cluster with any executable.

MapReduce

MapReduce is a way of thinking about big data problems as collections of smaller sub problems. It is a programming model for processing huge data. Generally, the programs are parallel and very useful for performing large scale data analysis using multiple machines. It works in two phases such as Map phase and Reduces Phase. It is a data processing job which splits the input data into independent chunks, which are then processed by map function and then reduced by similar grouping set of data.

Python

Python is an open source object-oriented programming language which is used for developing the desktop and the web applications. It is also used for developing both complex scientific and numeric applications. It is designed to facilitate virtualization and data analysis. Originally, it is excellent for backend web development, artificial intelligence, data analysis, and scientific computing process.

Hadoop Streaming - Python

Nowadays, major companies prefer their employees to be proficient in Python, because of the versatility of language. As well as, they use API to deal with Big Data Analytics problems using python language. It is very popular programming language that makes the application development simple and easy. Hadoop provides MapReduce applications can built using python.

Hadoop streaming is one of the popular ways to write python on Hadoop. Hadoopy is an extension of Hadoop streaming and uses Python MapReduce jobs. Most developers use Python because it is supporting libraries for data analytics tasks. Using Hadoop Streaming, Python is user-friendly, easy to learn, flexible language and yet powerful for end-to-end latest analytics applications. Python framework available for working with Hadoop such as

• Hadoop Streaming API
• Dumbo
• Mrjob
• Pydoop
• Hadoopy

Applications of Hadoop Streaming In Python

Working with Hadoop using Python is entirely possible with a collection of open source projects which provides APIs to Hadoop Components. Python with Hadoop is utilize to store, process and analyze the large data sets. For these applications, use python to write MapReduce programs to run on a cluster.

The executable reads the standard input from STDIN writes output to STDOUT and produce a result to standard inputs. As well as, there is a number of open source projects that support Hadoop in Python. One of the most important benefits is that we don't have to compile the code, instead use a scripting language.

• It makes more interactive development of analytics.
• Maintain and fixing application in environments.
• More comfortable to read the code.
• Access data analysis libraries such as scipy, nlkt, etc.

In the final analysis, the world is changing the way it is operating currently, and big data is playing an important role. Hadoop is a framework which makes life easy while working on a large set of data.