MapReduce

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Towards Data Science

Simplifying the MapReduce Framework

Introduction to MapReduce

Analytics Vidhya

MapReduce is a programming framework for distributed parallel processing of large jobs. It was first introduced by Google in 2004, and popularized by Hadoop. The primary motivation of MapReduce was…

A MapReduce overview

Towards Data Science

When I first started reading about MapReduce, nearly every tutorial intro’d with a Java or C++ prerequisite reminder. Yet there’s also the outdated (and increasingly sparse) mindset in the tech world…...

A Beginners Introduction into MapReduce

Towards Data Science

Many times, as Data Scientists, we have to deal with huge amount of data. In those cases, many approaches won’t work or won’t be feasible. A massive amount of data is good, it’s very good, and we…

Processing Data At Scale With MapReduce

Towards Data Science

In the current market landscape, organizations must engage in data-driven decision-making to maintain competitiveness and foster innovation. As a result, an immense amount of data is collected on a da...

MapReduce for Idiots

Pete Warden's blog

Photo by Stuart Pilbrow I'll admit it, I was intimidated by MapReduce. I'd tried to read explanations of it, but even the wonderful Joel Spolsky left me scratching my head. So I plowed ahead trying to...

MapReduce for Idiots: The Musical

Pete Warden's blog

MapReduce for Idiots I've just uploaded an audio slideshow of the talk I gave at Gnip last week, covering why MapReduce really isn't scary and why you should be looking into it for your problems. I'll...

Understanding MapReduce

Better Programming

MapReduce is a computing model for processing big data with a parallel, distributed algorithm on a cluster. It was invented by Google and has been largely used in the industry since 2004. Many…

Series on Distributed Computing 1: MapReduce

Towards Data Science

A simple explanation of how to run parallel workloads to process big data

MapReduce with Python

Python in Plain English

MapReduce with Python is a programming model. It allows big volumes of data to be processed and created by dividing work into independent tasks. It further enables performing the tasks in parallel…

Understanding MapReduce with the Help of Harry Potter

Towards Data Science

MapReduce is an algorithm that allows large data sets to be processed in parallel, i.e. on multiple computers simultaneously. This greatly accelerates queries for large data sets. MapReduce was…

MapReduce: Simplified Data Processing on Large Clusters

Level Up Coding

MapReduce is an interface that enables automatic parallelization and distribution of large-scale computation while abstracting over “the messy details of parallelization, fault-tolerance, data…

Elastic MapReduce Tips

Pete Warden's blog

Photo by Tofslie Amazon's Elastic MapReduce service is a god-send for anyone running big data-processing jobs. It takes the pain and suffering out of configuring Hadoop, and lets you run hundreds of m...

Netezza shows there’s more than one way to handle Big Data

Pete Warden's blog

Photo by Nick Dimmock As you may have noticed I'm a strong advocate of MapReduce, Hadoop and NoSQL, but I'm not blind to their limits. They're perfect for my needs primarily because they're dirt-cheap...

Understand MapReduce Intuitively

Towards Data Science

How big is big data, really? According to Rionaldi Chandraseta, his experience when working with big data was 128 petabytes. This amount of data is truly incomprehensible. I recommend reading his…

The Hadoop Ecosystem

Analytics Vidhya

Hadoop is a java-based big data analytics tool used to fill the voids and pitfalls in the traditional approach when there is voluminous data. It is an open source framework for storing data and…

What is MapReduce good for?

Pete Warden's blog

I’m working on a video series for O’Reilly that aims to de-mystify Hadoop and MapReduce, explaining how mere mortals can analyze massive data sets. I’m recording the first drafts of my segments now, a...

The Basics of Hadoop

Analytics Vidhya

Hadoop is an Apache open-source framework written in java that allows distributed processing of large datasets across clusters of computers using simple programming models. You may know that big tech…...

A Simple MapReduce in Go

Level Up Coding

Hadoop MapReduce is a software framework for easily writing applications that process vast amounts of data (multi-terabyte data-sets) in-parallel on large clusters (thousands of nodes) of commodity…

My ‘Introduction to MapReduce’ video is now available

Pete Warden's blog

For a while now I've been visiting companies and doing a 'brown bag' lunch, where I gather a bunch of engineers and database people, and walk them through writing their own simple MapReduce jobs in Py...

From Hadoop to Spark: An In-Depth Look at Distributed Computing Frameworks

Level Up Coding

Big Data in Action: Use Cases and Case Studies of Distributed Computing Continue reading on Level Up Coding

The World of Hadoop

Towards Data Science

When learning Hadoop, one of the biggest challenges I had was to put different components of the Hadoop ecosystem together and create a bigger picture. It’s a huge system which comprises of different…...

Getting Started with PySpark

Analytics Vidhya

In the last decade, there has been unprecedented demand for fast and reliable tools to handle and process the streaming of big data. One of the ways to tackle this is MapReduce- however, that does…

Introduction to Apache Spark

Analytics Vidhya

Today’s world runs on data, generating Terabytes of data every single day. Conventional systems are turning outdated overnight, with big data systems becoming a necessity. While we can argue that…