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You're reading from Apache Spark for Data Science Cookbook

Product typeBook

Published inDec 2016

Publisher

ISBN-139781785880100

Edition1st Edition

Tools

Apache Spark Pandas

Concepts

Data Science

Author (1)

Padma Priya Chitturi

Introduction

Apache Spark is a general-purpose distributed computing engine for large-scale data processing. It is an open source initiative from AMPLab and donated to the Apache Software Foundation. It is one of the top-level projects under the Apache Software Foundation. Apache Spark offers a data abstraction called Resilient Distributed Datasets (RDDs) to analyze the data in parallel on top of a cluster of resources. The Apache Spark framework is an alternative to Hadoop MapReduce. It is up to 100X faster than MapReduce and offers the best APIs for iterative and expressive data processing. This project is written in Scala and it offers client APIs in Scala, Java, Python, and R.

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Apache Spark for Data Science Cookbook

Published in: Dec 2016Publisher: ISBN-13: 9781785880100

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Author (1)

Padma Priya Chitturi

Padma Priya Chitturi is Analytics Lead at Fractal Analytics Pvt Ltd and has over five years of experience in Big Data processing. Currently, she is part of capability development at Fractal and responsible for solution development for analytical problems across multiple business domains at large scale. Prior to this, she worked for an Airlines product on a real-time processing platform serving one million user requests/sec at Amadeus Software Labs. She has worked on realizing large-scale deep networks (Jeffrey deans work in Google brain) for image classification on the big data platform Spark. She works closely with Big Data technologies such as Spark, Storm, Cassandra and Hadoop. She was an open source contributor to Apache Storm.
Read more about Padma Priya Chitturi

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