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Big Data Analytics with Hadoop 3

You're reading from Big Data Analytics with Hadoop 3

Product type Book

Published in May 2018

Publisher Packt

ISBN-13 9781788628846

Pages 482 pages

Edition 1st Edition

Languages

Concepts

Author (1):

Sridhar Alla

Table of Contents (18) Chapters

Title Page

Copyright and Credits

Packt Upsell

Contributors

Preface

Introduction to Hadoop

Overview of Big Data Analytics

Big Data Processing with MapReduce

Scientific Computing and Big Data Analysis with Python and Hadoop

Statistical Big Data Computing with R and Hadoop

Batch Analytics with Apache Spark

Real-Time Analytics with Apache Spark

Batch Analytics with Apache Flink

Stream Processing with Apache Flink

Visualizing Big Data

Introduction to Cloud Computing

Using Amazon Web Services

Index

Cloud characteristics

An IT environment requires a specific set of characteristics to enable the remote provisioning of scalable and measured IT resources in an effective manner. These characteristics need to exist to a meaningful extent for the IT environment to be considered an effective Cloud.

The following six specific characteristics are common to the majority of Cloud environments:

On-demand usage
Ubiquitous access
Multitenancy (and resource pooling)
Elasticity
Measured usage
Resiliency

On-demand usage

A Cloud consumer can unilaterally access Cloud-based IT resources, giving the Cloud consumer the freedom to self-provision these IT resources. Once configured, usage of the self-provisioned IT resources can be automated, reducing human involvement with the Cloud consumer or Cloud provider. This results in an on-demand usage environment. Also known as on-demand self-service usage, this characteristic enables the service-based and usage-driven features found in mainstream Clouds.

Ubiquitous access...

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Authors (1)

Sridhar Alla

Sridhar?Alla?is the co-founder and CTO of Blue Whale Consulting and is expert at helping companies (big and small) define their vision for systems and capabilities that will allow them to establish a strategic execution plan to deal with the ever-growing data collected to support analytics and product teams. He has very experienced at dealing with all aspects of data collection, security, governance, and processing as part of end-to-end big data analytics and machine learning initiatives (including predictive modeling, deep learning, and ML automation). Sridhar?is a published book author and an avid presenter at numerous conferences, including Strata, Hadoop World, and Spark Summit.? He also has several patents filed with the US PTO on large-scale computing and distributed systems.? He has over 18 years' experience writing code in Scala, Java, C, C++, Python, R, and Go, and has extensive hands-on knowledge of Spark, Flink, TensorFlow, Keras, Hadoop, Cassandra, HBase, MongoDB, Riak, Redis, Zeppelin, Mesos, Docker, Kafka, ElasticSearch, Solr, H2O, machine learning, text analytics, distributed computing, and high-performance computing. Sridhar lives with his wife and daughter in New Jersey and in his spare time loves blogging and coaching organizations on next-generation advancements in technology and their alignment with business goals.

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