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Big Data Analytics with Spark - A Practitioner's Guide to Using Spark for Large Scale Data Analysis (Paperback, 1st ed.)
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Big Data Analytics with Spark - A Practitioner's Guide to Using Spark for Large Scale Data Analysis (Paperback, 1st ed.)
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Big Data Analytics with Spark is a step-by-step guide for learning
Spark, which is an open-source fast and general-purpose cluster
computing framework for large-scale data analysis. You will learn
how to use Spark for different types of big data analytics
projects, including batch, interactive, graph, and stream data
analysis as well as machine learning. In addition, this book will
help you become a much sought-after Spark expert. Spark is one of
the hottest Big Data technologies. The amount of data generated
today by devices, applications and users is exploding. Therefore,
there is a critical need for tools that can analyze large-scale
data and unlock value from it. Spark is a powerful technology that
meets that need. You can, for example, use Spark to perform low
latency computations through the use of efficient caching and
iterative algorithms; leverage the features of its shell for easy
and interactive Data analysis; employ its fast batch processing and
low latency features to process your real time data streams and so
on. As a result, adoption of Spark is rapidly growing and is
replacing Hadoop MapReduce as the technology of choice for big data
analytics. This book provides an introduction to Spark and related
big-data technologies. It covers Spark core and its add-on
libraries, including Spark SQL, Spark Streaming, GraphX, and MLlib.
Big Data Analytics with Spark is therefore written for busy
professionals who prefer learning a new technology from a
consolidated source instead of spending countless hours on the
Internet trying to pick bits and pieces from different sources. The
book also provides a chapter on Scala, the hottest functional
programming language, and the program that underlies Spark. You'll
learn the basics of functional programming in Scala, so that you
can write Spark applications in it. What's more, Big Data Analytics
with Spark provides an introduction to other big data technologies
that are commonly used along with Spark, like Hive, Avro, Kafka and
so on. So the book is self-sufficient; all the technologies that
you need to know to use Spark are covered. The only thing that you
are expected to know is programming in any language. There is a
critical shortage of people with big data expertise, so companies
are willing to pay top dollar for people with skills in areas like
Spark and Scala. So reading this book and absorbing its principles
will provide a boost-possibly a big boost-to your career.
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