Sridhar Alla - Big Data Analytics with Hadoop 3

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Sridhar Alla is a big data expert helping companies solve complex problems in distributed computing, large scale data science and analytics practice. He presents regularly at several prestigious conferences and provides training and consulting to companies. He holds a bachelor's in computer science from JNTU, India.

He loves writing code in Python, Scala, and Java. He also has extensive hands-on knowledge of several Hadoop-based technologies, TensorFlow, NoSQL, IoT, and deep learning.

V. Naresh Kumar has more than a decade of professional experience in designing, implementing, and running very large-scale internet applications in Fortune 500 Companies. He is a full-stack architect with hands-on experience in e-commerce, web hosting, healthcare, big data, analytics, data streaming, advertising, and databases. He admires open source and contributes to it actively. He keeps himself updated with emerging technologies, from Linux system internals to frontend technologies. He studied in BITS- Pilani, Rajasthan, with a joint degree in computer science and economics.

Manoj R. Patil is a big data architect at TatvaSoftan IT services and consulting firm. He has a bachelor's degree in engineering from COEP, Pune. He is a proven and highly skilled business intelligence professional with 18 years, experience in IT. He is a seasoned BI and big data consultant with exposure to all the leading platforms.

Previously, he worked for numerous organizations, including Tech Mahindra and Persistent Systems. Apart from authoring a book on Pentaho and big data, he has been an avid reviewer of various titles in the respective fields from Packt and other leading publishers.

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Apache Hadoop is the most popular platform for big data processing, and can be combined with a host of other big data tools to build powerful analytics solutions. Big Data Analytics with Hadoop 3 shows you how to do just that, by providing insights into the software as well as its benefits with the help of practical examples.

Once you have taken a tour of Hadoop 3's latest features, you will get an overview of HDFS, MapReduce, and YARN, and how they enable faster, more efficient big data processing. You will then move on to learning how to integrate Hadoop with open source tools, such as Python and R, to analyze and visualize data and perform statistical computing on big data. As you become acquainted with all of this, you will explore how to use Hadoop 3 with Apache Spark and Apache Flink for real-time data analytics and stream processing. In addition to this, you will understand how to use Hadoop to build analytics solutions in the cloud and an end-to-end pipeline to perform big data analysis using practical use cases.