Apache Hadoop 3 Quick Start Guide:Learn about big data processing and analytics


Apache Hadoop 3 Quick Start Guide:Learn about big data processing and analytics
Authors:Hrishikesh Vijay Karambelkar
ISBN-10 书号:1788999835
ISBN-13 书号:9781788999830
Release Finelybook 出版日期:2018-10-31
pages 页数:220 pages
Publisher Finelybook 出版社:Packt


Book Description
Apache Hadoop is a widely used distributed data platform. It enables large datasets to be efficiently processed instead of using one large computer to store and process the data. This book will get you started with the Hadoop ecosystem, and introduce you to the main technical topics, including MapReduce, YARN, and HDFS.

The book begins with an overview of big data and Apache Hadoop. Then, you will set up a pseudo Hadoop development environment and a multi-node enterprise Hadoop cluster. You will see how the parallel programming paradigm, such as MapReduce, can solve many complex data processing problems.

The book also covers the important aspects of the big data software development lifecycle, including quality assurance and control, performance, administration, and monitoring.

You will then learn about the Hadoop ecosystem, and tools such as Kafka, Sqoop, Flume, Pig, Hive, and HBase. Finally, you will look at advanced topics, including real time streaming using Apache Storm, and data analytics using Apache Spark.

By the end of the book, you will be well versed with different configurations of the Hadoop 3 cluster.

Contents
1:HADOOP 3.0 – BACKGROUND AND INTRODUCTION
2:PLANNING AND SETTING UP HADOOP CLUSTERS
3:DEEP DIVE INTO THE HADOOP DISTRIBUTED FILE SYSTEM
4:DEVELOPING MAPREDUCE APPLICATIONS
5:BUILDING RICH YARN APPLICATIONS
6:MONITORING AND ADMINISTRATION OF A HADOOP CLUSTER
7:DEMYSTIFYING HADOOP ECOSYSTEM COMPONENTS
8:ADVANCED TOPICS IN APACHE HADOOP
What You Will Learn
Store and analyze data at scale using HDFS, MapReduce and YARN
Install and configure Hadoop 3 in different modes
Use Yarn effectively to run different applications on Hadoop based platform
Understand and monitor how Hadoop cluster is managed
Consume streaming data using Storm, and then analyze it using Spark
Explore Apache Hadoop ecosystem components, such as Flume, Sqoop, HBase, Hive, and Kafka
Authors
Hrishikesh Karambelkar
Hrishikesh Karambelkar is a software architect with a blend of entrepreneurial and professional experience. His core expertise involves working with multiple technologies such as Apache Hadoop and Solr, and architecting new solutions for the next generation of a product line for his organization. He has published various research papers in the domains of graph searches in databases at various international conferences in the past. On a technical note, Hrishikesh has worked on many challenging problems in the industry involving Apache Hadoop and Solr.


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