Hadoop Essentials - Tackling the Challenges of Big Data with Hadoop (Community Experience Distilled)

Hadoop Essentials - Tackling the Challenges of Big Data with Hadoop (Community Experience Distilled)
English | April 29, 2015 | ISBN: 1784396680 | 172 pages | PDF | 15 Mb

Key FeaturesGet to grips with the most powerful tools in the Hadoop ecosystem, including Storm and SparkLearn everything you need to take control of Big DataA fast-paced journey through the key features of HadoopBook Description
This book jumps into the world of Hadoop and its tools, to help you learn how to use them effectively to optimize and improve the way you handle Big Data.
Starting with the fundamentals Hadoop YARN, MapReduce, HDFS, and other vital elements in the Hadoop ecosystem, you will soon learn many exciting topics such as MapReduce patterns, data management, and real-time data analysis using Hadoop. You will also explore a number of the leading data processing tools including Hive and Pig, and learn how to use Sqoop and Flume, two of the most powerful technologies used for data ingestion. With further guidance on data streaming and real-time analytics with Storm and Spark, Hadoop Essentials is a reliable and relevant resource for anyone who understands the difficulties - and opportunities - presented by Big Data today.
With this guide, you'll develop your confidence with Hadoop, and be able to use the knowledge and skills you learn to successfully harness its unparalleled capabilities.
What you will learnGet to grips with the fundamentals of Hadoop, and tools such as HDFS, MapReduce, and YARNLearn how to use Hadoop for real-world Big Data projectsImprove the performance of your Big Data architectureFind out how to get the most from data processing tools such as Hive and PigLearn how to unlock real-time Big Data analytics with Apache SparkAbout the Author
Shiva Achari has more than 8 years of extensive industry experience and is currently working as a Big Data Architect consultant with companies such as Oracle and Teradata. Over the years, he has architected, designed, and developed multiple innovative and high-performance large-scale solutions, such as distributed systems, data centers, big data management tools, SaaS cloud applications, Internet applications, and Data Analytics solutions.
Table of ContentsIntroduction to Big Data and HadoopHadoop EcosystemPillars of Hadoop – HDFS, MapReduce, and YARNData Access Components – Hive and PigStorage Component – HBaseData Ingestion in Hadoop – Sqoop and FlumeStreaming and Real-time Analysis – Storm and Spark

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