Hadoop Ecosystem, YARN, NoSQL, MongoDB, Spark & Scala Guide

Dive into the world of big data with the comprehensive guide 'Hadoop Ecosystem, YARN, NoSQL, MongoDB, Spark & Scala Guide.' In Chapter 1, explore the intricacies of the Hadoop ecosystem and YARN, covering components, HDFS, MapReduce, YARN, PIG, HIVE, schedulers, failover, fencing, and HDFS federation. Chapter 2 introduces NoSQL databases, providing insights into different types, including document databases, key-value stores, column-oriented databases, and graph databases. Chapter 3 delves into MongoDB, offering an in-depth understanding of its introduction, data types, document creation, updating, deletion, querying, indexing, and capped collections. Moving to Chapter 4, embark on the journey of Spark, from installation to Spark applications, Resilient Distributed Databases, the anatomy of a Spark job run, and Spark on YARN. Uncover different deployment modes across the cluster. Finally, Chapter 5 introduces SCALA, exploring its features, classes, objects, constructors, implicit classes, mutable variables, basic types, operators, exception handling, match expressions, functions, closures, and inheritance.

Autorentext
Dr. Jaya SinhaDepartment of CSE, Galgotias College of Engineering and Technology, Greater Noida, India.Mr. T. AkilanDepartment of IQAC, Amity University Kolkata, West Bengal.Ms. ChandraprabhaDepartment of CSE, Galgotias College of Engineering and Technology, Greater Noida, India.

Klappentext

Dive into the world of big data with the comprehensive guide 'Hadoop Ecosystem, YARN, NoSQL, MongoDB, Spark & Scala Guide.' In Chapter 1, explore the intricacies of the Hadoop ecosystem and YARN, covering components, HDFS, MapReduce, YARN, PIG, HIVE, schedulers, failover, fencing, and HDFS federation. Chapter 2 introduces NoSQL databases, providing insights into different types, including document databases, key-value stores, column-oriented databases, and graph databases. Chapter 3 delves into MongoDB, offering an in-depth understanding of its introduction, data types, document creation, updating, deletion, querying, indexing, and capped collections. Moving to Chapter 4, embark on the journey of Spark, from installation to Spark applications, Resilient Distributed Databases, the anatomy of a Spark job run, and Spark on YARN. Uncover different deployment modes across the cluster. Finally, Chapter 5 introduces SCALA, exploring its features, classes, objects, constructors, implicit classes, mutable variables, basic types, operators, exception handling, match expressions, functions, closures, and inheritance.