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This book is a guide for developers and engineers to use Hadoop and Hive for scalable big data applications. It covers reading, writing, and managing large datasets with Hive and provides a concise introduction to Apache Hadoop and Hive, detailing their collaboration to simplify development. Through clear examples, the book explains the logic, code, and configurations needed for building successful distributed applications.
The course starts with an introduction to big data and Apache Hadoop fundamentals. It then covers the Hadoop Distributed Filesystem and how to get started with Hadoop. The journey continues with interfaces to access HDFS files, resource management with Yet Another Resource Negotiator, and MapReduce for data processing. The book also explores Hive architecture, storage types, and the Hive query language.
Mastering these concepts is vital for creating scalable big data solutions. This book ensures a smooth transition from novice to proficient Hadoop and Hive user, providing practical skills and comprehensive knowledge. By the end, readers will be able to set up, configure, and optimize Hadoop, utilize Hive for data management, and effectively solve big data challenges.
The course starts with an introduction to big data and Apache Hadoop fundamentals. It then covers the Hadoop Distributed Filesystem and how to get started with Hadoop. The journey continues with interfaces to access HDFS files, resource management with Yet Another Resource Negotiator, and MapReduce for data processing. The book also explores Hive architecture, storage types, and the Hive query language.
Mastering these concepts is vital for creating scalable big data solutions. This book ensures a smooth transition from novice to proficient Hadoop and Hive user, providing practical skills and comprehensive knowledge. By the end, readers will be able to set up, configure, and optimize Hadoop, utilize Hive for data management, and effectively solve big data challenges.