Hadoop Distributed File System

Hadoop Basics is a comprehensive guide to understanding Hadoop, a powerful framework for processing large-scale data. The book begins by introducing Hadoop's core components: the Hadoop Distributed File System (HDFS) and MapReduce, which together enable scalable and fault-tolerant data storage and processing. It explains the architecture of Hadoop, including the master-slave model where the NameNode manages metadata and DataNodes store actual data. The book covers setting up Hadoop clusters in both pseudo-distributed and fully distributed modes. It also delves into key Hadoop ecosystem tools like Apache Hive and Apache Pig for data querying and analysis. Additionally, it explores best practices for data management, including data ingestion and storage strategies. The guide provides practical examples and hands-on exercises to help readers gain experience in Hadoop operations. Overall, Hadoop Basics offers a solid foundation for anyone looking to harness the power of Hadoop for big data processing.

Autorentext

Dr. Usharani Bhimavarapu is an Associate Professor at Koneru Lakshmaiah Education Foundation in Andhra Pradesh, India, where she teaches Computer Science and Engineering. With a career spanning 17 years, she has become a respected authority in Data Mining, Machine Learning, and Data Structure.