Data Analytics with Hadoop

Dive into the world of big data with 'Data Analytics with Hadoop,' a practical guide that shifts the focus from deployment and operations to the analyses you can build. This book is tailored for data scientists and analysts, offering insights into data warehousing techniques and advanced data workflows that the Hadoop ecosystem can produce. You'll learn how to perform a wide range of techniques, from writing MapReduce and Spark applications with Python to using advanced modeling and data management with Spark MLlib, Hive, and HBase. The book also covers the analytical processes and data systems available to build and empower data products that can handle huge amounts of data./n/nIn this comprehensive guide, you'll understand the core concepts behind Hadoop and cluster computing, and learn design patterns and parallel analytical algorithms to create distributed data analysis jobs. You'll also explore data management, mining, and warehousing in a distributed context using Apache Hive and HBase, and learn how to ingest data from relational databases using Sqoop and Apache Flume. Additionally, you'll discover how to program complex Hadoop and Spark applications with Apache Pig and Spark DataFrames, and perform machine learning techniques such as classification, clustering, and collaborative filtering with Spark’s MLlib.