This book is a practical guide on using the Apache Hadoop projects including MapReduce, HDFS, Apache Hive, Apache HBase, Apache Kafka, Apache Mahout and Apache Solr. From setting up the environment to running sample applications each chapter is a practical tutorial on using a Apache Hadoop ecosystem project. While several books on Apache Hadoop are available, most are based on the main projects MapReduce and HDFS and none discusses the other Apache Hadoop ecosystem projects and how these all work together as a cohesive big data development platform. What you'll learn How to set up environment in Linux for Hadoop projects using Cloudera Hadoop Distribution CDH 5. How to run a MapReduce job How to store data with Apache Hive, Apache HBase How to index data in HDFS with Apache Solr How to develop a Kafka messaging system How to develop a Mahout User Recommender System How to stream Logs to HDFS with Apache Flume How to transfer data from MySQL database to Hive, HDFS and HBase with Sqoop How create a Hive table over Apache Solr Who this book is for: The primary audience is Apache Hadoop developers. Pre-requisite knowledge of Linux and some knowledge of Hadoop is required.
Index Terms
- Practical Hadoop Ecosystem: A Definitive Guide to Hadoop-Related Frameworks and Tools
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SACMAT '17 Abstracts: Proceedings of the 22nd ACM on Symposium on Access Control Models and TechnologiesApache Hadoop is a predominant software framework to store and process vast amount of data, produced in varied formats. Data stored in Hadoop multi-tenant data lake often includes sensitive data such as social security numbers, intelligence sources and ...