• Integrate Storm with other Big Data technologies like Hadoop, HBase, and Apache Kafka
• Explore log processing and machine learning using Storm
• Step-by-step and easy-to-understand guide to...

• Learn how to optimize Hadoop MapReduce, Pig and Hive
• Dive into YARN and learn how it can integrate Storm with Hadoop
• Understand how Hadoop can be deployed on the cloud...

• Develop a machine learning system with Spark's MLlib and scalable algorithms
• Deploy Spark jobs to various clusters such as Mesos, EC2, Chef, YARN, EMR, and so on
• This is a...

Re-architect relational applications to NoSQL, integrate relational database management systems with the Hadoop ecosystem, and transform and migrate relational data to and from Hadoop components. This book covers the best-practice design approaches to re-architecting your relational applications and transforming your relational data to...

• Comprehensive coverage of key topics in machine learning with an emphasis on both the theoretical and practical aspects
• More than 15 open source Java tools...

• Write complex processing job codes easily with the help of clear and step by...

A blueprints book with 10 different projects built in 10 different chapters which demonstrate the various use cases of storm for both beginner and intermediate users, grounded in real-world example applications.

Although the book focuses primarily on Java development with Storm, the patterns are more broadly applicable and...

Dive into the world of SQL on Hadoop and get the most out of your Hive data warehouses. This book is your go-to resource for using Hive: authors Scott Shaw, Ankur Gupta, David Kjerrumgaard, and Andreas Francois Vermeulen take you through learning HiveQL, the SQL-like language specific to Hive, to analyze, export, and massage the data stored...