Ulteriori informazioni
Analysis of so-called "Big Data" is becoming increasingly important for the competitive advantage it confers to businesses as they increasingly base decisions upon hidden trends and other factors that are teased out by successful application of statistics. Beginning Big Data with Java is written for Java programmers who want to build their skill set in this burgeoning and profitable new area.
Beginning Big Data with Java begins with the big picture and then quickly moves into getting set up with a productive development environment and toolset. You'll learn about NoSQL technologies and the advantages they confer. You'll learn about Hadoop, and how to run MapReduce processing locally on your desktop or server hardware. Then take it to the cloud where you can scale your processing to new heights using EC2 servers and S3 storage from Amazon Web Services, and also Google's App Engine. Today's cloud-providers give the ability to parallelize Big Data processing well beyond what many businesses can support in house.
But what if you do want to run your processing in house? Beginning Big Data with Java has you covered there too, with a solid chapter on creating your own, in house private cloud. Whatever your needs, Beginning Big Data with Java is the right book to get you started in applying your Java knowledge to the fast-growing field of Big Data analysis.
Shows the value from NoSQL data stores
Adds Big Data analysis to your Java-based skillset
Extends your range through scalability in the cloud
Info autore
Andrew Patzer is a web architect for a consulting firm located in the Midwest. His first book, Professional Java Server Programming, is a bestseller and one of the first books to cover J2EE technologies. Andrew served as a lead systems architect for an industry-leading application service provider in the insurance industry. He was directly involved in designing and building a J2EE development framework upon which the company's key product was built. Andrew has delivered several presentations over the years to both local user groups and national conferences.
