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Programming Hive
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From the early days of the Internet’s mainstream breakout, the major search engines and ecommerce companies wrestled with ever-growing quantities of data. More recently, social networking sites experienced the same problem. Today, many organizations realize that the data they gather is a valuable resource for understanding their customers, the performance of their business in the marketplace, and the effectiveness of their infrastructure. The Hadoop ecosystem emerged as a cost-effective way of working with such large data sets. It imposes a particular programming model, called Map Reduce, for breaking up computation tasks into units that can be distributed around a cluster of commodity, server class hardware, thereby providing cost-effective, horizontal scalability. Under- neath this computation model is a distributed file system called the Hadoop Distributed Filesystem (HDFS). Although the filesystem is “pluggable,” there are now several commercial and open source alternatives.
Edward Capriolo, Dean Wampler, and Jason Rutherglen - Personal Name
978-1-449-31933-5
NONE
Information Technology
English
2012
1-350
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