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As of the year 2012, clusters that are big are in the 100 Petabyte range.īig Data can be both structured and unstructured. The examples in this article use small samples to illustrate the capabilities of the technology. Using Big Data technology is not restricted to large volumes. There is so much hype in this space that there could be an extended debate just about the definition of big data. These factors make Big Data difficult to capture, mine, and manage using traditional methods. If you are doing the exercises without network connectivity, use the MySQL examples.īig Data is large in quantity, is captured at a rapid rate, and is structured or unstructured, or some combination of the above. There is a MySQL instance built into the VMWare image.Jump to the section that contains the code samples.Download the VMWare image from the Cloudera Website and increase the virtual machine RAM setting to 1.5 GB.For the super impatient, if you can already define Hadoop and want to get right to working on the code samples, then do the following.How can I get started with Big Data? What are some easy examples that run on a single PC?.How does Hadoop relate to IBM DB2 and Informix? Can these technologies play together?.What is Big Data, Hadoop, Sqoop, Hive, and Pig, and why is there so much excitement in this space?.Specifically let's focus on the following questions. This article will provide a working definition of Big Data and then work through a series of examples so you can have a first-hand understanding of some of the capabilities of Hadoop, the leading open source technology in the Big Data domain.

There is a lot of excitement about Big Data and a lot of confusion to go with it.

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