When you consider that there are more than 20 billion devices connected to the Internet today, most all of them generating data, and then think of the massive amounts of data being produced by Web sites, social networks, and other sources, you begin to understand the true implications of BIG DATA. Data is being collected in ever-escalating volumes, at increasingly high velocities, and in a widening variety of formats, and it's being used in increasingly diverse contexts. "Data" used to be something stored in a table in a database, but today it can be a sensor reading, a tweet, a GPS location, or almost anything else. The challenge for information scientists is to make sense of all that data.
A popular tool for analyzing big data is Apache Hadoop. Hadoop is "a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models." It is frequently combined with other open-source frameworks such as Apache Spark, Apache HBase, and Apache Storm to increase its capabilities and performance. Azure HDInsight is the Azure implementation of Hadoop, Spark, HBase, and Storm, with other tools such as Apache Pig and Apache Hive thrown in to provide a comprehensive and high-performance solution for advanced analytics. HDInsight can spin up Hadoop clusters for you using either Linux or Windows as the underlying operating system, and it integrates with popular business-intelligence tools such as Microsoft Excel and SQL Server Analysis Services.
The purpose of this lab is to acquaint you with the process of deploying and running Hadoop clusters provisioned by HDInsight on Linux VMs. Once your Hadoop cluster is running, most of the operations you perform on it are identical to the ones you would perform on hardware clusters running Hadoop.
In this hands-on lab, you will learn how to:
Click here to download a zip file containing the resources used in this lab. Copy the contents of the zip file into a folder on your hard disk.
This hands-on lab includes the following exercises:
Estimated time to complete this lab: 45 minutes.