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Note For more details on running Spark Notebooks, see my article on the subject in the _Cookbook_ ( __ ). # Spark Essentials If you have not used Spark before, you will need to get a feel for the basics. This chapter includes the following sections: * Section 1 Understanding what Spark is * Section 2 Understanding what the big picture looks like * Section 3 Learning more about Spark components # Understanding what Spark is Spark is a platform for managing big data. It helps you to manage data from Hadoop in various formats, run machine learning algorithms on it, and so on. Spark can be installed on your local computer or on a cluster of computers that you have set up on the Internet. The cluster might be very big; on the Internet, you can even have hundreds of thousands of computers set up to run Spark. ## How big is big data? Big data is data that is extremely large and complex. Data sets can become very large because of the sheer volume of data, data streams, and data generated by human activity. Big data involves storing large amounts of data—and accessing that data—at the speed of today's computers. The following are different types of big data: * Real-time data sources * Distributed systems * Streaming * Machine learning ## Real-time data sources Real-time data is data that needs to be processed as it is received. This data comes from various sources and can be generated by multiple sources in a single system. Examples of real-time data include stock prices from various financial markets, various time-series data

 

 

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