![]() ![]() ![]() We are going to install Spark 1.6.0 as standalone in a computer with a 32-bit Windows 10 installation (my very old laptop). Spark runs on Hadoop, Mesos, in the cloud or as standalone. It is possible to write Spark applications using Java, Python, Scala and R, and it comes with built-in libraries to work with structure data ( Spark SQL), graph computation ( GraphX), machine learning ( MLlib) and streaming ( Spark Streaming). A few words about Apache SparkĪpache Spark is making a lot of noise in the IT world as a general engine for large-scale data processing, able to run programs up to 100x faster than Hadoop MapReduce, thanks to its in-memory computing capabilities. ![]() The new version of these VMs come with Spark ready to use. If you really want to build a serious prototype, I strongly recommend to install one of the virtual machines I mentioned in this post a couple of years ago: Hadoop self-learning with pre-configured Virtual Machines or to spend some money in a Hadoop distribution on the cloud. This post is to help people to install and run Apache Spark in a computer with window 10 (it may also help for prior versions of Windows or even Linux and Mac OS systems), and want to try out and learn how to interact with the engine without spend too many resources. ![]()
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