Platform for data processing

A data processing architecture requires a lot of technologies and tools for jobs scheduling until data streaming. A few years ago, installing all the tools required for data processing. Now we may implement the entire environment in just one step. Data companies such as Cloudera, Hortonworks, and MapR provide us with a complete setup of data environment in a Virtual Machine for a single-node cluster and a Docker container (automates the deployment of Linux applications inside software containers) for multi-node cluster.

Many data analytics applications need to process large datasets in batch post-processing or live streaming. For a data scientist, the time to set up a complete environment is a priority, and installing a ready setup platform is the best way to get hands on into the action. One of the main advantages here is that if you are working with either a single-node cluster or a multi-node cluster, the programming of Apache Spark projects are independent...