Following are some of the most popular data processing technologies, which help you to perform transformation and processing for a large amount of data:
- Apache Hadoop uses a distributed processing architecture in which a task is mapped to a cluster of commodity servers for processing. Each piece of work distributed to the cluster servers can be run or re-run on any of the servers. The cluster servers frequently use HDFS to store data locally for processing. In the Hadoop framework, Hadoop takes a big job, splits it into discrete tasks, and processes them in parallel. It allows for massive scalability across an enormous number of Hadoop clusters. It's also designed for fault tolerance, where each of the worker nodes periodically reports its status to a master node, and the master node can redistribute work from a cluster that doesn't respond positively. Some of the most popular frameworks used with Hadoop are Hive, Presto,...
