Apache Hadoop Services
Hadoop is an open-source software framework that can process large amounts of data in a distributed cluster. Hadoop offers several use cases that allow the processing of big data with normal standard hardware. It is also highly scalable from one server to several server farms, with each cluster running on its own computing and storage. Hadoop offers high application layer availability, so cluster hardware can be unavailable and these nodes are easily interchangeable and inexpensive.
The main Apache Hadoop framework consists of the following modules:
- Hadoop Common -Contains libraries and utilities needed by other Hadoop modules.
- Hadoop Distributed File System (HDFS) – A distributed file system that stores data on a standard computer and offers very high shared bandwidth across clusters.
- Hadoop YARN -Platform responsible for managing cluster computing resources and using it to plan customer applications
- Hadoop MapReduce – Implementation of the MapReduce programming model for extensive data processing
The company is now targeting Hadoop vendors – a growing community that provides credible features, tools, and innovations for temporary commercial big data solutions for Hadoop.
Benefits for using Hadoop
- Hadoop framework allows the user to quickly write and test distributed systems. It is efficient, and it automatically distributes the data and works across the machines and in turn, utilizes the underlying parallelism of the CPU cores.
- Hadoop does not rely on hardware to provide fault-tolerance and high availability (FTHA), rather the Hadoop library itself has been designed to detect and handle failures at the application layer.
- Servers can be added or removed from the cluster dynamically and Hadoop continues to operate without interruption.
- Another big advantage of Hadoop is that apart from being open source, it is compatible with all the platforms since it is Java-based.