Single node cluster means only one DataNode running and setting up all the NameNode, DataNode, ResourceManager and NodeManager on a single machine. It can easily and efficiently the sequential workflow in a smaller environment as compared to large environments which contains terabytes of data distributed across hundreds of machines.
What is Big Data? What size of Data is considered to be big and will be termed as Big Data? We have many relative assumptions for the term Big Data. It is possible that, the amount of data say 50 terabytes can be considered as Big Data for Startup’s but it may not be Big Data for the companies like Google and Facebook. It is because they have infrastructure to store and process this vast amount of data. Apache Hadoop and Apache Spark are both Big Data analytics frameworks they provide some of the most popular tools used to carry out common Big Data-related tasks.
The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage.
Rather than rely on hardware to deliver high-availability, the library itself is designed to detect and handle failures at the application layer. So delivering a highly-available service on top of a cluster of computers, each of which may be prone to failures.
This describes how to setup and configure a cluster-node Hadoop installation so that you can quickly perform simple operations using Hadoop MapReduce and the Hadoop Distributed File System (HDFS).