Hadoop, MapReduce, and HDFS
As discussed in the previous sections, the rapidly increasing data storage, analysis, and process requirements are in the necessity of mining the essential information for business needs from such huge volume of data in storage clusters and data-intensive applications. Scalability, high availability, fault tolerance, data distribution, parallel processing, and load balancing are the expected features of such a system.
These features of big data are addressed by the MapReduce program introduced by Google.
Hadoop
Hadoop is the most prevalent and open source execution of the MapReduce programing model. Apache Hadoop is a scalable and reliable software framework for parallel and distributed computing. Instead of depending on expensive resources for storage and processing huge volume of data, Hadoop allows big data parallel processing on inexpensive commodity hardware. The following diagram represents the components of the Hadoop architecture:
Apache Hadoop contains five...
