Definition
A Hadoop cluster is a collection of commodity hardware nodes or servers that form a distributed computing infrastructure.
It facilitates parallel data processing across multiple nodes, enabling efficient storage, recovery, and analysis of big datasets.
Mike Cafarella and Doug Cutting designed Hadoop in 2005 as an open-source implementation of the Google File System (GFS) and Google’s MapReduce programming approach.
Named after Cutting’s son’s toy elephant, the project quickly gained popularity as a scalable and affordable way of processing complex datasets. Yahoo implemented Hadoop in 2006 for its search engine infrastructure.
Hadoop Clusters Application
- Genomic analysis: Hadoop clusters process and analyze genomic data in bioinformatics.
- Big data analytics: Hadoop clusters process and analyze vast datasets from multiple sources.
- Machine learning: They support training and deploying machine learning models on big datasets, enabling advanced analytics and AI applications.
- Data warehousing: They can act as efficient data warehouses to store and query structured and unstructured data, and in some instances, they can replace traditional relational databases.
- Log processing: Hadoop clusters assist with troubleshooting, security evaluation, and performance monitoring by executing logs created by web servers, applications, and network devices.