What is Clustered Computing in Big data?
To handle big data individual computers are often inadequate when it comes to storage and compute requirements. Node is a single computer and cluster is a bunch of them together.
Clustering helps in combining resources of smaller machines:
1. Resource pooling: Storage, CPU & Memory
2. High availability: Varying levels of fault tolerance to prevent failures
3. Easy scalability: Add machines horizontally
Manual & Automatic cluster examples: Veritas, Linux natic clusters, IBM AIX bases clusters.
One also needs solutions to manage cluster membership, resource sharing & scheduling work on individual nodes. Hadoop's YARN or Apache Mesos.
The cluster acts as a foundation layer for other processing software.
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