Big Data Processing Concepts

Big data is a fundamental aspect of modern data-driven decision making. To derive insights from this vast amount of data, it needs to be processed, analyzed, and stored using advanced technologies and techniques. This chapter delves into the key concepts and technologies involved in big data processing.

Introduction to distributed computing

Distributed computing is a model of computing that involves using multiple computers or devices to work together on a common task, using a network to communicate and coordinate their efforts. It is a system of software components spread across multiple nodes but works as a single entity. Cloud computing is one example of distributed computing, but other examples include content delivery networks, distributed databases, and distributed file systems.

Components of distributed computing

• Nodes: These are individual computers or devices on a network that can perform their own computing and share resources.

• Shared resources: This refers to anything that can be accessed remotely and used by the nodes, including hardware and software.

• Distributed transparency: This is a component that hides the complexities of distributed systems, making them appear as a single entity to users.

• Distribution of resources: This involves managing how resources are allocated and distributed across multiple nodes.

• Failover: This is a component that automatically switches to a backup node in case of failure, ensuring system availability and minimizing downtime.

• Replication: This component involves creating redundant copies of data or processes across multiple nodes ...