Explain the concept of distributed computing and its significance in big data processing.

Distributed computing is a computing paradigm that involves the use of multiple interconnected computers or servers working together to solve complex problems or process large volumes of data. In this concept, tasks are divided among different nodes in a network, and each node performs a portion of the computation independently. The results are then combined to produce the final output. Distributed computing is highly significant in big data processing due to the following reasons: 1. Scalability: Big data processing often involves massive volumes of data that cannot be effectively handled by a single machine. Distributed computing allows for horizontal scalability by adding more nodes to the network, thereby increasing processing power and storage capacity. This scalability enables organizations to handle growing data volumes and meet the demands of ever-expanding data requirements. 2. High Performance: By distributing the workload across multiple nodes, distributed computing can achieve high-performance data processing. Each node works on a portion of the data independently, allowing for parallel execution. This parallelism reduces the overall processing time, enabling faster data analysis and insights. The ability to process data in....