Real-time data processing

Real-time data processing has become increasingly critical in today’s fast-paced and data-driven world. Organizations need to analyze and derive insights from data as it arrives, enabling them to make timely decisions and take immediate action. Spark Streaming, a powerful component of Apache Spark, addresses this need by providing a scalable and fault-tolerant framework to process real-time data streams.

Real-time data processing has gained immense importance in various industries, ranging from finance and e-commerce to the Internet of Things (IoT) and social media. Traditional batch processing approaches, while suitable for many scenarios, fall short when immediate insights and actions are required. Real-time data processing fills this gap by enabling the analysis and processing of data as it arrives, allowing organizations to make timely decisions and respond quickly to changing conditions.

Real-time data processing involves the continuous ingestion...