Advanced Real Time Data Integration Apache Kafka And Spark Streaming Techniques
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Advanced Real-Time Data Integration: Apache Kafka and Spark Streaming Techniques
Unlock the potential of cutting-edge real-time data processing with "Advanced Real-Time Data Integration: Apache Kafka and Spark Streaming Techniques." This comprehensive guide serves as your gateway to mastering two pivotal technologies in the world of data integration. Perfect for software developers, data engineers, IT professionals, and students eager to explore the nuances of real-time data, this book equips you with the knowledge to build scalable, efficient, and reliable streaming applications. Delve into the sophisticated architecture of Apache Kafka, understanding its core components and advanced features that make it an essential element of contemporary data infrastructure. Examine the powerful capabilities of Spark Streaming, from foundational concepts to advanced performance optimizations, and discover how to integrate it effortlessly with Kafka to create dynamic data processing solutions. Covering a broad range of topics such as designing robust streaming applications, data serialization, system monitoring, and practical case studies, this book furnishes you with the necessary tools and insights to excel with streaming data. Through clear and concise explanations, "Advanced Real-Time Data Integration: Apache Kafka and Spark Streaming Techniques" simplifies the complexities of these technologies, making them accessible to a wide audience intent on harnessing the full potential of real-time data integration in their projects and enterprises.
Advanced Techniques for IoT Applications
Author: Jyotsna Kumar Mandal
language: en
Publisher: Springer Nature
Release Date: 2021-08-02
This book includes original, unpublished contributions presented at the Sixth International Conference on Emerging Applications of Information Technology (EAIT 2020), held at the University of Kalyani, Kalyani, West Bengal, India, on November 2020. The book covers the topics such as image processing, computer vision, pattern recognition, machine learning, data mining, big data and analytics, information security and privacy, wireless and sensor networks, and IoT. It will also include IoT application-related papers in pattern recognition, artificial intelligence, expert systems, natural language understanding, image processing, computer vision, applications in biomedical engineering, artificial neural networks, fuzzy logic, evolutionary optimization, data mining, Web intelligence, intelligent agent technology, virtual reality, and visualization.
Big Data Processing with Apache Spark
Apache Spark is a popular open-source big-data processing framework thatÕs built around speed, ease of use, and unified distributed computing architecture. Not only it supports developing applications in different languages like Java, Scala, Python, and R, itÕs also hundred times faster in memory and ten times faster even when running on disk compared to traditional data processing frameworks. Whether you are currently working on a big data project or interested in learning more about topics like machine learning, streaming data processing, and graph data analytics, this book is for you. You can learn about Apache Spark and develop Spark programs for various use cases in big data analytics using the code examples provided. This book covers all the libraries in Spark ecosystem: Spark Core, Spark SQL, Spark Streaming, Spark ML, and Spark GraphX.