Unit 1 Introduction & Designing Real-Time Streaming Architecture

9 lecture hours

• Sources of streaming data
• why streaming data is different
• infrastructure and algorithms
• Real-time architecture components
• features of a real- time architecture
• languages for real-time programming
• a real-time architecture checklist 04 10 Unit-II: Service Configuration and Coordination: Motivation for configuration and coordination systems
• maintaining distributed state
• Apache ZooKeeper 04 10 Unit-III: Data-Flow Management in Streaming Analysis: Distributed data flows
• Apache Kafka: high-throughput distributed messaging
• Apache Flume: distributed log collection
• 06 15 Unit-IV: Processing Streaming Data: Distributed streaming data processing
• processing data with Storm
• Processing data with Samza 06 15 Unit-V: Storing Streaming Data: Consistent Hashing
• NoSQL storage systems
• other storage technologies
• Choosing a technology

Unit 2 Delivering Streaming Metrics

9 lecture hours

• Streaming web applications
• Visualizing data
• mobile streaming applications

Unit 3 Exact Aggregation and Delivery

• Timed counting and summation
• multi-resolution time-series aggregation
• stochastic optimization
• delivering time-series data and recent trends in real-time data analytics 04 10 GUJARAT TECHNOLOGICAL UNIVERSITY Master of Engineering w.e.f
• AY 2021-22  Recent Development in Real Time Data Analytics (Study from latest research papers published in Scopus indexed/web of science journals - 04 hours during laboratory hours) Reference Book: 1
• Real-Time Analytics Techniques to Analyze and Visualize Streaming Dat, by Byron Ellis
• Practical Real-Time Data Processing and Analytics
• by Shilpi Saxena
• Saurabh Gupta
• 2017 Course Outcome: After Completion of the Course
• Student will able to: No Course Outcomes RBT Level* 01 Understand the basic real-time streaming architecture
• service configuration and coordination UN 02 Apply data flow management techniques/tools in streaming analysis AP 03 Demonstrate various streaming processings using various tools AP 04 Analyse of various techniques/systems for storage of streaming data AN 05 Evaluate various delivering streaming metrics and exact aggregation for various applications EL *RM: Remember
• UN: Understand
• AP: Apply
• AN: Analyze
• EL: Evaluate
• CR: Create Suggested Course Practical List: The practical work will be carried out based on the content covered during the academic session List of Laboratory/Learning Resouces Required:  List of Software : Python
• JavaScript, Go, R, MATLAB  List of Open Source Tools/Simulator: Apache Storm
• Apache ZooKeeper
• Apache Kafka
• Apache Flume
• Apache Samza  List of Useful websites/MOOCs:  https://nptel.ac.in/courses/110106064  https://nptel.ac.in/courses/106104189