Data Stream Management: Processing High-Speed Data Streams Ed by Minos Garofalakis, Johannes Gehrke, Rajeev Rastogi - New York Springer Heidelberg 2016 - 537p - Data-Centric Systems and Applications .

1. Data Stream Management: A Brave New World
2. Data-Stream Sampling: Basic Techniques and Results
3. Quantiles and Equi-depth Histograms over Streams
4. Join Sizes, Frequency Moments, and Applications
5. Top- $k$ Frequent Item Maintenance over Streams
6. Distinct-Values Estimation over Data Streams
7. The Sliding-Window Computation Model and Results
8. Clustering Data Streams
9. Mining Decision Trees from Streams
10. Frequent Itemset Mining over Data Streams
11. Temporal Dynamics of On-Line Information Streams
12. Sketch-Based Multi-Query Processing over Data Streams
13. Approximate Histogram and Wavelet Summaries of Streaming Data
14. Stable Distributions in Streaming Computations
15. Tracking Queries over Distributed Streams
16. STREAM: The Stanford Data Stream Management System
17. The Aurora and Borealis Stream Processing Engines
18. Extending Relational Query Languages for Data Streams
19. Hancock: A Language for Analyzing Transactional Data Streams
20. Sensor Network Integration with Streaming Database Systems
21. Stream Processing Techniques for Network Management
22. High-Performance XML Message Brokering
23. Fast Methods for Statistical Arbitrage
24. Adaptive, Automatic Stream Mining
25. Conclusions and Looking Forward


Streaming Technology
Computer Science
Big Data

005.55 / DAT

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