Data Streams Processing Techniques Data Streams Processing Techniques
Najib, Fatma; Ismail RM; Tolba MF; Badr NL;
Abstract
Many modern applications in several domains such as sensor networks, financial applications, web logs and click-streams operate on continuous, unbounded, rapid, time-varying streams of data elements. These applications present new challenges that are not addressed by traditional data management techniques. For the query processing of continuous data streams, we consider in particular continuous queries which are evaluated continuously as data streams continue to arrive. The answer to a continuous query is produced over time, always reflecting the stream data seen so far. One of the most critical requirements of stream processing is fast processing. So, parallel and distributed processing would be good solutions. This paper gives (1) analysis to the different continuous query processing techniques; (2) a comparative study for the data streams execution environments; and (3) finally, we propose an integrated system for processing data streams based on cloud computing which apply continuous query optimization technique on cloud environment.
Other data
Title | Data Streams Processing Techniques Data Streams Processing Techniques | Authors | Najib, Fatma ; Ismail RM ; Tolba MF ; Badr NL | Keywords | Continuous queries optimization, Multiple plans, Query mesh, Continuous bounded queries, Continuous nearest neighbor queries, Pattern mining, Continuous Top-k queries, Continuous skyline queries, Multiple continuous queries, Map reduce, Elastic processing, Load balancing, Recourses provisioning | Issue Date | 2017 | Publisher | IGI Global | Conference | Handbook of Research on Machine Learning Innovations and Trends | DOI | 10.4018/978-1-5225-2229-4.ch015 |
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