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Complex Event Processing on Ruby and Fluentd - RubyKaigi 2013
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Esperwhispering
This document discusses using Esper, a complex event processing (CEP) engine, to analyze real-time web activity data and provide answers to questions about that data within seconds. It describes the large volume of event data involved, defines what types of information each event contains, and provides examples of Esper queries to calculate statistics, detect anomalies, and retrieve snapshots of q
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4. STORM Norikra Jubatus CEP DSMS SPE Relational-stream XML-stream S4 STREAM System S Algorithm trading Borealis(MIT/Brandeis) Stream computing Complex event processing Online learning Incremental computation Continual query Spring (DTW) CPD (Change Point Detection) Window-aggregate Window-join FPGA GPU SASE Fraud detection Malware detection AQP (Adaptive Query Proc.) Esper BRIMOS Handshake-join I
Complex Event Processing ( CEP ) | Sybase Unofficial blog
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Stream(SQL) Event Processing with Esper - igvita.com
By Ilya Grigorik on May 27, 2011 The growth of both the types and the amount of data generated by servers, users, and applications have resulted in a number of recent trends and innovations: NoSQL, rise of popularity of Hadoop, and dozens of higher-level map-reduce frameworks. However, the batch-processing model imposed by map-reduce style of processing is not always a great fit either, especially
Event Stream Processor Matrix - Sematext
We published our first ever UI-focused post on Top JavaScript Dynamic Table Libraries the other day and got some valuable feedback – thanks! We are back to talking about the backend again.  Our Search Analytics and Scalable Performance Monitoring services/products accept, process, and store huge amounts of data.  One thing both of these services do is process a stream of events in real-time (and b
20130215 fluentd esper_2
3. ã“ã‚“ãªæ„Ÿã˜ select count(*) from accesslog:win(30sec ) group by path having count(*) > 5 output input { { count(*): 20, host: 10.1.1.1, path “/index.html†path : “/index.htmlâ€, } code: 200 { } count(*):6, path “/favicon.ico†} 5. Data Flow Query Registration Proces Compone Client(ruby) s nt RPC Client msgpack-RPC fluentd (ruby) Subscriber(java) query input 0mq publish 0mq Esper RPC output msgpack sub
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Complex Event Processing on Ruby, Fluentd and Norikra #rubykaigi
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Charming Python: Functional programming in Python, Part 3
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