In January I did a talk at Oreilly Strata SF 2014 about how we solved the DEBS grand challenge, which involved processing data collected from a sensors in the ball and players boots in a football Game. I had blogged about some of the details before. Following is the slide deck I used for the talk.
Also following is the abstract.
Mobile devices, sensors and GPS are driving the demand to handle big data in both batch and real time. This presentation discusses how we used complex event processing (CEP) and MapReduce based technologies to track and process data from a soccer match as part of the annual DEBS event processing challenge. In 2013, the challenge included a data set generated by a real soccer match in which sensors were placed in the soccer ball and players’ shoes. This session will review how we used CEP to implement DESB challenge and achieved throughput in excess of 100,000 events/sec. It also will examine how we extended the solution to conduct batch processing using business activity monitoring (BAM) using the same framework, enabling users to obtain both instant analytics as well as more detailed batch processing based results.
Also following is the abstract.
Mobile devices, sensors and GPS are driving the demand to handle big data in both batch and real time. This presentation discusses how we used complex event processing (CEP) and MapReduce based technologies to track and process data from a soccer match as part of the annual DEBS event processing challenge. In 2013, the challenge included a data set generated by a real soccer match in which sensors were placed in the soccer ball and players’ shoes. This session will review how we used CEP to implement DESB challenge and achieved throughput in excess of 100,000 events/sec. It also will examine how we extended the solution to conduct batch processing using business activity monitoring (BAM) using the same framework, enabling users to obtain both instant analytics as well as more detailed batch processing based results.
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