|Tested Item||Data Store||Query Type||Amount of events processed||Average Throughput (events per second)|
|Simple Pass-through||None||None||30 million||900K||0.9|
|Filter||None||Filter out all the events||30 million||900K||1.5|
|Window-small (1 second)||None||Sliding time window||30 million||100K||48|
|Window - Large (1 minute)||None||Sliding time window||30 million||100K||130|
|Patterns||None||Temporal event sequence patterns||1250 million||500K||550|
Event Ingestion with Persistence
Oracle Event Store
MS SQL Event Store
MySQL Event Store
The experiments were carried out in two c4.2xlarge (8 vCPU, 16GB RAM, EBS storage with 1000 Mbps max dedicated bandwidth) Amazon EC2 instances.
Linux kernel 4.44, java version "1.8.0_131", JVM flags : flagskickoff -Xmx4g -Xms2g
One node operated as a client.
Another node operated as a Stream Processor node.
Experiments were carried out using TCP as the transport.
The data used in 2013 DEBS Grand Challenge is collected by the Real-Time Locating System deployed on a football field of the Nuremberg Stadium in Germany. Data originates from sensors located near the players’ shoes (1 sensor per leg) and in the ball (1 sensor). The goalkeeper is equipped with two additional sensors in each hand. The sensors in the players’ shoes and hands produce data at a frequency of 200Hz, while the sensor in the ball produces data at a frequency of 2000Hz. The total data rate reaches roughly 15 position events per second. Every position event describes the position of a given sensor in a three-dimensional coordinate system. The center of the playing field is at coordinate (0, 0, 0) for the dimensions of the playing field and the coordinates of the kick offkickoff.
For more details about the dataset, see DEBS 2013 Grand Challenge: Soccer monitoring.