Join Query Optimization Techniques for Complex Event Processing Applications
Ilya Kolchinsky, Assaf Schuster

TL;DR
This paper explores the connection between complex event processing (CEP) and join query optimization, demonstrating how established join techniques can enhance CEP performance through theoretical analysis and experimental validation.
Contribution
It establishes the equivalence between CEP plan generation and join query plan generation, enabling the adaptation of join optimization methods to CEP systems.
Findings
Join query optimization techniques improve CEP throughput and latency.
CEP plan generation is NP-complete, similar to join query planning.
Experimental results show significant performance gains over existing CEP strategies.
Abstract
Complex event processing (CEP) is a prominent technology used in many modern applications for monitoring and tracking events of interest in massive data streams. CEP engines inspect real-time information flows and attempt to detect combinations of occurrences matching predefined patterns. This is done by combining basic data items, also called primitive events, according to a pattern detection plan, in a manner similar to the execution of multi-join queries in traditional data management systems. Despite this similarity, little work has been done on utilizing existing join optimization methods to improve the performance of CEP-based systems. In this paper, we provide the first theoretical and experimental study of the relationship between these two research areas. We formally prove that the CEP Plan Generation problem is equivalent to the Join Query Plan Generation problem for a…
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