A review of query optimization techniques for complex event processing

Abstract

Complex Event Processing (CEP) Systems is a technology that is used in many modern fields of application such as finance and business analysis. It tracks and analyses data from large information streams pertaining to a string of related or non-related events in order to identify patterns and relations that could be used to derive useful connections among seemingly unrelated factors within its applications. CEP systems make use of pattern queries to match identified events within an event stream. However, due to the generalized nature of CEP query languages and the lack of general structure and semantics, it is difficult to write queries that function optimally to deliver the expected results within the required time frames. This issue is particularly of importance as CEP systems often deal with time sensitive data and hence require rapid processing in order to output useful information and hence, defines the importance and requirement for query optimization techniques that may be applied to CEP systems. This paper focuses on research publications related to the four main pattern query optimization techniques, namely, Multi-Query Optimization, Join Query Optimization, Nested Query Processing techniques and Query Rewriting as well as their applications within modern CEP systems. This study further aims to identify possible limitations within the four techniques mentioned previously and advise on possible measures that may be taken to further improve these techniques in order to offer greater efficiency and stability to pattern query processing within CEP systems.