Processing nested complex sequence pattern queries over event streams

Complex event processing (CEP) has become increasingly important for tracking and monitoring applications ranging from healthcare, supply chain management to surveillance. These monitoring applications submit complex event queries to track sequences of events that match a given pattern. As these systems mature the needfor increasingly complex nested sequence queries arises, while thestate-of-the-art CEP systems mostly focus on the execution of flat sequence queries only. In this paper, we now introduce an iterative execution strategy for nested CEP queries composed of sequence, negation, AND and OR operators. Lastly the promise of applying selective caching of intermediate results to optimize the execution. Our experimental study using real-world stock trades evaluates the performance of our proposed iterative execution strategy for differentquery types.HP Labs Innovation Research Program ; National Science Foundation ; TÜBİTAKpost-prin

Processing nested complex sequence pattern queries over event streams

Complex event processing (CEP) has become increasingly important for tracking and monitoring applications ranging from healthcare, supply chain management to surveillance. These monitoring applications submit complex event queries to track sequences of events that match a given pattern. As these systems mature the needfor increasingly complex nested sequence queries arises, while thestate-of-the-art CEP systems mostly focus on the execution of flat sequence queries only. In this paper, we now introduce an iterative execution strategy for nested CEP queries composed of sequence, negation, AND and OR operators. Lastly the promise of applying selective caching of intermediate results to optimize the execution. Our experimental study using real-world stock trades evaluates the performance of our proposed iterative execution strategy for differentquery types.HP Labs Innovation Research Program ; National Science Foundation ; TÜBİTAKpost-prin

Materialized Object-Oriented Views in MultiView

Object-oriented view mechanisms have received much attention in the literature in recent years, since they provide powerful mechanisms for addressing tasks such as customized tool interfacing to object-oriented databases (OODBs) and interoperability of heterogeneous databases. However, little progress has been made thus far on addressing the topic of view materialization in object-oriented databases. In the context of the MultiView project, we have developed an object model and an accompanying set of algorithms for the support of updatable materialized views in OODBs. We take advantage of unique features of the MultiView model, including its support for object-preserving queries, the integration of base and virtual classes into a unified and consistent global class hierarchy, and an object-slicing approach. In this paper, we present the MultiView model of materialized views, supporting updates on both base and virtual classes. We also describe a set of efficient algorithms for increm..

Refinement driven processing of aggregation Constrained queries

© 2016, Copyright is with the authors. Although existing database systems provide users an efficient means to select tuples based on attribute criteria, they however provide little means to select tuples based on whether they meet aggregate requirements. For instance, a requirement may be that the cardinality of the query result must be 1000 or the sum of a particular attribute must be < $5000. In this work, we term such queries as "Aggregation Constrained Queries" (ACQs). Aggregation constrained queries are crucial in many decision support applications to maintain a product's competitive edge in this fast moving field of data processing. The challenge in processing ACQs is the unfamiliarity of the underlying data that results in queries being either too strict or too broad. Due to the lack of support of ACQs, users have to resort to a frustrating trial-and-error query refinement process. In this paper, we introduce and define the semantics of ACQs. We propose a refinement-based approach, called ACQUIRE, to efficiently process a range of ACQs. Lastly, in our experimental analysis we demonstrate the superiority of our technique over extensions of existing algorithms. More specifically, ACQUIRE runs up to 2 orders of magnitude faster than compared techniques while producing a 2X reduction in the amount of refinement made to the input queries

Physical Map Assembler: An Active OODB System for Human Genome Applications

We describe the design and implementation of a scientific database for the map assembly tasks performed by the geneticists at the University of Michigan Human Genome Center. Our system manages complex genomic data and supports the automation of the associated map assembly tasks. For the former, we present a genomic object model that integrates both experimental and derived data. For the latter, we describe operators to automate some of the analysis steps. To develop a framework for implementing our rule-based approach to physical mapping, we have designed and implemented an active object-oriented database (OODB) system, called Crystal, on GemStone. Crystal seamlessly integrates inference capabilities with complex object modeling and other typical database capabilities as required for physical mapping. We also discuss the implementation of a physical map assembly tool on top of Crystal. In conclusion, we provide a walk-through example that demonstrates how our approach can be used to ef..