PROMISE: modeling and predicting user behavior for online analytical processing applications

The workload that is generated by users of explorative navigational information systems typically contains characteristic patterns. If these task- respectively user-specific patterns are known to the system, they can be used to dynamically predict user interactions at runtime. These predictions enable the usage of predictive caching strategies and speculative execution strategies. Online analytical processing (OLAP) systems are database systems that are designed to interactively explore data that is structured according to the multidimensional data model. This thesis presents an approach (called PROMISE) to represent and acquire information about navigational patterns of OLAP systems and to use them in improving dynamic materialization (caching) strategies. To this end, the thesis contains a formal model to represent behavior of OLAP users taking into account the navigational and iterative query formulation via a graphical front-end tool. An according pattern model (based on the combination of different generalized Markov models) allows for representing navigational patterns. The PROMISE prediction algorithm uses these patterns in order to dynamically predict a set of queries at any point during a session. The prediction framework is completed by an algorithm that induces and updates the pattern information for the user's actual behavior online during the system's operation. In order to demonstrate the potentials of using prediction results for dynamic system optimization, we present two approaches improving the performance of semantic query level caches in OLAP system: through improved benefit estimation functions that allow more efficient admission and eviction algorithms and by means of speculative execution techniques. An empirical analysis of the characteristics of user behavior in a real-world data warehouse environment and performance measurements using simulated traces with data from a real world application demonstrate the usefulness of the approach.

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