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Predicting access to materialized methods by means of hidden Markov model

Masewicz M., Andrzejewski W., Wrembel W., Kró1ikowski Z.

Control and Cybernetics

2009

Vol. 38, no 1

127-152

Method materialization is a promising data access optimization technique for multiple applications, including, in particular object programming languages with persistence, object databases, distributed computing systems, object-relational data warehouses, multimedia data warehouses, and spatial data warehouses. A drawback of this technique is that the value of a materialized method becomes invalid when an object used for computing the value of the method is updated. As a consequence, a materialized value of the method has to be recomputed. The materialized value can be recomputed either immediately after updating the object or just before calling the method. The moment the method is recomputed bears a strong impact on the overall system performance. In this paper we propose a technique of predicting access to materialized methods and objects, for the purpose of selecting the most appropriate recomputation technique. The prediction technique is based on the Hidden Markov Model (HMM). The prediction technique was implemented and evaluated experimentally. Its performance characteristics were compared to: immediate recomputation, deferred recomputation, random recomputation, and to our previous prediction technique, called a PMAP.

Methods materialisation in object-oriented databases: implementation and experimental evaluation

Jezierski J., Masewicz M., Wrembel R.

Foundations of Computing and Decision Sciences

2004

Vol. 29, No. 3

171-192

A method can be a very complex program, whose computation may last long. Therefore the efficient execution of a method has a great impact on a query response time. Optimising access to data returned by methods is difficult as methods are written in a high-level programming languages. Moreover, estimating a method's execution cost is another serious problem because of the complexity of a method's code. In this paper we propose a framework for the materialisation of method results in object-oriented databases. A materialisation of a method consists in computing the result of a method once, store it persistently in a database and then use the persistent value when the method is invoked. However, the result of a materialised method has to be kept up to date after updating objects used to compute the value of this method. To this end, we use additional data structures representing links between materialised methods and objects used to compute these methods. When such an object is updated, the system uses these data structures in order to invalidate outdated results. In our approach, the materialisation of method m results also in the materialisation of intermediate results of methods called from m. We call this technique hierarchical materialisation. When an object used to materialise the result of in is updated, then in is invalidated. Next invocation of in for the same object, results in the recomputation of in by using unaffected intermediate materialised results of methods called from in. Thus, the recomputation time overhead is reduced. The hierarchical materialisation technique was implemented and evaluated in a prototype based on the FcistObjects t7 object-oriented database.