Flattening an object algebra to provide performance

Algebraic transformation and optimization techniques have been the method of choice in relational query execution, but applying them in object-oriented (OO) DBMSs is difficult due to the complexity of OO query languages. This paper demonstrates that the problem can be simplified by mapping an OO data model to the binary relational model implemented by Monet, a state-of-the-art database kernel. We present a generic mapping scheme to flatten data models and study the case of straightforward OO model. We show how flattening enabled us to implement a query algebra, using only a very limited set of simple operations. The required primitives and query execution strategies are discussed, and their performance is evaluated on the 1-GByte TPC-D (Transaction-processing Performance Council's Benchmark D), showing that our divide-and-conquer approach yields excellent result

Implementing PRISMA/DB in an OOPL

PRISMA/DB is implemented in a parallel object-oriented language to gain insight in the usage of parallelism. This environment allows us to experiment with parallelism by simply changing the allocation of objects to the processors of the PRISMA machine. These objects are obtained by a strictly modular design of PRISMA/DB. Communication between the objects is required to cooperatively handle the various tasks, but it limits the potential for parallelism. From this approach, we hope to gain a better understanding of parallelism, which can be used to enhance the performance of PRISMA/DB.\ud The work reported in this document was conducted as part of the PRISMA project, a joint effort with Philips Research Eindhoven, partially supported by the Dutch "Stimuleringsprojectteam Informaticaonderzoek (SPIN)

Implementation and Performance Evaluation of a Parallel Transitive Closure Algorithms on PRISMA/DB

This paper is one of the first to discuss actual implementation of and experimentation with parallel transitive closure operations on a full-fledged relational database system. It brings two research efforts together; the development of an efficient execution strategy for parallel computation of path problems, called Disconnection Set Approach, and the development and implementation of a parallel, main-memory DBMS, called PRISMA/DB. First, we report on the implementation of the disconnection set approach on PRISMA/DB, showing how the latter's design allowed us to easily extend the functionality of the system. Second, we investigate the disconnection set approach's parallel behavior and performance by means of extensive experimentation. It is shown that the parallel implementation of the disconnection set approach yields very good performance characteristics, and that (super)linear speedup w.r.t. a special implementation of semi-naive is achieved for regular, so-called linear fragmenta..

Parallel Evaluation of Multi-join Queries

A number of execution strategies for parallel evaluation of multi-join queries have been proposed in the literature. In this paper we give a comparative performance evaluation of four execution strategies by implementing all of them on the same parallel database system, PRISMA/DB. Experiments have been done up to 80 processors. These strategies, coming from the literature, are named: Sequential Parallel, Synchronous Execution, Segmented Right-Deep, and Full Parallel. Based on the experiments clear guidelines are given when to use which strategy. This is an extended abstract; the full paper appeared in Proc. ACM SIGMOD'94, Minneapolis, Minnesota, May 24–27, 199