Parallel database systems: the future of high performance database systems
Communications of the ACM
Scheduling problems in parallel query optimization
PODS '95 Proceedings of the fourteenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Parallelism and its price: a case study of nonstop SQL/MP
ACM SIGMOD Record
Multi-dimensional resource scheduling for parallel queries
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
Open issues in parallel query optimization
ACM SIGMOD Record
Optimization of SQL queries for parallel machines
Optimization of SQL queries for parallel machines
SC '97 Proceedings of the 1997 ACM/IEEE conference on Supercomputing
Applying Segmented Right-Deep Trees to Pipelining Multiple Hash Joins
IEEE Transactions on Knowledge and Data Engineering
Parallel Query Scheduling and Optimization with Time- and Space-Shared Resources
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
Architecture of Oracle Parallel Server
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
Dynamic Load Balancing for Parallel Association Rule Mining on Heterogenous PC Cluster Systems
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Approximation algorithms for scheduling problems
Approximation algorithms for scheduling problems
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Pipelined operator tree (POT) scheduling is an important problem in the area of parallel query optimization. A POT is a tree with nodes representing query operators that can run in parallel and edges representing communication between adjacent operators that is handled by sending long streams of data in a parallel-pipelined fashion. The problem is to find a schedule for the POT that minimizes the total response time. This problem has only been previously addressed for homogeneous environments, but the new parallel database systems tend to be more heterogeneous. In this paper, we consider processors with different fixed speeds (called uniform processor system). This problem has been shown to be NP-hard even for identical processors. We propose three approximate algorithms for some special cases of the problem with good low-performance ratio (or approximation factor) bound in the worst case. The performance ratios of these algorithms, even for the general case, are shown by experimentation to be near optimal on the average. We will show that the performance ratios of these algorithms, if used for homogeneous systems, are lower than the previous results. For the general case, we propose an algorithm which has a constant bound on the performance ratio in the worst case and is near optimal on the average.