Distributed databases principles and systems
Distributed databases principles and systems
Optimizing chain queries in a distributed database system.
SIAM Journal on Computing
Optimization of distributed tree queries
Journal of Computer and System Sciences
ACM Computing Surveys (CSUR)
A state transition model for distributed query processing
ACM Transactions on Database Systems (TODS)
Optimizing Join Queries in Distributed Databases
IEEE Transactions on Software Engineering
Effect of skew on join performance in parallel architectures
DPDS '88 Proceedings of the first international symposium on Databases in parallel and distributed systems
On the effect of join operations on relation sizes
ACM Transactions on Database Systems (TODS)
On the propagation of errors in the size of join results
SIGMOD '91 Proceedings of the 1991 ACM SIGMOD international conference on Management of data
On Workload Characterization of Relational Database Environments
IEEE Transactions on Software Engineering
Query processing in a system for distributed databases (SDD-1)
ACM Transactions on Database Systems (TODS)
Using Semi-Joins to Solve Relational Queries
Journal of the ACM (JACM)
Recent Advances in Distributed Data Base Management
Recent Advances in Distributed Data Base Management
Graph Algorithms
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Query processing for distributed databases using generalized semi-joins
SIGMOD '82 Proceedings of the 1982 ACM SIGMOD international conference on Management of data
The tree property is fundamental for query processing
PODS '82 Proceedings of the 1st ACM SIGACT-SIGMOD symposium on Principles of database systems
An Intelligent Search Method for Query Optimization by Semijoins
IEEE Transactions on Knowledge and Data Engineering
Interleaving a Join Sequence with Semijoins in Distributed Query Processing
IEEE Transactions on Parallel and Distributed Systems
Combining Joint and Semi-Join Operations for Distributed Query Processing
IEEE Transactions on Knowledge and Data Engineering
Scheduling and Processor Allocation for Parallel Execution of Multi-Join Queries
Proceedings of the Eighth International Conference on Data Engineering
Optimizing Star Queries in a Distributed Database System
VLDB '84 Proceedings of the 10th International Conference on Very Large Data Bases
The optimization of query processing on distributed database systems
The optimization of query processing on distributed database systems
Processing Distributed Mobile Queries with Interleaved Remote Mobile Joins
IEEE Transactions on Computers
On the Complexity of Distributed Query Optimization
IEEE Transactions on Knowledge and Data Engineering
Efficient Query Processing in Integrated Multiple Object Databases with Maybe Result Certification
IEEE Transactions on Knowledge and Data Engineering
ICDCS '01 Proceedings of the The 21st International Conference on Distributed Computing Systems
Information Sciences: an International Journal
Tree balance and node allocation
IDEAS'97 Proceedings of the 1997 international conference on International database engineering and applications symposium
Journal of Computer and System Sciences
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Semijoin has traditionally been relied upon to reduce the cost of data transmission for distributed query processing. However, judiciously applying join operations as reducers can lead to further reduction in the amount of data transmission required. In view of this fact, we explore the approach of using join operations as reducers in distributed query processing. We first show that the problem of determining a sequence of join operations for a query can be transformed to that of finding a specific type of set of cuts to the corresponding query graph, where a cut to a graph is a partition of nodes in that graph. Then, in light of this concept, we prove that the problem of determining the optimal sequence of join operations for a given query graph is of exponential complexity, thus justifying the necessity of applying heuristic approaches to solve this problem. By mapping the problem of determining a sequence of join reducers into the one of finding a set of cuts, we develop (for tree and general query graphs, respectively) efficient heuristic algorithms to determine a join reducer sequence for distributed query processing. The algorithms developed are based on the concept of divide and conquer and are of polynomial time complexity. Simulation is performed to evaluate these algorithms.