ACM Computing Surveys (CSUR)
Introduction to algorithms
Principles of database query processing for advanced applications
Principles of database query processing for advanced applications
The state of the art in distributed query processing
ACM Computing Surveys (CSUR)
Considering data skew factor in multi-way join query optimization for parallel execution
The VLDB Journal — The International Journal on Very Large Data Bases - Parallelism in database systems
A Graph Theoretical Approach to Determine a Join Reducer Sequence in Distributed Query Processing
IEEE Transactions on Knowledge and Data Engineering
Optimal Allocation for Partially Replicated Database Systems on Ring Networks
IEEE Transactions on Knowledge and Data Engineering
Combinatorial Optimization of Distributed Queries
IEEE Transactions on Knowledge and Data Engineering
Optimization of Parallel Execution for Multi-Join Queries
IEEE Transactions on Knowledge and Data Engineering
On the Complexity of Distributed Query Optimization
IEEE Transactions on Knowledge and Data Engineering
A Parallel Sort Merge Join Algorithm for Managing Data Skew
IEEE Transactions on Parallel and Distributed Systems
Combining Joint and Semi-Join Operations for Distributed Query Processing
IEEE Transactions on Knowledge and Data Engineering
Join Index Hierarchies for Supporting Efficient Navigations in Object-Oriented Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
A Scheme for High-Performance Data Delivery in the Web Environment
ICPADS '98 Proceedings of the 1998 International Conference on Parallel and Distributed Systems
Efficient data distribution strategy for join query processing in the cloud
Proceedings of the third international workshop on Cloud data management
| Hi-index | 0.00 |
Abstract: We introduce the concept of network graph for distributed query processing. Semijoins and joins are termed contributive replicated semijoins and contributed replicated joins, respectively, when they are interleaved into a join sequence to reduce the amount of data transmission cost required in a network with replicated relations. Our solution procedure consists of three consecutive steps, namely relation selection, join sequence scheduling and merge processing. A simulator is developed to evaluate the performance of algorithms devised. Our results show that the approach of interleaving a join sequence with contributive replicated semijoins/joins is not only efficient in its execution but also effective in reducing the total amount of data transmission cost required to process distributed queries.