Partition Strategy for Distributed Query Processing in Fast Local Networks
IEEE Transactions on Software Engineering
Optimizing equijoin queries in distributed databases where relations are hash partitioned
ACM Transactions on Database Systems (TODS)
Parallel database systems: the future of high performance database systems
Communications of the ACM
Adaptive parallel aggregation algorithms
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
Query processing in a system for distributed databases (SDD-1)
ACM Transactions on Database Systems (TODS)
Automating physical database design in a parallel database
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
A Hash Partition Strategy for Distributed Query Processing
EDBT '96 Proceedings of the 5th International Conference on Extending Database Technology: Advances in Database Technology
Efficient OLAP Query Processing in Distributed Data Warehouses
EDBT '02 Proceedings of the 8th International Conference on Extending Database Technology: Advances in Database Technology
An Efficient Algorithm for Processing Distributed Queries Using Partition Dependency
ICPADS '00 Proceedings of the Seventh International Conference on Parallel and Distributed Systems
Hash-based Placement and Processing for Efficient Node Partitioned Query-Intensive Databases
ICPADS '04 Proceedings of the Parallel and Distributed Systems, Tenth International Conference
Multiprocessor hash-based join algorithms
VLDB '85 Proceedings of the 11th international conference on Very Large Data Bases - Volume 11
INFOCOM'96 Proceedings of the Fifteenth annual joint conference of the IEEE computer and communications societies conference on The conference on computer communications - Volume 2
Quality of experience in distributed databases
Distributed and Parallel Databases
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The recent trend towards peer-to-peer and networked data management raises some challenging issues regarding data placement and processing. Additionally, as data management environments change from a machine into a local area network and from there into a global inter-network, the context of application of parallel query processing changes. In this paper we analyze parallel processing of aggregation queries in different networked contexts. First we describe briefly the Node-Partitioned Data Manager architecture and the aggregation processing in that architecture. We identify a performance bottleneck in the basic typical parallel aggregation strategy and discuss the use of hierarchical aggregation to overcome the problem. We analyze and compare the strategies both analytically and experimentally by means of a model and a simulator capable of generating different networked settings. This allowed us to compare the influence of different parameters on the performance. We were able to show the increased efficiency of the strategy and also to analyze and obtain interesting results of its behavior in varied settings.