SIGMOD '89 Proceedings of the 1989 ACM SIGMOD international conference on Management of data
Tradeoffs in processing complex join queries via hashing in multiprocessor database machines
Proceedings of the sixteenth international conference on Very large databases
Parallel database systems: the future of high performance database systems
Communications of the ACM
A framework for workload allocation in distributed transaction processing systems
Journal of Systems and Software
Optimization of parallel query execution plans in XPRS
Distributed and Parallel Databases - Selected papers from the first international conference on parallel and distributed information systems
Improvements on a heuristic algorithm for multiple-query optimization
Data & Knowledge Engineering
Scheduling problems in parallel query optimization
PODS '95 Proceedings of the fourteenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Parallel evaluation of multi-join queries
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
Multi-dimensional resource scheduling for parallel queries
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
ACM SIGMOD Record
Parallelism in relational data base systems: architectural issues and design approaches
DPDS '90 Proceedings of the second international symposium on Databases in parallel and distributed systems
OLAP Query Routing and Physical Design in a Database Cluster
EDBT '00 Proceedings of the 7th International Conference on Extending Database Technology: Advances in Database Technology
Batch Scheduling in Parallel Database Systems
Proceedings of the Ninth International Conference on Data Engineering
Goal Oriented, Adaptive Transaction Routing for High Performance Transaction Processing Systems
PDIS '93 Proceedings of the 2nd International Conference on Parallel and Distributed Information Systems
Parallel Query Scheduling and Optimization with Time- and Space-Shared Resources
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
Database Architecture Optimized for the New Bottleneck: Memory Access
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
What Happens During a Join? Dissecting CPU and Memory Optimization Effects
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Dynamic Memory Allocation for Multiple-Query Workloads
VLDB '93 Proceedings of the 19th International Conference on Very Large Data Bases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Coloring Away Communication in Parallel Query Optimization
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Efficient Relational Storage and Retrieval of XML Documents
Selected papers from the Third International Workshop WebDB 2000 on The World Wide Web and Databases
MIL primitives for querying a fragmented world
The VLDB Journal — The International Journal on Very Large Data Bases
The leganet system: Freshness-aware transaction routing in a database cluster
Information Systems
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Query throughput is one of the primary optimization goals in interactive web-based information systems in order to achieve the performance necessary to serve large user communities. Queries in this application domain differ significantly from those in traditional database applications: they are of lower complexity and almost exclusively read-only. The architecture we propose here is specifically tailored to take advantage of the query characteristics. It is based on a large parallel shared-nothing database cluster where each node runs a separate server with a fully replicated copy of the database. A query is assigned and entirely executed on one single node avoiding network contention or synchronization effects. However, the actual key to enhanced throughput is a resource efficient scheduling of the arriving queries. We develop a simple and robust scheduling scheme that takes the currently memory resident data at each server into account and trades off memory re-use and execution time, reordering queries as necessary.Our experimental evaluation demonstrates the effectiveness when scaling the system beyond hundreds of nodes showing super-linear speedup.