PREFER: a system for the efficient execution of multi-parametric ranked queries
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Top-k selection queries over relational databases: Mapping strategies and performance evaluation
ACM Transactions on Database Systems (TODS)
Evaluating Top-k Selection Queries
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Optimizing Multi-Feature Queries for Image Databases
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Evaluating top-k queries over web-accessible databases
ACM Transactions on Database Systems (TODS)
Optimizing Top-k Selection Queries over Multimedia Repositories
IEEE Transactions on Knowledge and Data Engineering
Efficient top-K query calculation in distributed networks
Proceedings of the twenty-third annual ACM symposium on Principles of distributed computing
Progressive Distributed Top-k Retrieval in Peer-to-Peer Networks
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
KLEE: a framework for distributed top-k query algorithms
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Reducing network traffic in unstructured P2P systems using Top-k queries
Distributed and Parallel Databases
Answering top-k queries using views
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
Efficient top-k processing in large-scaled distributed environments
Data & Knowledge Engineering
Best position algorithms for top-k queries
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Stop-and-restart style execution for long running decision support queries
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
On efficient top-k query processing in highly distributed environments
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
A survey of top-k query processing techniques in relational database systems
ACM Computing Surveys (CSUR)
PROQID: partial restarts of queries in distributed databases
Proceedings of the 17th ACM conference on Information and knowledge management
Efficient and Robust Database Support for Data-Intensive Applications in Dynamic Environments
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
View usability and safety for the answering of top-k queries via materialized views
Proceedings of the ACM twelfth international workshop on Data warehousing and OLAP
Distributed top-k query processing by exploiting skyline summaries
Distributed and Parallel Databases
On saying "enough already!" in MapReduce
Proceedings of the 1st International Workshop on Cloud Intelligence
Efficient top-k query answering using cached views
Proceedings of the 16th International Conference on Extending Database Technology
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Recently, there has been an increased interest in incorporating in database management systems rank-aware query operators, such as top-k queries, that allow users to retrieve only the most interesting data objects. In this paper, we propose a cache-based approach for efficiently supporting top-k queries in distributed database management systems. In large distributed systems, the query performance depends mainly on the network cost, measured as the number of tuples transmitted over the network. Ideally, only the k tuples that belong to the query result set should be transmitted. Nevertheless, a server cannot decide based only on its local data which tuples belong to the result set. Therefore, in this paper, we use caching of previous results to reduce the number of tuples that must be fetched over the network. To this end, our approach always delivers as many tuples as possible from cache and constructs a remainder query to fetch the remaining tuples. This is different from the existing distributed approaches that need to re-execute the entire top-k query when the cached entries are not sufficient to provide the result set. We demonstrate the feasibility and efficiency of our approach through implementation in a distributed database management system.