Dataflow query execution in a parallel main-memory environment
PDIS '91 Proceedings of the first international conference on Parallel and distributed information systems
R-trees: a dynamic index structure for spatial searching
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
Continuous queries over data streams
ACM SIGMOD Record
Proceedings of the 17th International Conference on Data Engineering
Approximate join processing over data streams
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Load Shedding for Aggregation Queries over Data Streams
ICDE '04 Proceedings of the 20th International Conference on Data Engineering
Maintaining Sliding Window Skylines on Data Streams
IEEE Transactions on Knowledge and Data Engineering
Relaxing join and selection queries
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Continuous Nearest Neighbor Queries over Sliding Windows
IEEE Transactions on Knowledge and Data Engineering
Load shedding in a data stream manager
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
A survey of top-k query processing techniques in relational database systems
ACM Computing Surveys (CSUR)
Probing Queries in Wireless Sensor Networks
ICDCS '08 Proceedings of the 2008 The 28th International Conference on Distributed Computing Systems
Robust approximate aggregation in sensor data management systems
ACM Transactions on Database Systems (TODS)
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
Small synopses for group-by query verification on outsourced data streams
ACM Transactions on Database Systems (TODS)
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In a data stream management system, users may not be acquainted with the actual data arriving on the stream. Therefore, they may issue queries that return an empty result over several windows. In the relational context, relaxation skyline queries have been proposed as a solution to the so-called empty answer problem. Given a query composed of selection and join operations, a relaxation skyline query relies on the usage of a relaxation function (usually, a numeric function) to quantify the distance of each tuple (or pair of tuples in case of join) from the specified conditions and uses a skyline-based semantics to compute the answer. This paper addresses skyline-based relaxation over data streams. Relaxation skyline queries for selection and window-based join over data streams are defined and two different processing algorithms are proposed and experimentally compared.