Rapid bushy join-order optimization with Cartesian products
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
Iterative dynamic programming: a new class of query optimization algorithms
ACM Transactions on Database Systems (TODS)
Access path selection in a relational database management system
SIGMOD '79 Proceedings of the 1979 ACM SIGMOD international conference on Management of data
Using EELs, a Practical Approach to Outerjoin and Antijoin Reordering
Proceedings of the 17th International Conference on Data Engineering
Measuring the Complexity of Join Enumeration in Query Optimization
VLDB '90 Proceedings of the 16th International Conference on Very Large Data Bases
Adaptive ordering of pipelined stream filters
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Semantics and evaluation techniques for window aggregates in data streams
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Update-pattern-aware modeling and processing of continuous queries
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Exploiting predicate-window semantics over data streams
ACM SIGMOD Record
On-the-fly sharing for streamed aggregation
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
The CQL continuous query language: semantic foundations and query execution
The VLDB Journal — The International Journal on Very Large Data Bases
Incremental Evaluation of Sliding-Window Queries over Data Streams
IEEE Transactions on Knowledge and Data Engineering
Processing sliding window multi-joins in continuous queries over data streams
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
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Many scientific applications including environmental monitoring, outpatient health care research, and wild life tracking require real-time stream processing. While state-of-the-art techniques for processing window-constrained stream queries tend to employ the delta result strategy (to react to each and every change of the stream sensor measurements), some scientific applications only require to produce results periodically - making the complete result strategy a better choice. In this work, we analyze the trade-offs between the delta and the complete result query evaluation strategies. We then design a solution for hopping window query processing based on the above analysis. In particular, we propose query operators equipped with the ability to accept either delta or complete results as input and to produce either as output. Unlike prior works, these flexible operators can then be integrated within one mode aware query plan - taking advantage of both processing methodologies. Third, we design a mode assignment algorithm to optimally assign the input and output modes for each operator in the mode aware query plan. Lastly, mode assignment is integrated with a cost-based plan optimizer. The proposed techniques have been implemented within the WPI stream query engine, called CAPE. Our experimental results demonstrate that our solution routinely outperforms the state-of-the-art single-mode solutions for various arrival rate and query plan shapes.