Models and issues in data stream systems
Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Chain: operator scheduling for memory minimization in data stream systems
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Aurora: a new model and architecture for data stream management
The VLDB Journal — The International Journal on Very Large Data Bases
Static optimization of conjunctive queries with sliding windows over infinite streams
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Where are the hard knapsack problems?
Computers and Operations Research
Adaptive load shedding for windowed stream joins
Proceedings of the 14th ACM international conference on Information and knowledge management
Run-time operator state spilling for memory intensive long-running queries
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
GrubJoin: An Adaptive, Multi-Way, Windowed Stream Join with Time Correlation-Aware CPU Load Shedding
IEEE Transactions on Knowledge and Data Engineering
Maximizing the output rate of multi-way join queries over streaming information sources
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
Load shedding in a data stream manager
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
Operator scheduling in a data stream manager
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
CAPE: continuous query engine with heterogeneous-grained adaptivity
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Self-tuning query mesh for adaptive multi-route query processing
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
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Due to high data volumes and unpredictable arrival rates, continuous query systems processing expensive queries in real-time may fail to keep up with the input data streams - resulting in buffer overflow and uncontrolled data loss. We explore join direction adaptation (JDA) to tackle CPU-limited processing of multi-join stream queries. The existing JDA solutions allocate the scarce CPU resources to the most productive half-way join within a single operator. We instead leverage the operator interdependencies to optimize the overall query throughput. We identify result staleness, typically ignored by most state-of-the-art techniques, as a critical issue in CPU-limited processing. It gets further aggravated if throughput optimizing techniques are employed. We establish the novel pathproductivity model and the Freshness predicate. Our proposed JAQPOT approach is the first integrated solution to achieve near optimal query throughput while also guaranteeing freshness satisfiability. JAQPOT runs in quadratic time of the number of streams irrespective of the query plan shape. Our experimental study demonstrates the superiority of JAQPOT in achieving higher throughput than the state-of-the-art JDA strategy while also fulfilling freshness predicates.