Concurrency control and recovery in database systems
Concurrency control and recovery in database systems
Wave-indices: indexing evolving databases
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
NiagaraCQ: a scalable continuous query system for Internet databases
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Transactional information systems: theory, algorithms, and the practice of concurrency control and recovery
Gigascope: high performance network monitoring with an SQL interface
Proceedings of the 2002 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
PSoup: a system for streaming queries over streaming data
The VLDB Journal — The International Journal on Very Large Data Bases
Holistic UDAFs at streaming speeds
SIGMOD '04 Proceedings of the 2004 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
The CQL continuous query language: semantic foundations and query execution
The VLDB Journal — The International Journal on Very Large Data Bases
StatStream: statistical monitoring of thousands of data streams in real time
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
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
Resource sharing in continuous sliding-window aggregates
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
SFCS '83 Proceedings of the 24th Annual Symposium on Foundations of Computer Science
A study of replacement algorithms for a virtual-storage computer
IBM Systems Journal
Transactional stream processing
Proceedings of the 15th International Conference on Extending Database Technology
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Data stream systems execute a dynamic workload of long-running and one-time queries, with the streaming inputs typically bounded by sliding windows. For efficiency, windows may be advanced periodically by replacing the oldest part of the window with a batch of new data. Existing work on stream processing assumes that a window cannot be advanced while it is being accessed by a query. In this paper, we argue that concurrent processing of queries (reads) and window-slides (writes) is required by data stream systems in order to allow prioritized query scheduling and improve the freshness of answers. We prove that the traditional notion of conflict serializability is insufficient in this context and define stronger isolation levels that restrict the allowed serialization orders. We also design and experimentally evaluate a transaction scheduler that efficiently enforces the new isolation levels.