Eddies: continuously adaptive query processing
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Hancock: a language for extracting signatures from data streams
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Dataflow query execution in a parallel main-memory environment
PDIS '91 Proceedings of the first international conference on Parallel and distributed information systems
Models and issues in data stream systems
Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Gigascope: high performance network monitoring with an SQL interface
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Access path selection in a relational database management system
SIGMOD '79 Proceedings of the 1979 ACM SIGMOD international conference on Management of data
Exploiting Punctuation Semantics in Continuous Data Streams
IEEE Transactions on Knowledge and Data Engineering
Fjording the Stream: An Architecture for Queries Over Streaming Sensor Data
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
Flexible time management in data stream systems
PODS '04 Proceedings of the twenty-third ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Monitoring streams: a new class of data management applications
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
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
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
Foundations and Trends in Databases
Out-of-order processing: a new architecture for high-performance stream systems
Proceedings of the VLDB Endowment
Anomaly-free incremental output in stream processing
Proceedings of the 17th ACM conference on Information and knowledge management
An Optimization Technique for Multiple Continuous Multiple Joins over Data Streams
DEXA '09 Proceedings of the 20th International Conference on Database and Expert Systems Applications
FENCE: continuous access control enforcement in dynamic data stream environments
Proceedings of the third ACM conference on Data and application security and privacy
SkySuite: a framework of skyline-join operators for static and stream environments
Proceedings of the VLDB Endowment
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Continuous join queries (CJQ) are needed for correlating data from multiple streams. One fundamental problem for processing such queries is that since the data streams are infinite, this would require the join operator to store infinite states and eventually run out of space. Punctuation semantics has been proposed to specifically address this problem. In particular, punctuations explicitly mark the end of a subset of data and, hence, enable purging of the stored data which will not contribute to any new query results. Given a set of available punctuation schemes, if one can identify that a CJQ still requires unbounded storage, then this query can be flagged as unsafe and can be prevented from running. Unfortunately, while punctuation semantics is clearly useful, the mechanisms to identify if and how a particular CJQ could benefit from a given set of punctuation schemes are not yet known. In this paper, we provide sufficient and necessary conditions for checking whether a CJQ can be safely executed under a given set of punctuation schemes or not. In particular, we introduce a novel punctuation graph to aid the analysis of the safety for a given query. We show that the safety checking problem can be done in polynomial time based on this punctuation graph construct. In addition, various issues and challenges related to the safety checking of CJQs are highlighted.