The Unified Modeling Language user guide
The Unified Modeling Language user guide
On computing correlated aggregates over continual data streams
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Models and issues in data stream systems
Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Complex Aggregation at Multiple Granularities
EDBT '98 Proceedings of the 6th International Conference on Extending Database Technology: Advances in Database Technology
Querying Multiple Features of Groups in Relational Databases
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
The Design and Implementation of a Sequence Database System
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
Exploiting Punctuation Semantics in Continuous Data Streams
IEEE Transactions on Knowledge and Data Engineering
User Defined Aggregates in Object-Relational Systems
ICDE '00 Proceedings of the 16th International Conference on Data Engineering
Gigascope: a stream database for network applications
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Monitoring streams: a new class of data management applications
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
AQuery: query language for ordered data, optimization techniques, and experiments
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
Using grouping variables to express complex decision support queries
Data & Knowledge Engineering
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This article identifies an interesting class of applications where stream sessions may be organized in a hierarchical fashion - i.e. sessions may contain sub-sessions. For example, log streams from call centers belong to different call sessions and call sessions consist of services' sub-sessions. We may want to monitor statistics and perform accounting at any level on this hierarchy, relative to any other higher level (e.g. monitoring the average service session per call vs. the average service session for the entire system.) We argue that data streams of this kind have rich procedural semantics - i.e. behavior - and therefore a semantically rich model should be used: a session may be defined by opening and closing conditions, may have data and methods and may consist of sub-sessions. We propose a simple conceptual model based on the notion of "session" - similar to a class in an object-oriented environment -- having lifetime semantics. Queries on top of this schema can be formulated via HSA (hierarchical stream aggregate) expressions. We describe an algorithm dictating how stream data flow down session hierarchies and discuss potential evaluation and optimization techniques for HSAs. Finally we introduce NESTREAM, a prototype implementation for these ideas and give some preliminary experimental results.