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Materialized Views in a Distributed Event Stream Processing Environment
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Materialized Views over Heterogeneous Structured Data Sources in a Distributed Event Stream Processing
Environment
Funded by NSF Grant CSR: #0915325

Software systems are becoming
increasingly complex, requiring
the coordination of heterogeneous
structured data sources in a
loosely-coupled distributed
environment with support for
handling events and streaming
data. Some sample systems
include homeland security,
criminal justice, supply chain
management, health care, and
consumer monitoring systems to
support marketing,
personalization, and fraud
detection. Such software systems
involve query expressions over the
data for detecting events,
monitoring conditions, handling streams, and querying data. This research analyzes the dependencies among these
filtering query expressions over structured data sources defined in different language components over relational or
data-centric XML to detect common subexpressions as candidates for materialized views. When views are
materialized, the results of the computed view are stored so that subsequent access to the view can efficiently
retrieve information to avoid the cost of recomputing the entire view on subsequent references. This performance
improvement is even more critical with distributed data sources. However, the materialized view must be updated if
any data source that it depends on has changed. To avoid the recomputation of the entire view, an incremental view
maintenance algorithm uses the change to incrementally compute updates to the materialized view. Using stateof-the-art commercial and open-source components, a prototype environment that supports a distributed event
stream processing environment provides a research and evaluation platform to explore the identification,
specification, and incremental evaluation of materialized views over heterogeneous, distributed structured data
sources.
Disclaimer: Any opinions, findings, and conclusions or recommendations expressed in this material are those of
the author(s) and do not necessarily reflect the views of the National Science Foundation.
Copyright 2009-2014. Arizona State University. All rights reserved.

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