Researchers in data management have recently recognized the
importance of a new class of data-intensive applications that
requires managing data streams, i.e., data composed of continuous,
real-time sequence of items. Streaming applications pose new and
interesting challenges for data management systems. Such
application domains require queries to be evaluated continuously as
opposed to the one time evaluation of a query for traditional
applications. Streaming data sets grow continuously and queries
must be evaluated on such unbounded data sets. These, as well as
other challenges, require a major rethink of almost all aspects of
traditional database management systems to support streaming
applications.
Stream Data Management comprises eight invited chapters by
researchers active in stream data management. The collected
chapters provide exposition of algorithms, languages, as well as
systems proposed and implemented for managing streaming data.
Stream Data Management is designed to appeal to researchers or
practitioners already involved in stream data management, as well
as to those starting out in this area. This book is also suitable
for graduate students in computer science interested in learning
about stream data management.
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