Data Streams: Models and Algorithms primarily discusses issues related to the mining aspects of data streams. Recent progress in hardware technology makes it possible for organizations to store and record large streams of transactional data. For example, even simple daily transactions such as using ...
M. Zaharia, T. Das, H. Li, S.Shenker, and I. Stoica, “Discretized Streams: An Efficient and Fault-TolerantModel for Stream Processing on Large Clusters” E. Jacobsen and R. Lyons, “The Sliding DFT“ Elmagarmid, Data Streams Modelsand Algorithms N. Marz, “Big Data Lambda Architec...
M. Zaharia, T. Das, H. Li, S.Shenker, and I. Stoica, “Discretized Streams: An Efficient and Fault-TolerantModel for Stream Processing on Large Clusters” E. Jacobsen and R. Lyons, “The Sliding DFT“ Elmagarmid, Data Streams Modelsand Algorithms N. Marz, “Big Data Lambda Architec...
Data streams: models and algorithms (advances in database systems) (2006) M.K. Albertini et al. A self-organizing neural network for detecting novelties Proceedings of the 2007 acm symposium on applied computing (2007) K. Alligood Chaos : an introduction to dynamical systems (1997) C. Band...
Elmagarmid, Data Streams Modelsand Algorithms N. Marz, “Big Data Lambda Architecture” J. Kinley, “The Lambda architecture: principles for architecting realtimeBig Data systems” http://hortonworks.com/hadoop/tez/ ...
Aggarwal CC, Han J, Wang J, Yu PS (2007) On clustering massive data streams: a summarization paradigm. In: Advances in database systems: data streams models and algorithms, vol 31. Springer, Heidelberg, pp 9–38 Ai C, Du R, Zhang M, Li Y (2009) In-network historical data storage ...
Normally, timestamps can be implemented in two forms: (1) as a string of absolute time-values, which consumes more resources to be processed, but makes it easier for developers to devisejointalgorithms on separate streams; or (2) as a sequence of positive real-time intervals that only reco...
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Oracle also supports AI-driven solutions based on machine learning algorithms, so you might consider this if you’re into ML. IBM Streaming Analytics IBM Streaming Analytics is available for building real-time analytical applications. It’s powered by IBM Streams, a data platform for stream process...
It also incorporates advanced streamlined algorithms from Huawei, and the modeling library from its Noah's Ark Lab. These functions provide powerful support for operators to build big data modeling capabilities. The data service layer is rich with outstanding features: ...