By Lei Chen, Chengfei Liu, Xiao Zhang, Shan Wang, Darijus Strasunskas, Stein L. Tomassen, Jinghai Rao, Wen-Syan Li, K. Selcuk Candan, Dickson K. W. Chiu, Yi Zhuang

This quantity includes papers from 4 APWeb/WAIM 2009 workshops, that are 1. foreign Workshop on Web-based Contents administration applied sciences (WCMT 2009), 2. foreign Workshop on Real-Time enterprise Intelligence (RTBI 2009), three. foreign Workshop on DataBase and knowledge Retrieval and facets in comparing Holistic caliber of Ontology-based info Retrieval (DBIR-ENQOIR 2009), in addition to four. foreign Workshop on approach acutely aware details platforms (PAIS 2009. those 4 workshops have been chosen from a public call-for-proposals approach. The workshop organizers have positioned a major volume of attempt into soliciting and choosing learn papers with a stability of top quality and new principles and new functions.

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Nodes are connected by a gigabit network. Every two nodes are equal, and none is master or slave. We optimize the storage architecture and add one level of NetMemory, which is the memory resource of other nodes. On every node, there is a MMDB based on the open source MMDB MonetDB [5] which adopts the column stored model. Each column is stored as a Binary Association Table (BAT). BAT is the smallest object of operation. Query is transformed into MonetDB Assembly Language (MAL). MAL is a kind of execution plan, also a sequence of operations.

There are not too many attributes in practical applications, especially for OLAP application. However, a lot of complex queries bring on “Skew” phenomenon for visiting attributes. That means so many values of the Attribute Distance Matrix (ADM) are 1. Hierarchical clustering method is simple, easy to implement and more suitable than other methods. There are a set of N attributes to be clustered, an N*N distance matrix dist[N][N], and M nodes in ScaMMDB. Starting by assigning each attribute to a cluster, so that if you have N attributes, you now have N clusters, each contains just one attribute.

Then expressions with outmost negation operator are rewritten into expressions with predicates injected into the denotation of operators in right places. At last we compute the temporal relevance of primitive events to the registered queries. An arbitrarily complex event query is converted to an event tree. There is one node in the tree for every temporal related and logic operator (sequence, its variants like concurrency, and logic like conjunction) in the query and Temporal Restriction Query Optimization for Event Stream Processing 27 Fig.

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