A dynamic load balancing strategy for parallel datacube computation
Proceedings of the 2nd ACM international workshop on Data warehousing and OLAP
Eddies: continuously adaptive query processing
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
NiagaraCQ: a scalable continuous query system for Internet databases
SIGMOD '00 Proceedings of the 2000 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
Data Cube: A Relational Aggregation Operator Generalizing Group-By, Cross-Tab, and Sub-Totals
Data Mining and Knowledge Discovery
Continuous queries over data streams
ACM SIGMOD Record
Gigascope: a stream database for network applications
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Parallel ROLAP Data Cube Construction on Shared-Nothing Multiprocessors
Distributed and Parallel Databases
Efficient incremental maintenance of data cubes
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
History offset implementation scheme for large scale multidimensional data sets
Proceedings of the 2008 ACM symposium on Applied computing
Supporting asynchronous update for distributed data cubes
Journal of Network and Computer Applications
Frequency-based load shedding over a data stream of tuples
Information Sciences: an International Journal
An extendible array based implementation of relational tables for multi dimensional databases
DaWaK'05 Proceedings of the 7th international conference on Data Warehousing and Knowledge Discovery
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We propose a distributed construction scheme of MOLAP data cubes in related sites on the network. The server that directly receives tuple data sent from tuple generation source constructs the base cuboid, and sends them to downstream sites in tuple stream. The downstream site receives the tuple data to aggregate and construct its own cuboid whose dimension is lower than the upstream cuboid, then sends the aggregated data to its downstream sites. Using the implementation scheme of multidimensional datasets based on the history-offset tuple encoding method, the tuple stream can be processed efficiently to construct cuboids in real-time on each site, while MOLAP operations can be processed against one of the data cube versions in background. In this paper, we describe our tuple stream processing scheme and distributed data cube construction, then evaluate the required communication cost.