Building the data warehouse (2nd ed.)
Building the data warehouse (2nd ed.)
The data warehouse toolkit: practical techniques for building dimensional data warehouses
The data warehouse toolkit: practical techniques for building dimensional data warehouses
An array-based algorithm for simultaneous multidimensional aggregates
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
A foundation for capturing and querying complex multidimensional data
Information Systems - Data warehousing
Data Cube: A Relational Aggregation Operator Generalizing Group-By, Cross-Tab, and Sub-Total
ICDE '96 Proceedings of the Twelfth International Conference on Data Engineering
Semantic Data Caching and Replacement
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
A predicate-based caching scheme for client-server database architectures
The VLDB Journal — The International Journal on Very Large Data Bases
Operators for multidimensional aggregate data
Multidimensional databases
SOSP '03 Proceedings of the nineteenth ACM symposium on Operating systems principles
Historical spatio-temporal aggregation
ACM Transactions on Information Systems (TOIS)
C-store: a column-oriented DBMS
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Interpreting the data: Parallel analysis with Sawzall
Scientific Programming - Dynamic Grids and Worldwide Computing
Map-reduce-merge: simplified relational data processing on large clusters
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
MapReduce: simplified data processing on large clusters
Communications of the ACM - 50th anniversary issue: 1958 - 2008
Advanced Data Warehouse Design: From Conventional to Spatial and Temporal Applications (Data-Centric Systems and Applications)
Pig latin: a not-so-foreign language for data processing
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
SCOPE: easy and efficient parallel processing of massive data sets
Proceedings of the VLDB Endowment
Data mining-based materialized view and index selection in data warehouses
Journal of Intelligent Information Systems
MapReduce and parallel DBMSs: friends or foes?
Communications of the ACM - Amir Pnueli: Ahead of His Time
Spatial Queries Evaluation with MapReduce
GCC '09 Proceedings of the 2009 Eighth International Conference on Grid and Cooperative Computing
Building a high-level dataflow system on top of Map-Reduce: the Pig experience
Proceedings of the VLDB Endowment
Hive: a warehousing solution over a map-reduce framework
Proceedings of the VLDB Endowment
Scalable test data generation from multidimensional models
Proceedings of the ACM SIGSOFT 20th International Symposium on the Foundations of Software Engineering
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Data warehouses and OLAP systems are business intelligence technologies. They allow decision-makers to analyze on the fly huge volumes of data represented according to the multidimensional model. Cloud computing on the impulse of ICT majors like Google, Microsoft and Amazon, has recently focused the attention. OLAP querying and data warehousing in such a context consists in a major issue. Indeed, problems to be tackled are basic ones for large scale distributed OLAP systems (large amount of data querying, semantic and structural heterogeneity) from a new point of view, considering specificities from these architectures (pay-as-you-go rule, elasticity, and user-friendliness). In this paper we address the pay-as-you-go rules for warehousing data storage. We propose to use the multidimensional arrays storage techniques for clouds. First experiments validate our proposal.