Parallel database systems: the future of high performance database systems
Communications of the ACM
Parallel sorting by regular sampling
Journal of Parallel and Distributed Computing
Implementing data cubes efficiently
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
An array-based algorithm for simultaneous multidimensional aggregates
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
T2: a customizable parallel database for multi-dimensional data
ACM SIGMOD Record
High performance multidimensional analysis of large datasets
Proceedings of the 1st ACM international workshop on Data warehousing and OLAP
Bottom-up computation of sparse and Iceberg CUBE
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
Polar: an architecture for a parallel ODMG compliant object database
Proceedings of the ninth international conference on Information and knowledge management
Automating physical database design in a parallel database
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Distributed and Parallel Databases - Special issue: Parallel and distributed data mining
R-trees: a dynamic index structure for spatial searching
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
Prototyping Bubba, A Highly Parallel Database System
IEEE Transactions on Knowledge and Data Engineering
The Gamma Database Machine Project
IEEE Transactions on Knowledge and Data Engineering
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
Multi-Dimensional Database Allocation for Parallel Data Warehouses
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Data partitioning and load balancing in parallel disk systems
The VLDB Journal — The International Journal on Very Large Data Bases
Hierarchical dwarfs for the rollup cube
DOLAP '03 Proceedings of the 6th ACM international workshop on Data warehousing and OLAP
Parallel ROLAP Data Cube Construction on Shared-Nothing Multiprocessors
Distributed and Parallel Databases
Parallel SQL execution in Oracle 10g
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Experimental evidence on partitioning in parallel data warehouses
Proceedings of the 7th ACM international workshop on Data warehousing and OLAP
OS support for a commodity database on PC clusters: distributed devices vs. distributed file systems
ADC '05 Proceedings of the 16th Australasian database conference - Volume 39
Communication and Memory Optimal Parallel Data Cube Construction
IEEE Transactions on Parallel and Distributed Systems
Physical and Virtual Partitioning in OLAP Database Clusters
SBAC-PAD '05 Proceedings of the 17th International Symposium on Computer Architecture on High Performance Computing
The cgmCUBE project: Optimizing parallel data cube generation for ROLAP
Distributed and Parallel Databases
CURE for cubes: cubing using a ROLAP engine
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
A hilbert space compression architecture for data warehouse environments
DaWaK'07 Proceedings of the 9th international conference on Data Warehousing and Knowledge Discovery
High Performance Analytics with the R3-Cache
DaWaK '09 Proceedings of the 11th International Conference on Data Warehousing and Knowledge Discovery
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Online Analytical Processing (OLAP) has become a primary component of today's pervasive Decision Support systems. The rich multi-dimensional analysis that OLAP provides allows corporate decision makers to more fully assess and evaluate organizational progress than ever before. However, as the data repositories upon which OLAP is based become larger and larger, single CPU OLAP servers are often stretched to, or even beyond, their limits. In this paper, we present a comprehensive architectural model for a fully parallelized OLAP server. Our multi-node platform actually consists of a series of largely independent sibling servers that are "glued" together with a lightweight MPI-based Parallel Service Interface (PSI). Physically, we target the commodityoriented, "shared nothing" Linux cluster, a model that provides an extremely cost effective alterative to the "shared everything" commercial platforms often used in high-end database environments. Experimental results demonstrate both the viability and robustness of the design.