This article addresses the query performance issue for Relational OLAP (ROLAP) datacubes. We present RCUBE, a distributed multidimensional ROLAP indexing scheme which is practical to implement, requires only a small communication volume, and is fully adapted to distributed disks. Our solution is efficient for spatial searches in high dimensions and scalable in terms of data sizes, dimensions, and number of processors. Our method is also incrementally maintainable. Using "surrogate" group-bys, it allows for the efficient processing of arbitrary OLAP queries on partial cubes, where not all of the group-bys have been materialized. Our experiments with RCUBE show that the ROLAP advantage of better scalability, in comparison to MOLAP, can be mai...
Computing multiple related group-bys and aggregates is one of the core operations of On-Line Analyti...
Being able to efficiently answer arbitrary OLAP queries that aggregate along any combination of dime...
On-line analytical processing (OLAP) has become a very useful tool in decision support systems built...
This paper addresses the query performance issue for Relational OLAP (ROLAP) datacubes. We present R...
This paper addresses the query performance issue for Relational OLAP (ROLAP) datacubes. We present a...
The pre-computation of data cubes is critical to improving the response time of On-Line Analytical P...
Online Analytical Processing is a powerful framework for the analysis of organizational data. OLAP i...
We present the cgmOLAP server, the first fully functional parallel OLAP system able to build data cu...
ROLAP (Relational OLAP) and MOLAP (Multidimensional OLAP) are two opposing techniques for building O...
Online Analytical Processing is a powerful framework for the analysis of organizational data. OLAP i...
OLAP models can be categorized with two types: MOLAP (multidimensional OLAP) and ROLAP (relational O...
as the dominant approach in data warehousing with decision support applications. In order to enhance...
This paper presents an improved parallel method for generating ROLAP data cubes on a shared-nothing ...
With huge amounts of data collected in various kinds of applications, data warehouse is becoming a m...
On-line Analytical Processing (OLAP) has become one of the most powerful and prominent technologies ...
Computing multiple related group-bys and aggregates is one of the core operations of On-Line Analyti...
Being able to efficiently answer arbitrary OLAP queries that aggregate along any combination of dime...
On-line analytical processing (OLAP) has become a very useful tool in decision support systems built...
This paper addresses the query performance issue for Relational OLAP (ROLAP) datacubes. We present R...
This paper addresses the query performance issue for Relational OLAP (ROLAP) datacubes. We present a...
The pre-computation of data cubes is critical to improving the response time of On-Line Analytical P...
Online Analytical Processing is a powerful framework for the analysis of organizational data. OLAP i...
We present the cgmOLAP server, the first fully functional parallel OLAP system able to build data cu...
ROLAP (Relational OLAP) and MOLAP (Multidimensional OLAP) are two opposing techniques for building O...
Online Analytical Processing is a powerful framework for the analysis of organizational data. OLAP i...
OLAP models can be categorized with two types: MOLAP (multidimensional OLAP) and ROLAP (relational O...
as the dominant approach in data warehousing with decision support applications. In order to enhance...
This paper presents an improved parallel method for generating ROLAP data cubes on a shared-nothing ...
With huge amounts of data collected in various kinds of applications, data warehouse is becoming a m...
On-line Analytical Processing (OLAP) has become one of the most powerful and prominent technologies ...
Computing multiple related group-bys and aggregates is one of the core operations of On-Line Analyti...
Being able to efficiently answer arbitrary OLAP queries that aggregate along any combination of dime...
On-line analytical processing (OLAP) has become a very useful tool in decision support systems built...