Applying OLAP Pre-Aggregation Techniques to ... - Jacobs University

Chapter 2
Background and Related Work
This chapter describes existing database technology for two environments: GIS/remotesensing
imaging and data warehousing/OLAP. Our investigation shows that conceptual
data models and operations are similar in both application domains. This suggests
that array database technology can be substantially enhanced by adopting a preaggregation
scheme using a basis of existing OLAP technology.
2.1 Array Databases
Multidimensional data analysis has recently taken the spotlight in the context of
scientific applications. A fundamental demand from science users is extremely fast
response times for multidimensional queries. While most scientific users can use relational
tables and have been forced to do so by many commercial DBMS systems, only
a few users find tables to be a natural data model that closely matches their data. Furthermore,
few users are satisfied with SQL as the interface language [30]. In contrast,
it appears that arrays are a natural data model for a significant subset of science users,
specifically in astronomy, oceanography, and remote-sensing applications. Moreover,
a table with a primary key is merely a 1D array. Hence, an array data model can
subsume the needs of users who are satisfied with tables.
Next we review the existing database technology supporting multidimensional arrays
in scientific applications: 1D sensor time-series, 2D satellite imagery, 3D image
time-series, and 4D atmospheric data.
2.1.1 Basic Notion of Arrays
Several approaches have been proposed towards the formalization of arrays and
array query languages. The underlying methods of formalization differ, and it is still
an open discussion. However, the following notion of arrays is quite common [79]:
An array is a set of cells of a fixed data type T , with a fixed cell size. Each
cell corresponds to one element in the multidimensional domain of the array. The
domain D of an array is a d-dimensional subinterval of a discrete coordinate set S =
S 1 × ... × S d , where each S i , i = 1, ..., d is a finite totally ordered discrete set and d is
the dimensionality of the array.
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