Dimension (data warehouse) | EPFL Graph Search

A dimension is a structure that categorizes facts and measures in order to enable users to answer business questions. Commonly used dimensions are people, products, place and time. (Note: People and time sometimes are not modeled as dimensions.) In a data warehouse, dimensions provide structured labeling information to otherwise unordered numeric measures. The dimension is a data set composed of individual, non-overlapping data elements. The primary functions of dimensions are threefold: to provide filtering, grouping and labelling. These functions are often described as "slice and dice". A common data warehouse example involves sales as the measure, with customer and product as dimensions. In each sale a customer buys a product. The data can be sliced by removing all customers except for a group under study, and then diced by grouping by product. A dimensional data element is similar to a categorical variable in statistics. Typically dimensions in a data warehouse are organized i

High-dimensional Data Cubes

Sachin Basil John, Christoph Koch

This paper introduces an approach to supporting high-dimensional data cubes at interactive query speeds and moderate storage cost. The approach is based on binary(-domain) data cubes that are judiciously partially materialized; the missing information can be quickly reconstructed using statistical or linear programming techniques. This enables new applications such as exploratory data analysis for feature engineering and other fields of data science. Moreover, it allows us to use data cubes in data warehouses and data lakes without design regret. It removes the need to compromise when building a data cube — all columns that we might ever wish to use can be included as dimensions. As a collateral benefit, our approach also speeds up certain dice, roll-up, and drill-down operations on data cubes with hierarchical dimensions compared to traditional data cubes.

2022

Scaling up Mixed Workloads: a Battle of Data Freshness, Flexibility, and Scheduling

Anastasia Ailamaki, Iraklis Psaroudakis

The common "one size does not fit all" paradigm isolates transactional and analytical workloads into separate, specialized database systems. Operational data is periodically replicated to a data warehouse for analytics. Competitiveness of enterprises today, however, depends on real-time reporting on operational data, necessitating an integration of transactional and analytical processing in a single database system. The mixed workload should be able to query and modify common data in a shared schema. The database needs to provide performance guarantees for transactional workloads, and, at the same time, efficiently evaluate complex analytical queries. In this paper, we share our analysis of the performance of two main-memory databases that support mixed workloads, SAP HANA and HyPer, while evaluating the mixed workload CH-benCHmark. By examining their similarities and differences, we identify the factors that affect performance while scaling the number of concurrent transactional and analytical clients. The three main factors are (a) data freshness, i.e., how recent is the data processed by analytical queries, (b) flexibility, i.e., restricting transactional features in order to increase optimization choices and enhance performance, and (c) scheduling, i.e., how the mixed workload utilizes resources. Specifically for scheduling, we show that the absence of workload management under cases of high concurrency leads to analytical workloads overwhelming the system and severely hurting the performance of transactional workloads.

Springer International Publishing AG2014

An informed environment for inhabited city simulation

In combination with the rapid technical improvements of computers, building large virtual scenes has become a popular field in computer graphics for education, films or games. Often, virtual humans populate scenes such as real reconstructed city, disappeared building or virtual town, and they are expected to provide a real life feeling. The specific aim of this thesis is to perform action planning in order to populate these scenes with virtual humans. To achieve this goal, we use a database dedicated to urban life simulation called an Informed Environment. This report presents a design methodology and associated tools for animation purposes in large scale scenes. We propose a space decomposition of the scene into a set of entities allowing automatic path computing regardless of scene size. In order to achieve human behavioural simulation, we decide to focus on the definition of scene decomposition resulting in the creation of a database. The first stage of this work consisted of building a database simulating "urban knowledge" (knowledge about location and associated functionalities) and virtual perceptions (contact with the ground, object perception etc.). These virtual perceptions, necessary for autonomy simulation, but highly costly in time processor consuming, are simulated through database access corresponding to our Informed Environment. We decided to define an ideal 3D model as a test-bed for concepts and tools, integrating both geometrical and semantical data. We also define rules for the design, storage and display options. The "urban knowledge" attached to a simulation is the base of a generic hierarchical model of space decomposition. This model of space decomposition of the 3D scene is related to a specific type of simulation and directly applied to the modelling of the tridimensional scene. Once the database is created, some tools access the database content for path/action computation, knowledge concerning a place, display optimization, places and objects. As 3D data visibility and verification with associated semantic information are difficult to observe, we have defined some tools for database visualisation, verification and modification (the "applicity" software). These tools have been developed in order to offer assistance to the user during manipulation of three-dimensional data. This system is applied to real reconstructed scenes in the framework of the European project CROSSES, for panic simulation during accident. Our field of research has also been extended to the domain of disability help in order to compute path for people with reduced mobility. Our goal was to define some tools and a few constraint methodology that automatically generate all information needed for simulating autonomous behaviour in an urban environment.

EPFL2001

An informed environment for inhabited city simulation

EPFL2001