Related papers: A Join Index for XML Data Warehouses
To process a large volume of data, modern data management systems use a collection of machines connected through a network. This paper looks into the feasibility of scaling up such a shared-nothing system while processing a compute- and…
Database management systems (DBMSs) carefully optimize complex multi-join queries to avoid expensive disk I/O. As servers today feature tens or hundreds of gigabytes of RAM, a significant fraction of many analytic databases becomes…
Presently, large enterprises rely on database systems to manage their data and information. These databases are useful for conducting daily business transactions. However, the tight competition in the marketplace has led to the concept of…
The data warehousing is becoming increasingly important in terms of strategic decision making through their capacity to integrate heterogeneous data from multiple information sources in a common storage space, for querying and analysis. So…
HRDBMS is a novel distributed relational database that uses a hybrid model combining the best of traditional distributed relational databases and Big Data analytics platforms such as Hive. This allows HRDBMS to leverage years worth of…
This paper proposes a set of tools to help dealing with XML database evolution. It aims at establishing a multi-system environment where a global integrated system works in harmony with some local original ones, allowing data translation in…
In this paper we tackle the fragmentation problem for highly distributed databases. In such an environment, a suitable fragmentation strategy may provide scalability and availability by minimizing distributed transactions. We propose an…
Indexing is an effective way to support efficient query processing in large databases. Recently the concept of learned index, which replaces or complements traditional index structures with machine learning models, has been actively…
With the wide development of databases in general and data warehouses in particular, it is important to reduce the tasks that a database administrator must perform manually. The idea of using data mining techniques to extract useful…
XML simplifies data exchange among heterogeneous computers, but it is notoriously verbose and has spawned the development of many XML-specific compressors and binary formats. We present an XML test corpus and a combined efficiency metric…
Data discovery is a major challenge in enterprise data analysis: users often struggle to find data relevant to their analysis goals or even to navigate through data across data sources, each of which may easily contain thousands of tables.…
Spreadsheet software is the tool of choice for interactive ad-hoc data management, with adoption by billions of users. However, spreadsheets are not scalable, unlike database systems. On the other hand, database systems, while highly…
As the fundamental phrase of collecting and analyzing data, data integration is used in many applications, such as data cleaning, bioinformatics and pattern recognition. In big data era, one of the major problems of data integration is to…
The aim of this article is to present an overview of the major families of state-of-the-art index and materialized view selection methods, and to discuss the issues and future trends in data warehouse performance optimization. We…
Multidimensional in data warehouse is a compulsion and become the most important for information delivery, without multidimensional data warehouse is incomplete. Multidimensional give the able to analyze business measurement in many…
In the last few years, much effort has been devoted to developing join algorithms in order to achieve worst-case optimality for join queries over relational databases. Towards this end, the database community has had considerable success in…
The aim of this article is to present an overview of the major families of state-of-the-art data-base benchmarks, namely: relational benchmarks, object and object-relational benchmarks, XML benchmarks, and decision-support benchmarks, and…
One of the purposes of Big Data systems is to support analysis of data gathered from heterogeneous data sources. Since data warehouses have been used for several decades to achieve the same goal, they could be leveraged also to provide…
Traditionally, DBMSs separate their storage layer from their indexing layer. While the storage layer physically materializes the database and provides low-level access methods to it, the indexing layer on top enables a faster locating of…
There has been considerable research on automated index tuning in database management systems (DBMSs). But the majority of these solutions tune the index configuration by retrospectively making computationally expensive physical design…