Efficient OLAP query processing in distributed data warehouses

TL;DR: Two algorithms to decompose a complex aggregate query to its group query components are presented and a syntactic criterion to identify group queries in SQL is presented, showing that every group query can be expressed in a way that satisfies this criterion.

TL;DR: This article reviews the concept of grouping variable and describes a simple SQL extension that enables the facile expression of a large class of practical data analysis queries and studies the potential of grouping variables in formulating decision support queries over streams of data.

TL;DR: A storage structure PK-map and a query processing algorithm is proposed that not only decreases the inter-node communication overhead but also decreases the work load of joins.

TL;DR: A framework for building logical schema and query decomposition procedure for federations of data warehouses has been proposed and it is proposed that a user query refers to the schema of the federation, therefore, the query decompose process is needed.

TL;DR: An overview of data warehousing and OLAP technologies, with an emphasis on their new requirements, is provided, based on a tutorial presented at the VLDB Conference, 1996.

TL;DR: This third edition of a classic textbook can be used to teach at the senior undergraduate and graduate levels and concentrates on fundamental theories as well as techniques and algorithms in distributed data management.

TL;DR: The data cube operator as discussed by the authors generalizes the histogram, cross-tabulation, roll-up, drill-down, and sub-total constructs found in most report writers.

TL;DR: The paper presents the “textbook” architecture for distributed query processing and a series of techniques that are particularly useful for distributed database systems, and discusses different kinds of distributed systems such as client-server, middleware (multitier), and heterogeneous database systems and shows how query processing works in these systems.