Optimal Aggregation Algorithms for Middleware

Assume that each object in a database has m grades, or scores, one for each of m attributes. For example, an object can have a color grade, that tells how red it is, and a shape grade, that tells how round it is. For each attribute, there is a sorted list, which lists each object and its grade under that attribute, sorted by grade (highest grade first). Each object is assigned an overall grade, that is obtained by combining the attribute grades using a fixed monotone aggregation function, or combining rule, such as min or average. To determine the top k objects, that is, k objects with the highest overall grades, the naive algorithm must access every object in the database, to find its grade under each attribute. Fagin has given an algorithm (``Fagin's Algorithm'', or FA) that is much more efficient. For some monotone aggregation functions, FA is optimal with high probability in the worst case. We analyze an elegant and remarkably simple algorithm (``the threshold algor...

• Type: Conference
• Year: 2001
• Where: PODS
• Authors: Ronald Fagin, Amnon Lotem, Moni Naor
• Keywords: Database, Monotone Aggregation Functions, Overall Grade, PODS 2001, Sorted Access