Algorithms and Support for Horizontal Class Partitioning in Object-Oriented Databases

Abstract

Horizontal partitioning is a logical database design technique which facilitates efficient execution of queries by reducing the irrelevant objects accessed. Given a set of most frequently executed queries on a class, the horizontal partitioning generates horizontal class fragments (each of which is a subset of object instances of the class), that meet the queries requirements. There are two types of horizontal class partitioning, namely, primary and derived. Primary horizontal partitioning of a class is performed using predicates of queries accessing the class. Derived horizontal partitioning of a class is the partitioning of a class based on the horizontal partitioning of another class. We present algorithms for both primary and derived horizontal partitioning and discuss some issues in derived horizontal partitioning and present their solutions. There are two important aspects for supporting database operations on a partitioned database, namely, fragment localization for queries and object migration for updates. Fragment localization deals with identifying the horizontal fragments that contribute to the result of the query, and object migration deals with migrating objects from one class fragment to another due to updates. We provide novel solutions to these two problems, and finally we show the utility of horizontal partitioning for query processing.