Indexing Semistructured Data

Abstract

This paper describes techniques for building and exploiting indexes on semistructured data: data that may not have a fixed schema and that may be irregular or incomplete. We first present a general framework for indexing values in the presence of automatic type coercion. Then based on Lore, a DBMS for semistructured data, we introduce four types of indexes and illustrate how they are used during query processing. Our techniques and indexing structures are fully implemented and integrated into the Lore prototype.