Provided by: Harvard University
Topic: Big Data
Date Added: Dec 2006
Database indices provide a non-discriminative navigational infrastructure to localize tuples of interest. Their maintenance cost is taken during database updates. In this paper, the authors study the complementary approach, addressing index maintenance as part of query processing using continuous physical reorganization, i.e., cracking the database into manageable pieces. The motivation is that by automatically organizing data the way users request it; they can achieve fast access and the much desired self-organized behavior. They present the first mature cracking architecture and report on their implementation of cracking in the context of a fully fledged relational system.