Abstract :
Given a fixed set S of n keys, we would like to store them so that queries of the form "Is x ∈ S?" can be answered quickly. A commonly employed scheme to solve this problem uses a table to store the keys, and a special purpose program depending on S which probes the table. We analyze the tradeoff between the maximum number of probes allowable to answer a query, and the information-theoretic complexity of the program to do so. Perfect hashing (where the query must be answered in one probe) has a program complexity of nlog2 e(1 + o(1)) bits, and this lower bound can be achieved. Under a model combining perfect hashing and binary search methods, it is shown that for k probes to the table, nk/2k+1(1 + o(1)) bits are necessary and sufficient to describe a table searching algorithm. This model gives some information-theoretic bounds on the complexity of searching an external memory. We examine some schemes where pointers are allowed in the table, and show that for k probes to the table, about nlog2e/e(k+1)!(1+o(1)) bits are necessary and sufficient to describe the search. Finally, we prove some lower bounds on the worst case performance of hash functions described by bounded Boolean circuits, and worst case performance of universal classes of hash functions.
