Hash tables are one of the most fundamental data structures in computer science, in both theory and practice. They are especially useful in external memory, where their query performance approaches the ideal cost of just one disk access. Knuth [16] gave an elegant analysis showing that with some simple collision resolution strategies such as linear probing or chaining, the expected average number of disk I/Os of a lookup is merely 1 + 1/2(b) , where each I/O can read and/or write a disk block containing b items. Inserting a new item into the hash table also costs 1 + 1/2(b) I/Os, which is again almost the best one can do if the hash table is entirely stored on disk. However, this requirement is unrealistic since any algorithm operating on an external hash table must have some internal memory (at least (1) blocks) to work with. The availability of a small internal memory buffer can dramatically reduce the amortized insertion cost to o(1) I/Os for many external memory data structures. I...