Trie hashing is a scheme, proposed by Litwin, for indexing records with very long alphanumeric keys. The records are grouped into buckets of capacity b and maintained on secondary storage. To retrieve a record, the memory resident trie is traversed from the root to a leaf node where the address of the target bucket is found. Using the address found, the data bucket is read into memory and searched to determine the presence or absence of the record. The scheme, for all practical purposes, locates a record in one or two disk accesses. Unlike a trie, the scheme proposed suffers from potential degeneracy when the keys inserted are ordered and has an expensive reconstruction cost if a system failure occurs during a session. We present a new approach to implementing Trie Hashing that resolves the degeneracy problem. Our approach combines the basic trie hashing algorithm with the balancing techniques of the Red-Black Binary Search Tree, to produce a relatively balanced trie hashing scheme. As...

We apply the trie structures to indexing, storing and querying structured data on secondary storage. We are interested in the storage compactness, the I/O efficiency, the order-preserving properties, the general orthogonal range queries and the exact match queries for very large files and databases. We also apply the trie structures to relational joins (set operations). We compare trie structures to various data structures on secondary storage: multipaging and grid files in the direct access method category, R-trees/R*-trees and X-trees in the logarithmic access cost category, as well as some representative join algorithms for performing join operations. Our results show that range queries by trie method are superior to these competitors in search cost when queries return more than a few records and are competitive to direct access methods for exact match queries. Furthermore, as the trie structure compresses data, it is the winner in terms of storage compared to all other methods mentioned above. We also present a new tidy function for order-preserving key-to-address transformation. Our tidy function is easy to construct and cheaper in access time and storage cost compared to its closest competitor.

Trie hashing is a scheme, proposed by Litwin, for indexing records with very long alphanumeric keys. The records are grouped into buckets of capacity b records per bucket and maintained on secondary storage. To retrieve a record, the memory resident trie is traversed from the root to a leaf node where the address of the target bucket is found. Using the address found, the data bucket is read into memory and searched to determine the presence or absence of the record. The scheme, for all practical purposes, locates a record in one or two disk accesses. Unlike a trie, the scheme suffers from: i) potential degeneracy when the keys inserted are ordered, ii) expensive reconstruction cost if a system failure occurs during a session. We present a new approach to implementing Trie Hashing that resolves the problem of potential degeneracy. Our approach combines the basic trie hashing algorithm with the balancing techniques of the Red-Black Binary Search Tree, to produce a relatively balanced tr...