The sum of the digits classifies the data into the highest number of buckets, thus making the job to track the buckets more difficult than the rest.

Bucket overflow can occur in many ways. When a bucket does not have enough space, there are insufficient buckets, when a bucket skew occurs.

Hashing can be used for 2 different purposes, hash file organization and hash index organization. In a hash index organization, we organize the search keys, with their associated pointers, into a hash file structure.

If K denotes the set of all the search key values, and B denotes the set of all bucket addresses, a function h from K to B is called as the hash function. It determines which bucket should contain the data in question.

Some buckets are assigned more records than the others which causes bucket overflow, this condition is called as Bucket skew. Skew occurs if multiple records have the same search key or if the given hash function is non uniform.

All the overflow buckets are chained together in a linked list. Overflow handling using a linked list of buckets is called as Overflow chaining.

Hash indices are only secondary index structures. A hash index is never needed as a clustering index structure.

Hashing can be used for 2 different purposes, hash file organization and hash index organization. In a Hash file organization, we obtain the address of the disk block containing a desired record directly by computing a function on the search key value of the record.

The term bucket is used to denote a unit of storage that can store one or more records. A bucket is typically a disk block but it can also be larger than a disk block.

A hash index organizes the search keys, with their associated pointers, into a hash file structure. We can construct a hash index by applying a hash function on a search key and store the key and its associated pointers in the bucket.