How does a text index work in a database?

A text index in a database works by mapping words or phrases to their locations in the database, speeding up search queries.

In more detail, a text index is a data structure that improves the speed of data retrieval operations on a database. It is similar to the index at the end of a book, which provides a quick way to locate information without having to read every page. In the context of a database, an index allows the database management system (DBMS) to find and retrieve specific rows much faster than it could do without an index.

The process of creating a text index involves scanning the text and building a list of words, often referred to as tokens, along with their corresponding locations in the text. This process is known as tokenisation. The tokens are then stored in a data structure, such as a B-tree or a hash table, which allows for efficient searching.

When a search query is made, the DBMS uses the index to find the locations of the words or phrases in the query, rather than scanning the entire database. This can significantly speed up search operations, especially in large databases. However, it's worth noting that while indexes can speed up data retrieval, they can also slow down data insertion, deletion, and updating because the index must be updated each time these operations are performed.

There are different types of text indexes, including full-text indexes and inverted indexes. A full-text index includes every word in the text and its location, while an inverted index lists every word and the documents or rows in which it appears. Inverted indexes are particularly useful for search engines and information retrieval systems, as they allow for fast, efficient searching of large amounts of text.

In summary, a text index in a database works by mapping words or phrases to their locations in the database, providing a quick and efficient way to perform search queries.