In today's digital age, data is being generated at an unprecedented pace. This data, however, is meaningless if it cannot be effectively accessed, interpreted, and utilized. For applications dealing with a large amount of data, search is an indispensable feature. It allows users to sift through this data and find the information that's most relevant to them. This could range from something as simple as looking for a particular email in the inbox, to something as complex as finding a specific data point within a large dataset.
Be it an e-commerce platform, streaming services, online libraries, research databases, and social media platforms - the utility of a robust search function in these applications is beyond question. It not only enhances the user experience but also contributes significantly to the efficiency of the application.
The simplest and traditional way to implement search in SQL databases is to use standard pattern-matching operators such as LIKE, ILIKE, and POSIX regular expressions (~, ~*, !~, and !~*). These operators can match and return records that satisfy the specified conditions. Let's look at each of them briefly:
LIKE and ILIKE: These operators are used to match a pattern in a string. The LIKE operator is case-sensitive, while ILIKE is not. They both use the wildcard character % to represent any sequence of characters and _ to represent any single character.
This query will return all the books whose titles start with 'Harry'. However, the LIKE and ILIKE operators are limited in their functionality. They are not ideal for handling complex search queries involving multiple words, synonyms, or language-specific variations.
POSIX Regular Expressions: PostgreSQL also supports POSIX regular expressions using operators like ~, ~*, !~, and !~*. The ~ operator performs a case-sensitive regular expression match, while ~* performs a case-insensitive match. The !~ and !~* operators return true if the regular expression does not match. For example:
