In this video, we dive deep into Text Search Data Types in PostgreSQL, focusing on the powerful combination of tsvector
and tsquery
. These types form the foundation of PostgreSQL’s built-in Full-Text Search capabilities, enabling developers to perform fast and accurate text searches directly within the database—without needing external tools.
We begin by exploring the tsvector
type, which is used to store normalized searchable content, and learn how to manage lexemes, weights, and positions. Then, we examine the tsquery
type, which enables rich search logic using Boolean operators, prefix matching, phrase matching (<->
), and more.
This tutorial also includes:
-
Creating tables and inserting text data
-
Using
to_tsvector()
andto_tsquery()
for normalization -
Matching vectors with queries using the
@@
operator -
Improving performance with GIN indexes
-
Automatically updating vectors via triggers
-
Ranking results using
ts_rank
-
Highlighting search results with
ts_headline
-
Debugging with
ts_debug
Whether you're building a blog search, product catalog filter, or document search engine, PostgreSQL makes it all possible—natively. This is an essential episode in our PostgreSQL Full Playlist. Don’t forget to like, comment, and subscribe!
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