Files
supabase/apps/docs/content/guides/database/full-text-search.mdx
T
Miranda Limonczenko 7ce4ee53ae chore(docs) Retire supa-mdx-lint (#50602)
Closes
[DOCS-1289](https://linear.app/supabase/issue/DOCS-1289/get-the-linter-to-fix-what-it-flags-or-retirereplace-the-linter)

Stacked on #50600, which points contributors at the authoring skills.
Merge that one first.

## Problem

Contributors experienced friction with the linter. They felt nickle and
dimed for tiny nits and felt detracted from the work itself. PRs would
become noisy with tiny one-word suggestions.

Additionally, our homegrown linter is not very intelligent, causing
frequent overrides.

## Solution

This removes the linter entirely in favor of directing contributors to
use SKILLS instead.

The removal entails...

- **CI.** Delete the three `docs_lint` workflows: the PR check, the
external-PR comment companion, and the nightly `--fix` bot. Drop the
stale `zizmor.yml` ignore entry for the deleted workflow.
- **Tooling.** Delete `supa-mdx-lint.config.toml` and the 14 rule files.
Drop the `lint:mdx` script and the `@supabase/supa-mdx-lint` dependency
from docs, learn, and ui-library, and regenerate the lockfile.
- **Content.** Remove the 181 directives. A separate commit carries
Prettier's reformatting of the tables and blank lines those comments had
suppressed, so the deletion commit stays readable. No prose changes.
- **Style guide.** The word list states each rule directly instead of
describing what the linter flagged. Every term survives, including the
phrase groups that mirrored `Rule004ExcludeWords`.
- **Skills.** `write-the-docs`, `edit-the-docs`, and `review-the-docs`
drop `pnpm lint:mdx` from their self-review commands and check the word
list directly. `ask-the-docs`'s CI reference drops both workflows.

## Manual testing

1. Run `git grep -i supa-mdx-lint -- . ':!pnpm-lock.yaml'`. No matches.
2. Run `pnpm install --frozen-lockfile --lockfile-only`. It passes, so
the lockfile matches the three trimmed manifests.
3. Run `git diff master...HEAD --name-only --diff-filter=ACMR | grep -E
'\.(md|mdx)$' | xargs npx prettier --config prettier.config.mjs
--check`. All changed markdown passes.
4. Open the [reformatted filter
table](https://docs-git-docs-retire-mdx-linter-supabase.vercel.app/docs/guides/observability/logs#filter-events)
on the preview and compare it with
[production](https://supabase.com/docs/guides/observability/logs#filter-events).
The table renders the same.

<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->
## Summary by CodeRabbit

* **Documentation**
* Documentation guidance now uses manual prose and terminology review
with the shared word list.
* Clarified storage configuration and common Realtime channel mistakes.
* Improved table formatting, text wrapping, and selected reference
links.
  * Updated documentation authoring and review guidance.

* **Chores**
* Retired automated MDX linting from workflows and local validation
commands.
* Removed lint-suppression markers throughout documentation without
changing instructions.
  * Added targeted documentation review guidance for pull requests.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
2026-09-22 10:00:41 -07:00

1702 lines
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Plaintext

---
id: 'full-text-search'
title: 'Full Text Search'
description: 'How to use full text search in Postgres.'
subtitle: 'How to use full text search in Postgres.'
tocVideo: 'GRwIa-ce7RA'
---
Postgres has built-in functions to handle `Full Text Search` queries. This is like a "search engine" within Postgres.
## Preparation
For this guide we'll use the following example data:
<Tabs
scrollable
size="small"
type="underlined"
defaultActiveId="data"
queryGroup="example-view"
>
<TabPanel id="data" label="Data">
| id | title | author | description |
| --- | ----------------------------------- | ---------------------- | ------------------------------------------------------------------ |
| 1 | The Poky Little Puppy | Janette Sebring Lowrey | Puppy is slower than other, bigger animals. |
| 2 | The Tale of Peter Rabbit | Beatrix Potter | Rabbit eats some vegetables. |
| 3 | Tootle | Gertrude Crampton | Little toy train has big dreams. |
| 4 | Green Eggs and Ham | Dr. Seuss | Sam has changing food preferences and eats unusually colored food. |
| 5 | Harry Potter and the Goblet of Fire | J.K. Rowling | Fourth year of school starts, big drama ensues. |
</TabPanel>
<TabPanel id="sql" label="SQL">
```sql
create table books (
id serial primary key,
title text,
author text,
description text
);
insert into books
(title, author, description)
values
(
'The Poky Little Puppy',
'Janette Sebring Lowrey',
'Puppy is slower than other, bigger animals.'
),
('The Tale of Peter Rabbit', 'Beatrix Potter', 'Rabbit eats some vegetables.'),
('Tootle', 'Gertrude Crampton', 'Little toy train has big dreams.'),
(
'Green Eggs and Ham',
'Dr. Seuss',
'Sam has changing food preferences and eats unusually colored food.'
),
(
'Harry Potter and the Goblet of Fire',
'J.K. Rowling',
'Fourth year of school starts, big drama ensues.'
);
```
</TabPanel>
</Tabs>
## Usage
The functions we'll cover in this guide are:
### `to_tsvector()` [#to-tsvector]
Converts your data into searchable tokens. `to_tsvector()` stands for "to text search vector." For example:
```sql
select to_tsvector('green eggs and ham');
-- Returns 'egg':2 'green':1 'ham':4
```
Collectively these tokens are called a "document" which Postgres can use for comparisons.
### `to_tsquery()` [#to-tsquery]
Converts a query string into tokens to match. `to_tsquery()` stands for "to text search query."
This conversion step is important because we will want to "fuzzy match" on keywords.
For example if a user searches for `eggs`, and a column has the value `egg`, we probably still want to return a match.
Postgres provides several functions to create tsquery objects:
- **`to_tsquery()`** - Requires manual specification of operators (`&`, `|`, `!`)
- **`plainto_tsquery()`** - Converts plain text to an AND query: `plainto_tsquery('english', 'fat rats')` → `'fat' & 'rat'`
- **`phraseto_tsquery()`** - Creates phrase queries: `phraseto_tsquery('english', 'fat rats')` → `'fat' <-> 'rat'`
- **`websearch_to_tsquery()`** - Supports web search syntax with quotes, "or", and negation
### Match: `@@` [#match]
The `@@` symbol is the "match" symbol for Full Text Search. It returns any matches between a `to_tsvector` result and a `to_tsquery` result.
Take the following example:
<Tabs
scrollable
size="small"
type="underlined"
defaultActiveId="sql"
queryGroup="language"
>
<TabPanel id="sql" label="SQL">
```sql
select *
from books
where title = 'Harry';
```
</TabPanel>
<TabPanel id="js" label="JavaScript">
```js
const { data, error } = await supabase.from('books').select().eq('title', 'Harry')
```
</TabPanel>
<$Show if="sdk:dart">
<TabPanel id="dart" label="Dart">
```dart
final result = await client
.from('books')
.select()
.eq('title', 'Harry');
```
</TabPanel>
</$Show>
<$Show if="sdk:swift">
<TabPanel id="swift" label="Swift">
```swift
let response = try await supabase.from("books")
.select()
.eq("title", value: "Harry")
.execute()
```
</TabPanel>
</$Show>
<$Show if="sdk:kotlin">
<TabPanel id="kotlin" label="Kotlin">
```kotlin
val data = supabase.from("books").select {
filter {
eq("title", "Harry")
}
}
```
</TabPanel>
</$Show>
<$Show if="sdk:python">
<TabPanel id="python" label="Python">
```python
data = supabase.from_('books').select().eq('title', 'Harry').execute()
```
</TabPanel>
</$Show>
<$Show if="sdk:csharp">
<TabPanel id="csharp" label="C#">
```c#
var result = await supabase
.From<Book>()
.Where(x => x.Title == "Harry")
.Get();
```
</TabPanel>
</$Show>
</Tabs>
The equality symbol above (`=`) is very "strict" on what it matches. In a full text search context, we might want to find all "Harry Potter" books and so we can rewrite the
example above:
<Tabs
scrollable
size="small"
type="underlined"
defaultActiveId="sql"
queryGroup="language"
>
<TabPanel id="sql" label="SQL">
```sql
select *
from books
where to_tsvector(title) @@ to_tsquery('Harry');
```
</TabPanel>
<TabPanel id="js" label="JavaScript">
```js
const { data, error } = await supabase.from('books').select().textSearch('title', `'Harry'`)
```
</TabPanel>
<$Show if="sdk:dart">
<TabPanel id="dart" label="Dart">
```dart
final result = await client
.from('books')
.select()
.textSearch('title', "'Harry'");
```
</TabPanel>
</$Show>
<$Show if="sdk:swift">
<TabPanel id="swift" label="Swift">
```swift
let response = try await supabase.from("books")
.select()
.textSearch("title", value: "'Harry'")
```
</TabPanel>
</$Show>
<$Show if="sdk:kotlin">
<TabPanel id="kotlin" label="Kotlin">
```kotlin
val data = supabase.from("books").select {
filter {
textSearch("title", "'Harry'", TextSearchType.NONE)
}
}
```
</TabPanel>
</$Show>
<$Show if="sdk:csharp">
<TabPanel id="csharp" label="C#">
```c#
var result = await supabase
.From<Book>()
.Filter("title", Operator.FTS, new FullTextSearchConfig("'Harry'", null))
.Get();
```
</TabPanel>
</$Show>
</Tabs>
## Basic full text queries
### Search a single column
To find all `books` where the `description` contain the word `big`:
<Tabs
scrollable
size="small"
type="underlined"
defaultActiveId="sql"
queryGroup="language"
>
<TabPanel id="sql" label="SQL">
```sql
select
*
from
books
where
to_tsvector(description)
@@ to_tsquery('big');
```
</TabPanel>
<TabPanel id="js" label="JavaScript">
```js
const { data, error } = await supabase.from('books').select().textSearch('description', `'big'`)
```
</TabPanel>
<$Show if="sdk:dart">
<TabPanel id="dart" label="Dart">
```dart
final result = await client
.from('books')
.select()
.textSearch('description', "'big'");
```
</TabPanel>
</$Show>
<$Show if="sdk:swift">
<TabPanel id="swift" label="Swift">
```swift
let response = await client.from("books")
.select()
.textSearch("description", value: "'big'")
.execute()
```
</TabPanel>
</$Show>
<$Show if="sdk:kotlin">
<TabPanel id="kotlin" label="Kotlin">
```kotlin
val data = supabase.from("books").select {
filter {
textSearch("description", "'big'", TextSearchType.NONE)
}
}
```
</TabPanel>
</$Show>
<$Show if="sdk:python">
<TabPanel id="python" label="Python">
```python
data = supabase.from_('books').select().text_search('description', "'big'").execute()
```
</TabPanel>
</$Show>
<$Show if="sdk:csharp">
<TabPanel id="csharp" label="C#">
```c#
var result = await supabase
.From<Book>()
.Filter("description", Operator.FTS, new FullTextSearchConfig("'big'", null))
.Get();
```
</TabPanel>
</$Show>
<TabPanel id="data" label="Data">
| id | title | author | description |
| --- | ----------------------------------- | ----------------- | ----------------------------------------------- |
| 3 | Tootle | Gertrude Crampton | Little toy train has big dreams. |
| 5 | Harry Potter and the Goblet of Fire | J.K. Rowling | Fourth year of school starts, big drama ensues. |
</TabPanel>
</Tabs>
### Search multiple columns
Right now there is no direct way to use JavaScript or Dart to search through multiple columns but you can do it by creating [computed columns](https://postgrest.org/en/stable/api.html#computed-virtual-columns) on the database.
To find all `books` where `description` or `title` contain the word `little`:
<Tabs
scrollable
size="small"
type="underlined"
defaultActiveId="sql"
queryGroup="language"
>
<TabPanel id="sql" label="SQL">
```sql
select
*
from
books
where
to_tsvector(description || ' ' || title) -- concat columns, but be sure to include a space to separate them!
@@ to_tsquery('little');
```
</TabPanel>
<TabPanel id="js" label="JavaScript">
```sql
create function title_description(books) returns text as $$
select $1.title || ' ' || $1.description;
$$ language sql immutable;
```
```js
const { data, error } = await supabase
.from('books')
.select()
.textSearch('title_description', `little`)
```
</TabPanel>
<$Show if="sdk:dart">
<TabPanel id="dart" label="Dart">
```sql
create function title_description(books) returns text as $$
select $1.title || ' ' || $1.description;
$$ language sql immutable;
```
```dart
final result = await client
.from('books')
.select()
.textSearch('title_description', "little")
```
</TabPanel>
</$Show>
<$Show if="sdk:swift">
<TabPanel id="swift" label="Swift">
```sql
create function title_description(books) returns text as $$
select $1.title || ' ' || $1.description;
$$ language sql immutable;
```
```swift
let response = try await client
.from("books")
.select()
.textSearch("title_description", value: "little")
.execute()
```
</TabPanel>
</$Show>
<$Show if="sdk:kotlin">
<TabPanel id="kotlin" label="Kotlin">
```sql
create function title_description(books) returns text as $$
select $1.title || ' ' || $1.description;
$$ language sql immutable;
```
```kotlin
val data = supabase.from("books").select {
filter {
textSearch("title_description", "title", TextSearchType.NONE)
}
}
```
</TabPanel>
</$Show>
<$Show if="sdk:python">
<TabPanel id="python" label="Python">
```sql
create function title_description(books) returns text as $$
select $1.title || ' ' || $1.description;
$$ language sql immutable;
```
```python
data = supabase.from_('books').select().text_search('title_description', "little").execute()
```
</TabPanel>
</$Show>
<$Show if="sdk:csharp">
<TabPanel id="csharp" label="C#">
```sql
create function title_description(books) returns text as $$
select $1.title || ' ' || $1.description;
$$ language sql immutable;
```
```c#
var result = await supabase
.From<Book>()
.Filter("title_description", Operator.FTS, new FullTextSearchConfig("little", null))
.Get();
```
</TabPanel>
</$Show>
<TabPanel id="data" label="Data">
| id | title | author | description |
| --- | --------------------- | ---------------------- | ------------------------------------------- |
| 1 | The Poky Little Puppy | Janette Sebring Lowrey | Puppy is slower than other, bigger animals. |
| 3 | Tootle | Gertrude Crampton | Little toy train has big dreams. |
</TabPanel>
</Tabs>
### Match all search words
To find all `books` where `description` contains BOTH of the words `little` and `big`, we can use the `&` symbol:
<Tabs
scrollable
size="small"
type="underlined"
defaultActiveId="sql"
queryGroup="language"
>
<TabPanel id="sql" label="SQL">
```sql
select
*
from
books
where
to_tsvector(description)
@@ to_tsquery('little & big'); -- use & for AND in the search query
```
</TabPanel>
<TabPanel id="js" label="JavaScript">
```js
const { data, error } = await supabase
.from('books')
.select()
.textSearch('description', `'little' & 'big'`)
```
</TabPanel>
<$Show if="sdk:dart">
<TabPanel id="dart" label="Dart">
```dart
final result = await client
.from('books')
.select()
.textSearch('description', "'little' & 'big'");
```
</TabPanel>
</$Show>
<$Show if="sdk:swift">
<TabPanel id="swift" label="Swift">
```swift
let response = try await client
.from("books")
.select()
.textSearch("description", value: "'little' & 'big'");
.execute()
```
</TabPanel>
</$Show>
<$Show if="sdk:kotlin">
<TabPanel id="kotlin" label="Kotlin">
```kotlin
val data = supabase.from("books").select {
filter {
textSearch("description", "'title' & 'big'", TextSearchType.NONE)
}
}
```
</TabPanel>
</$Show>
<$Show if="sdk:python">
<TabPanel id="python" label="Python">
```python
data = supabase.from_('books').select().text_search('description', "'little' & 'big'").execute()
```
</TabPanel>
</$Show>
<$Show if="sdk:csharp">
<TabPanel id="csharp" label="C#">
```c#
var result = await supabase
.From<Book>()
.Filter("description", Operator.FTS, new FullTextSearchConfig("'little' & 'big'", null))
.Get();
```
</TabPanel>
</$Show>
<TabPanel id="data" label="Data">
| id | title | author | description |
| --- | ------ | ----------------- | -------------------------------- |
| 3 | Tootle | Gertrude Crampton | Little toy train has big dreams. |
</TabPanel>
</Tabs>
### Match any search words
To find all `books` where `description` contain ANY of the words `little` or `big`, use the `|` symbol:
<Tabs
scrollable
size="small"
type="underlined"
defaultActiveId="sql"
queryGroup="language"
>
<TabPanel id="sql" label="SQL">
```sql
select
*
from
books
where
to_tsvector(description)
@@ to_tsquery('little | big'); -- use | for OR in the search query
```
</TabPanel>
<TabPanel id="js" label="JavaScript">
```js
const { data, error } = await supabase
.from('books')
.select()
.textSearch('description', `'little' | 'big'`)
```
</TabPanel>
<$Show if="sdk:dart">
<TabPanel id="dart" label="Dart">
```dart
final result = await client
.from('books')
.select()
.textSearch('description', "'little' | 'big'");
```
</TabPanel>
</$Show>
<$Show if="sdk:swift">
<TabPanel id="swift" label="Swift">
```swift
let response = try await client
.from("books")
.select()
.textSearch("description", value: "'little' | 'big'")
.execute()
```
</TabPanel>
</$Show>
<$Show if="sdk:kotlin">
<TabPanel id="kotlin" label="Kotlin">
```kotlin
val data = supabase.from("books").select {
filter {
textSearch("description", "'title' | 'big'", TextSearchType.NONE)
}
}
```
</TabPanel>
</$Show>
<$Show if="sdk:python">
<TabPanel id="python" label="Python">
```python
response = client.from_('books').select().text_search('description', "'little' | 'big'").execute()
```
</TabPanel>
</$Show>
<$Show if="sdk:csharp">
<TabPanel id="csharp" label="C#">
```c#
var result = await supabase
.From<Book>()
.Filter("description", Operator.FTS, new FullTextSearchConfig("'little' | 'big'", null))
.Get();
```
</TabPanel>
</$Show>
<TabPanel id="data" label="Data">
| id | title | author | description |
| --- | --------------------- | ---------------------- | ------------------------------------------- |
| 1 | The Poky Little Puppy | Janette Sebring Lowrey | Puppy is slower than other, bigger animals. |
| 3 | Tootle | Gertrude Crampton | Little toy train has big dreams. |
</TabPanel>
</Tabs>
Notice how searching for `big` includes results with the word `bigger` (or `biggest`, etc).
## Partial search
Partial search is particularly useful when you want to find matches on substrings within your data.
### Implementing partial search
You can use the `:*` syntax with `to_tsquery()`. Here's an example that searches for any book titles beginning with "Lit":
```sql
select title from books where to_tsvector(title) @@ to_tsquery('Lit:*');
```
### Extending functionality with RPC
To make the partial search functionality accessible through the API, you can wrap the search logic in a database function.
After creating this function, you can invoke it from your application using the SDK for your platform. Here's an example:
<Tabs
scrollable
size="small"
type="underlined"
defaultActiveId="sql"
queryGroup="language"
>
<TabPanel id="sql" label="SQL">
```sql
create or replace function search_books_by_title_prefix(prefix text)
returns setof books AS $$
begin
return query
select * from books where to_tsvector('english', title) @@ to_tsquery(prefix || ':*');
end;
$$ language plpgsql;
```
</TabPanel>
<TabPanel id="js" label="JavaScript">
```js
const { data, error } = await supabase.rpc('search_books_by_title_prefix', { prefix: 'Lit' })
```
</TabPanel>
<$Show if="sdk:dart">
<TabPanel id="dart" label="Dart">
```dart
final data = await supabase.rpc('search_books_by_title_prefix', params: { 'prefix': 'Lit' });
```
</TabPanel>
</$Show>
<$Show if="sdk:swift">
<TabPanel id="swift" label="Swift">
```swift
let response = try await supabase.rpc(
"search_books_by_title_prefix",
params: ["prefix": "Lit"]
)
.execute()
```
</TabPanel>
</$Show>
<$Show if="sdk:kotlin">
<TabPanel id="kotlin" label="Kotlin">
```kotlin
val rpcParams = mapOf("prefix" to "Lit")
val result = supabase.postgrest.rpc("search_books_by_title_prefix", rpcParams)
```
</TabPanel>
</$Show>
<$Show if="sdk:python">
<TabPanel id="python" label="Python">
```python
data = client.rpc('search_books_by_title_prefix', { 'prefix': 'Lit' }).execute()
```
</TabPanel>
</$Show>
<$Show if="sdk:csharp">
<TabPanel id="csharp" label="C#">
```c#
await supabase.Rpc("search_books_by_title_prefix", new Dictionary<string, object> { { "prefix", "Lit" } });
```
</TabPanel>
</$Show>
</Tabs>
This function takes a prefix parameter and returns all books where the title contains a word starting with that prefix. The `:*` operator is used to denote a prefix match in the `to_tsquery()` function.
## Handling spaces in queries
When you want the search term to include a phrase or multiple words, you can concatenate words using a `+` as a placeholder for space:
```sql
select * from search_books_by_title_prefix('Little+Puppy');
```
## Web search syntax with `websearch_to_tsquery()` [#websearch-to-tsquery]
The `websearch_to_tsquery()` function provides an intuitive search syntax similar to popular web search engines, making it ideal for user-facing search interfaces.
### Basic usage
<Tabs
scrollable
size="small"
type="underlined"
defaultActiveId="sql"
queryGroup="language"
>
<TabPanel id="sql" label="SQL">
```sql
select *
from books
where to_tsvector(description) @@ websearch_to_tsquery('english', 'green eggs');
```
</TabPanel>
<TabPanel id="js" label="JavaScript">
```js
const { data, error } = await supabase
.from('books')
.select()
.textSearch('description', 'green eggs', { type: 'websearch' })
```
</TabPanel>
<$Show if="sdk:csharp">
<TabPanel id="csharp" label="C#">
```c#
var result = await supabase
.From<Book>()
.Filter("description", Operator.WFTS, new FullTextSearchConfig("green eggs", null))
.Get();
```
</TabPanel>
</$Show>
</Tabs>
### Quoted phrases
Use quotes to search for exact phrases:
```sql
select * from books
where to_tsvector(description || ' ' || title) @@ websearch_to_tsquery('english', '"Green Eggs"');
-- Matches documents containing "Green" immediately followed by "Eggs"
```
### OR searches
Use "or" (case-insensitive) to search for multiple terms:
```sql
select * from books
where to_tsvector(description) @@ websearch_to_tsquery('english', 'puppy or rabbit');
-- Matches documents containing either "puppy" OR "rabbit"
```
### Negation
Use a dash (-) to exclude terms:
```sql
select * from books
where to_tsvector(description) @@ websearch_to_tsquery('english', 'animal -rabbit');
-- Matches documents containing "animal" but NOT "rabbit"
```
### Complex queries
Combine multiple operators for sophisticated searches:
```sql
select * from books
where to_tsvector(description || ' ' || title) @@
websearch_to_tsquery('english', '"Harry Potter" or "Dr. Seuss" -vegetables');
-- Matches books by "Harry Potter" or "Dr. Seuss" but excludes those mentioning vegetables
```
## Creating indexes
Now that you have Full Text Search working, create an `index`. This allows Postgres to "build" the documents preemptively so that they
don't need to be created at the time we execute the query. This will make our queries much faster.
### Searchable columns
Create a new column `fts` inside the `books` table to store the searchable index of the `title` and `description` columns.
We can use a special feature of Postgres called
[Generated Columns](https://www.postgresql.org/docs/current/ddl-generated-columns.html)
to ensure that the index is updated any time the values in the `title` and `description` columns change.
<Tabs
scrollable
size="small"
type="underlined"
defaultActiveId="sql"
queryGroup="example-view"
>
<TabPanel id="sql" label="SQL">
```sql
alter table
books
add column
fts tsvector generated always as (to_tsvector('english', description || ' ' || title)) stored;
create index books_fts on books using gin (fts); -- generate the index
select id, fts
from books;
```
</TabPanel>
<TabPanel id="data" label="Data">
```
| id | fts |
| --- | --------------------------------------------------------------------------------------------------------------- |
| 1 | 'anim':7 'bigger':6 'littl':10 'poki':9 'puppi':1,11 'slower':3 |
| 2 | 'eat':2 'peter':8 'rabbit':1,9 'tale':6 'veget':4 |
| 3 | 'big':5 'dream':6 'littl':1 'tootl':7 'toy':2 'train':3 |
| 4 | 'chang':3 'color':9 'eat':7 'egg':12 'food':4,10 'green':11 'ham':14 'prefer':5 'sam':1 'unus':8 |
| 5 | 'big':6 'drama':7 'ensu':8 'fire':15 'fourth':1 'goblet':13 'harri':9 'potter':10 'school':4 'start':5 'year':2 |
```
</TabPanel>
</Tabs>
### Search using the new column
Now that we've created and populated our index, we can search it using the same techniques as before:
<Tabs
scrollable
size="small"
type="underlined"
defaultActiveId="sql"
queryGroup="language"
>
<TabPanel id="sql" label="SQL">
```sql
select
*
from
books
where
fts @@ to_tsquery('little & big');
```
</TabPanel>
<TabPanel id="js" label="JavaScript">
```js
const { data, error } = await supabase.from('books').select().textSearch('fts', `'little' & 'big'`)
```
</TabPanel>
<$Show if="sdk:dart">
<TabPanel id="dart" label="Dart">
```dart
final result = await client
.from('books')
.select()
.textSearch('fts', "'little' & 'big'");
```
</TabPanel>
</$Show>
<$Show if="sdk:swift">
<TabPanel id="swift" label="Swift">
```swift
let response = try await client
.from("books")
.select()
.textSearch("fts", value: "'little' & 'big'")
.execute()
```
</TabPanel>
</$Show>
<$Show if="sdk:kotlin">
<TabPanel id="kotlin" label="Kotlin">
```kotlin
val data = supabase.from("books").select {
filter {
textSearch("fts", "'title' & 'big'", TextSearchType.NONE)
}
}
```
</TabPanel>
</$Show>
<$Show if="sdk:python">
<TabPanel id="python" label="Python">
```python
data = client.from_('books').select().text_search('fts', "'little' & 'big'").execute()
```
</TabPanel>
</$Show>
<$Show if="sdk:csharp">
<TabPanel id="csharp" label="C#">
```c#
var result = await supabase
.From<Book>()
.Filter("fts", Operator.FTS, new FullTextSearchConfig("'little' & 'big'", null))
.Get();
```
</TabPanel>
</$Show>
<TabPanel id="data" label="Data">
| id | title | author | description | fts |
| --- | ------ | ----------------- | -------------------------------- | ------------------------------------------------------- |
| 3 | Tootle | Gertrude Crampton | Little toy train has big dreams. | 'big':5 'dream':6 'littl':1 'tootl':7 'toy':2 'train':3 |
</TabPanel>
</Tabs>
## Query operators
Visit [Postgres: Text Search Functions and Operators](https://www.postgresql.org/docs/current/functions-textsearch.html)
to learn about additional query operators you can use to do more advanced `full text queries`, such as:
### Proximity: `<->` [#proximity]
The proximity symbol is useful for searching for terms that are a certain "distance" apart.
For example, to find the phrase `big dreams`, where the a match for "big" is followed immediately by a match for "dreams":
<Tabs
scrollable
size="small"
type="underlined"
defaultActiveId="sql"
queryGroup="language"
>
<TabPanel id="sql" label="SQL">
```sql
select
*
from
books
where
to_tsvector(description) @@ to_tsquery('big <-> dreams');
```
</TabPanel>
<TabPanel id="js" label="JavaScript">
```js
const { data, error } = await supabase
.from('books')
.select()
.textSearch('description', `'big' <-> 'dreams'`)
```
</TabPanel>
<$Show if="sdk:dart">
<TabPanel id="dart" label="Dart">
```dart
final result = await client
.from('books')
.select()
.textSearch('description', "'big' <-> 'dreams'");
```
</TabPanel>
</$Show>
<$Show if="sdk:swift">
<TabPanel id="swift" label="Swift">
```swift
let response = try await client
.from("books")
.select()
.textSearch("description", value: "'big' <-> 'dreams'")
.execute()
```
</TabPanel>
</$Show>
<$Show if="sdk:kotlin">
<TabPanel id="kotlin" label="Kotlin">
```kotlin
val data = supabase.from("books").select {
filter {
textSearch("description", "'big' <-> 'dreams'", TextSearchType.NONE)
}
}
```
</TabPanel>
</$Show>
<$Show if="sdk:python">
<TabPanel id="python" label="Python">
```python
data = client.from_('books').select().text_search('description', "'big' <-> 'dreams'").execute()
```
</TabPanel>
</$Show>
<$Show if="sdk:csharp">
<TabPanel id="csharp" label="C#">
```c#
var result = await supabase
.From<Book>()
.Filter("description", Operator.FTS, new FullTextSearchConfig("'big' <-> 'dreams'", null))
.Get();
```
</TabPanel>
</$Show>
</Tabs>
We can also use the `<->` to find words within a certain distance of each other. For example to find `year` and `school` within 2 words of each other:
<Tabs
scrollable
size="small"
type="underlined"
defaultActiveId="sql"
queryGroup="language"
>
<TabPanel id="sql" label="SQL">
```sql
select
*
from
books
where
to_tsvector(description) @@ to_tsquery('year <2> school');
```
</TabPanel>
<TabPanel id="js" label="JavaScript">
```js
const { data, error } = await supabase
.from('books')
.select()
.textSearch('description', `'year' <2> 'school'`)
```
</TabPanel>
<$Show if="sdk:dart">
<TabPanel id="dart" label="Dart">
```dart
final result = await client
.from('books')
.select()
.textSearch('description', "'year' <2> 'school'");
```
</TabPanel>
</$Show>
<$Show if="sdk:swift">
<TabPanel id="swift" label="Swift">
```swift
let response = try await supabase
.from("books")
.select()
.textSearch("description", value: "'year' <2> 'school'")
.execute()
```
</TabPanel>
</$Show>
<$Show if="sdk:kotlin">
<TabPanel id="kotlin" label="Kotlin">
```kotlin
val data = supabase.from("books").select {
filter {
textSearch("description", "'year' <2> 'school'", TextSearchType.NONE)
}
}
```
</TabPanel>
</$Show>
<$Show if="sdk:python">
<TabPanel id="python" label="Python">
```python
data = client.from_('books').select().text_search('description', "'year' <2> 'school'").execute()
```
</TabPanel>
</$Show>
<$Show if="sdk:csharp">
<TabPanel id="csharp" label="C#">
```c#
var result = await supabase
.From<Book>()
.Filter("description", Operator.FTS, new FullTextSearchConfig("'year' <2> 'school'", null))
.Get();
```
</TabPanel>
</$Show>
</Tabs>
### Negation: `!` [#negation]
The negation symbol can be used to find phrases which _don't_ contain a search term.
For example, to find records that have the word `big` but not `little`:
<Tabs
scrollable
size="small"
type="underlined"
defaultActiveId="sql"
queryGroup="language"
>
<TabPanel id="sql" label="SQL">
```sql
select
*
from
books
where
to_tsvector(description) @@ to_tsquery('big & !little');
```
</TabPanel>
<TabPanel id="js" label="JavaScript">
```js
const { data, error } = await supabase
.from('books')
.select()
.textSearch('description', `'big' & !'little'`)
```
</TabPanel>
<$Show if="sdk:dart">
<TabPanel id="dart" label="Dart">
```dart
final result = await client
.from('books')
.select()
.textSearch('description', "'big' & !'little'");
```
</TabPanel>
</$Show>
<$Show if="sdk:swift">
<TabPanel id="swift" label="Swift">
```swift
let response = try await client
.from("books")
.select()
.textSearch("description", value: "'big' & !'little'")
.execute()
```
</TabPanel>
</$Show>
<$Show if="sdk:kotlin">
<TabPanel id="kotlin" label="Kotlin">
```kotlin
val data = supabase.from("books").select {
filter {
textSearch("description", "'big' & !'little'", TextSearchType.NONE)
}
}
```
</TabPanel>
</$Show>
<$Show if="sdk:python">
<TabPanel id="python" label="Python">
```python
data = client.from_('books').select().text_search('description', "'big' & !'little'").execute()
```
</TabPanel>
</$Show>
<$Show if="sdk:csharp">
<TabPanel id="csharp" label="C#">
```c#
var result = await supabase
.From<Book>()
.Filter("description", Operator.FTS, new FullTextSearchConfig("'big' & !'little'", null))
.Get();
```
</TabPanel>
</$Show>
</Tabs>
## Ranking search results [#ranking]
Postgres provides ranking functions to sort search results by relevance, helping you present the most relevant matches first. Since ranking functions need to be computed server-side, use RPC functions and generated columns.
### Creating a search function with ranking [#search-function-ranking]
First, create a Postgres function that handles search and ranking:
```sql
create or replace function search_books(search_query text)
returns table(id int, title text, description text, rank real) as $$
begin
return query
select
books.id,
books.title,
books.description,
ts_rank(to_tsvector('english', books.description), to_tsquery(search_query)) as rank
from books
where to_tsvector('english', books.description) @@ to_tsquery(search_query)
order by rank desc;
end;
$$ language plpgsql;
```
Now you can call this function from your client:
<Tabs
scrollable
size="small"
type="underlined"
defaultActiveId="js"
queryGroup="language"
>
<TabPanel id="js" label="JavaScript">
```js
const { data, error } = await supabase.rpc('search_books', { search_query: 'big' })
```
</TabPanel>
<$Show if="sdk:dart">
<TabPanel id="dart" label="Dart">
```dart
final result = await client
.rpc('search_books', params: { 'search_query': 'big' });
```
</TabPanel>
</$Show>
<$Show if="sdk:python">
<TabPanel id="python" label="Python">
```python
data = client.rpc('search_books', { 'search_query': 'big' }).execute()
```
</TabPanel>
</$Show>
<$Show if="sdk:csharp">
<TabPanel id="csharp" label="C#">
```c#
await supabase.Rpc("search_books", new Dictionary<string, object> { { "search_query", "big" } });
```
</TabPanel>
</$Show>
<TabPanel id="sql" label="SQL">
```sql
select * from search_books('big');
```
</TabPanel>
</Tabs>
### Ranking with weighted columns [#weighted-ranking]
Postgres allows you to assign different importance levels to different parts of your documents using weight labels. This is especially useful when you want matches in certain fields (like titles) to rank higher than matches in other fields (like descriptions).
#### Understanding weight labels
Postgres uses four weight labels: **A**, **B**, **C**, and **D**, where:
- **A** = Highest importance (weight 1.0)
- **B** = High importance (weight 0.4)
- **C** = Medium importance (weight 0.2)
- **D** = Low importance (weight 0.1)
#### Creating weighted search columns
First, create a weighted tsvector column that gives titles higher priority than descriptions:
```sql
-- Add a weighted fts column
alter table books
add column fts_weighted tsvector
generated always as (
setweight(to_tsvector('english', title), 'A') ||
setweight(to_tsvector('english', description), 'B')
) stored;
-- Create index for the weighted column
create index books_fts_weighted on books using gin (fts_weighted);
```
Now create a search function that uses this weighted column:
```sql
create or replace function search_books_weighted(search_query text)
returns table(id int, title text, description text, rank real) as $$
begin
return query
select
books.id,
books.title,
books.description,
ts_rank(books.fts_weighted, to_tsquery(search_query)) as rank
from books
where books.fts_weighted @@ to_tsquery(search_query)
order by rank desc;
end;
$$ language plpgsql;
```
#### Custom weight arrays
You can also specify custom weights by providing a weight array to `ts_rank()`:
```sql
create or replace function search_books_custom_weights(search_query text)
returns table(id int, title text, description text, rank real) as $$
begin
return query
select
books.id,
books.title,
books.description,
ts_rank(
'{0.0, 0.2, 0.5, 1.0}'::real[], -- Custom weights {D, C, B, A}
books.fts_weighted,
to_tsquery(search_query)
) as rank
from books
where books.fts_weighted @@ to_tsquery(search_query)
order by rank desc;
end;
$$ language plpgsql;
```
This example uses custom weights where:
- A-labeled terms (titles) have maximum weight (1.0)
- B-labeled terms (descriptions) have medium weight (0.5)
- C-labeled terms have low weight (0.2)
- D-labeled terms are ignored (0.0)
#### Using the weighted search
<Tabs
scrollable
size="small"
type="underlined"
defaultActiveId="js"
queryGroup="language"
>
<TabPanel id="js" label="JavaScript">
```js
// Search with standard weighted ranking
const { data, error } = await supabase.rpc('search_books_weighted', { search_query: 'Harry' })
// Search with custom weights
const { data: customData, error: customError } = await supabase.rpc('search_books_custom_weights', {
search_query: 'Harry',
})
```
</TabPanel>
<$Show if="sdk:python">
<TabPanel id="python" label="Python">
```python
# Search with standard weighted ranking
data = client.rpc('search_books_weighted', { 'search_query': 'Harry' }).execute()
# Search with custom weights
custom_data = client.rpc('search_books_custom_weights', { 'search_query': 'Harry' }).execute()
```
</TabPanel>
</$Show>
<$Show if="sdk:csharp">
<TabPanel id="csharp" label="C#">
```c#
// Search with standard weighted ranking
await supabase.Rpc("search_books_weighted", new Dictionary<string, object> { { "search_query", "Harry" } });
// Search with custom weights
await supabase.Rpc("search_books_custom_weights", new Dictionary<string, object> { { "search_query", "Harry" } });
```
</TabPanel>
</$Show>
<TabPanel id="sql" label="SQL">
```sql
-- Standard weighted search
select * from search_books_weighted('Harry');
-- Custom weighted search
select * from search_books_custom_weights('Harry');
```
</TabPanel>
</Tabs>
#### Practical example with results
Say you search for "Harry". With weighted columns:
1. **"Harry Potter and the Goblet of Fire"** (title match) gets weight A = 1.0
2. **Books mentioning "Harry" in description** get weight B = 0.4
This ensures that books with "Harry" in the title ranks significantly higher than books that only mention "Harry" in the description, providing more relevant search results for users.
### Using ranking with indexes [#ranking-with-indexes]
When using the `fts` column you created earlier, ranking becomes more efficient. Create a function that uses the indexed column:
```sql
create or replace function search_books_fts(search_query text)
returns table(id int, title text, description text, rank real) as $$
begin
return query
select
books.id,
books.title,
books.description,
ts_rank(books.fts, to_tsquery(search_query)) as rank
from books
where books.fts @@ to_tsquery(search_query)
order by rank desc;
end;
$$ language plpgsql;
```
<Tabs
scrollable
size="small"
type="underlined"
defaultActiveId="js"
queryGroup="language"
>
<TabPanel id="js" label="JavaScript">
```js
const { data, error } = await supabase.rpc('search_books_fts', { search_query: 'little & big' })
```
</TabPanel>
<$Show if="sdk:dart">
<TabPanel id="dart" label="Dart">
```dart
final result = await client
.rpc('search_books_fts', params: { 'search_query': 'little & big' });
```
</TabPanel>
</$Show>
<$Show if="sdk:python">
<TabPanel id="python" label="Python">
```python
data = client.rpc('search_books_fts', { 'search_query': 'little & big' }).execute()
```
</TabPanel>
</$Show>
<$Show if="sdk:csharp">
<TabPanel id="csharp" label="C#">
```c#
await supabase.Rpc("search_books_fts", new Dictionary<string, object> { { "search_query", "little & big" } });
```
</TabPanel>
</$Show>
<TabPanel id="sql" label="SQL">
```sql
select * from search_books_fts('little & big');
```
</TabPanel>
</Tabs>
### Using web search syntax with ranking [#websearch-ranking]
You can also create a function that combines `websearch_to_tsquery()` with ranking for user-friendly search:
```sql
create or replace function websearch_books(search_text text)
returns table(id int, title text, description text, rank real) as $$
begin
return query
select
books.id,
books.title,
books.description,
ts_rank(books.fts, websearch_to_tsquery('english', search_text)) as rank
from books
where books.fts @@ websearch_to_tsquery('english', search_text)
order by rank desc;
end;
$$ language plpgsql;
```
<Tabs
scrollable
size="small"
type="underlined"
defaultActiveId="js"
queryGroup="language"
>
<TabPanel id="js" label="JavaScript">
```js
// Support natural search syntax
const { data, error } = await supabase.rpc('websearch_books', {
search_text: '"little puppy" or train -vegetables',
})
```
</TabPanel>
<$Show if="sdk:csharp">
<TabPanel id="csharp" label="C#">
```c#
// Support natural search syntax
await supabase.Rpc("websearch_books", new Dictionary<string, object> { { "search_text", "\"little puppy\" or train -vegetables" } });
```
</TabPanel>
</$Show>
<TabPanel id="sql" label="SQL">
```sql
select * from websearch_books('"little puppy" or train -vegetables');
```
</TabPanel>
</Tabs>
## Resources
- [Postgres: Text Search Functions and Operators](https://www.postgresql.org/docs/12/functions-textsearch.html)