---
title: Match
noindex: true
canonical: https://docs.paradedb.com/documentation/advanced/full-text/match
---

Match queries are the go-to query type for text search in ParadeDB. There are two types of match queries:
[match disjunction](#match-disjunction) and [match conjunction](#match-conjunction).

## Match Disjunction

Match disjunction uses the `|||` operator and means "find all documents that contain one or more of the terms tokenized from this text input."

To understand what this looks like in practice, let's consider the following query:

```sql
SELECT description, rating, category
FROM mock_items
WHERE description ||| 'running shoes';
```

This query returns:

```csv
     description     | rating | category
---------------------+--------+----------
 Sleek running shoes |      5 | Footwear
 White jogging shoes |      3 | Footwear
 Generic shoes       |      4 | Footwear
(3 rows)
```

### How It Works

Let's look at what the `|||` operator does:

1. Retrieves the tokenizer configuration of the `description` column. In this example,
   let's assume `description` uses the [simple](/v2/tokenizers/available_tokenizers/simple) tokenizer.
2. Tokenizes the query string with the same tokenizer. This means `running shoes` becomes two tokens: `running` and `shoes`.
3. Finds all rows where `description` contains **any one** of the tokens, `running` or `shoes`.

This is why all results have either `running` or `shoes` tokens in `description`.

### Examples

Let's consider a few more hypothetical documents to see whether they would be returned by match disjunction.
These examples assume that the index uses the default tokenizer and token filters, and that the query is
`running shoes`.

| Original Text       | Tokens                    | Match | Reason                                  | Related                                                    |
| ------------------- | ------------------------- | ----- | --------------------------------------- | ---------------------------------------------------------- |
| Sleek running shoes | `sleek` `running` `shoes` | ✅    | Contains both `running` and `shoes`.    |
| Running shoes sleek | `sleek` `running` `shoes` | ✅    | Contains both `running` and `shoes`.    | [Phrase](/v2/full-text/phrase)                             |
| SLeeK RUNNING ShOeS | `sleek` `running` `shoes` | ✅    | Contains both `running` and `shoes`.    | [Lowercasing](/v2/indexing/create_index)                   |
| Sleek run shoe      | `sleek` `run` `shoe`      | ❌    | Contains neither `running` nor `shoes`. | [Stemming](/v2/indexing/create_index)                      |
| Sleke ruining shoez | `sleke` `ruining` `shoez` | ❌    | Contains neither `running` nor `shoes`. | [Fuzzy](/v2/full-text/fuzzy)                               |
| White jogging shoes | `white` `jogging` `shoes` | ✅    | Contains `shoes`.                       | [Match conjunction](/v2/full-text/match#match-conjunction) |

## Match Conjunction

Suppose we want to find rows that contain both `running` **and** `shoes`. This is where the `&&&` match conjunction operator comes in.
`&&&` means "find all documents that contain all terms tokenized from this text input."

```sql
SELECT description, rating, category
FROM mock_items
WHERE description &&& 'running shoes';
```

This query returns:

```csv
     description     | rating | category
---------------------+--------+----------
 Sleek running shoes |      5 | Footwear
(1 row)
```

Note that `White jogging shoes` and `Generic shoes` are no longer returned because they do not have the token `running`.

### How It Works

Match conjunction works exactly like match disjunction, except for one key distinction. Instead of finding documents containing
at least one matching token from the query, it finds documents where **all tokens** from the query are a match.

### Examples

Let’s consider a few more hypothetical documents to see whether they would be returned by match conjunction.
These examples assume that the index uses the default tokenizer and token filters, and that the query is
`running shoes`.

| Original Text       | Tokens                    | Match | Reason                                       | Related                                                    |
| ------------------- | ------------------------- | ----- | -------------------------------------------- | ---------------------------------------------------------- |
| Sleek running shoes | `sleek` `running` `shoes` | ✅    | Contains both `running` and `shoes`.         |
| Running shoes sleek | `sleek` `running` `shoes` | ✅    | Contains both `running` and `shoes`.         | [Phrase](/v2/full-text/phrase)                             |
| SLeeK RUNNING ShOeS | `sleek` `running` `shoes` | ✅    | Contains both `running` and `shoes`.         | [Lowercasing](/v2/indexing)                                |
| Sleek run shoe      | `sleek` `run` `shoe`      | ❌    | Does not contain both `running` and `shoes`. | [Stemming](/v2/indexing)                                   |
| Sleke ruining shoez | `sleke` `ruining` `shoez` | ❌    | Does not contain both `running` and `shoes`. | [Fuzzy](/v2/full-text/fuzzy)                               |
| White jogging shoes | `white` `jogging` `shoes` | ❌    | Does not contain both `running` and `shoes`. | [Match conjunction](/v2/full-text/match#match-conjunction) |

<Note>
If the query string only contains one token, then `|||` and `&&&` are effectively the same:

```sql
-- These two queries produce the same results
SELECT description, rating, category
FROM mock_items
WHERE description ||| 'shoes';

SELECT description, rating, category
FROM mock_items
WHERE description &&& 'shoes';
```

</Note>

## Using a Custom Tokenizer

By default, the match query automatically tokenizes the query string with the same tokenizer used by the field it's being searched against.
This behavior can be overridden by explicitly casting the query to a different tokenizer.

```sql
SELECT description, rating, category
FROM mock_items
WHERE description ||| 'running shoes'::pdb.whitespace;
```
