---
title: Quickstart
---
This guide will walk you through a few queries to give you a feel for ParadeDB.
## Create Example Table
ParadeDB comes with a helpful procedure that creates a table populated with mock data to help
you get started. Once connected with `psql`, run the following commands to create and inspect
this table.
```sql
CALL paradedb.create_bm25_test_table(
schema_name => 'public',
table_name => 'mock_items'
);
SELECT description, rating, category
FROM mock_items
LIMIT 3;
```
```csv
description | rating | category
--------------------------+--------+-------------
Ergonomic metal keyboard | 4 | Electronics
Plastic Keyboard | 4 | Electronics
Sleek running shoes | 5 | Footwear
(3 rows)
```
Next, let's create a BM25 index called `search_idx` on this table. A BM25 index is a covering index, which means that multiple columns can be included in the same index.
```sql
CREATE INDEX search_idx ON mock_items
USING bm25 (id, description, category, rating, in_stock, created_at, metadata, weight_range)
WITH (key_field='id');
```
As a general rule of thumb, any columns that you want to filter, `COUNT`, `GROUP BY`, or `ORDER BY` as part of a full text query should be added to the index for faster
performance.
Note the mandatory `key_field` option. Every BM25 index needs a `key_field`,
which should be the name of a column that will function as a row's unique
identifier within the index. Additionally, the `key_field` must be the first field
in the list of columns. See [choosing a key field](/documentation/indexing/create_index#choosing-a-key-field) for more details.
## Match Query
We're now ready to execute a basic text search query. We'll look for matches where `description` matches `running shoes` where `rating` is greater than `2`.
```sql
SELECT description, rating, category
FROM mock_items
WHERE description ||| 'running shoes' AND rating > 2
ORDER BY rating
LIMIT 5;
```
``` csv
description | rating | category
---------------------+--------+----------
White jogging shoes | 3 | Footwear
Generic shoes | 4 | Footwear
Sleek running shoes | 5 | Footwear
(3 rows)
```
`|||` is ParadeDB's custom [match disjunction](/v2/full-text/match#disjunction) operator, which means "find me all documents containing
`running OR shoes`.
If we want all documents containing `running AND shoes`, we can use ParadeDB's `&&&` [match conjunction](/v2/full-text/match#conjunction) operator.
```sql
SELECT description, rating, category
FROM mock_items
WHERE description &&& 'running shoes' AND rating > 2
ORDER BY rating
LIMIT 5;
```
``` csv
description | rating | category
---------------------+--------+----------
Sleek running shoes | 5 | Footwear
(1 row)
```
## BM25 Scoring
Next, let's add BM25 scoring to the results, which allows us to sort matches by relevance. To do this, we'll use `paradedb.score`.
```sql
SELECT description, paradedb.score(id)
FROM mock_items
WHERE description ||| 'running shoes' AND rating > 2
ORDER BY score DESC
LIMIT 5;
```
``` csv
description | score
---------------------+-----------
Sleek running shoes | 6.833782
Generic shoes | 3.901802
White jogging shoes | 3.4987166
(3 rows)
```
## Highlighting
Finally, let's also [highlight](/v2/full-text/highlight) the relevant portions of the documents that were matched.
To do this, we'll use `paradedb.snippet`.
```sql
SELECT description, paradedb.snippet(description), paradedb.score(id)
FROM mock_items
WHERE description ||| 'running shoes' AND rating > 2
ORDER BY score DESC
LIMIT 5;
```
``` csv
description | snippet | score
---------------------+-----------------------------------+-----------
Sleek running shoes | Sleek running shoes | 6.833782
Generic shoes | Generic shoes | 3.901802
White jogging shoes | White jogging shoes | 3.4987166
(3 rows)
```
That's it! Next, let's [load your data](/documentation/getting-started/load) to start running real queries.