---
title: "Joins"
sidebarTitle: "Join"
description: "Combining rows from more than one table, including across namespaces."
icon: link
keywords: ["join", "inner", "left", "outer", "cross", "namespace"]
---

<Badge color="red">Enterprise</Badge> [SQL runs on a deployment.](/sql)

Joining is the other thing the query builders cannot do. A question spanning two
tables is a SQL question.

## The join types {#types}

```sql
SELECT d.title, c.name
FROM documents AS d
JOIN categories AS c ON c.id = d.category_id
```

| | What it keeps |
| --- | --- |
| `[INNER] JOIN` | rows matching on both sides |
| `LEFT [OUTER] JOIN` | every left row, nulls where the right has no match |
| `RIGHT [OUTER] JOIN` | every right row |
| `FULL [OUTER] JOIN` | every row from both |
| `CROSS JOIN` | every combination -- the product of the two |

`USING (col)` is shorthand for an equality join on a shared column name, and
avoids repeating it in the select list.

## Across namespaces {#namespaces}

Tables in different [namespaces](/namespaces) join by their dotted paths -- the
catalog is one catalog, so there is nothing to federate:

```sql
SELECT c.id, u.email
FROM prod.events.clicks AS c
JOIN prod.reference.users AS u ON u.id = c.user_id
```

## Joining a search result {#search}

[`fts()`](/sql/functions#fts) is a table function, so its result is a relation
and joins like any other:

```sql
SELECT c.name, count(*) AS hits
FROM fts('my_docs', 'puppy') AS m
JOIN categories AS c ON c.id = m.category_id
GROUP BY c.name
ORDER BY hits DESC
```

That composition is the reason full-text search is a relation rather than a
predicate -- a `WHERE` clause has nowhere to put the relevance score.

## Performance {#performance}

A join key with a [scalar index](/indexing/scalar-index) on it lets the planner
look rows up rather than scan for them. Check with
[`explain_plan`](/search/explain): an indexed key shows a `ScalarIndexQuery`,
an unindexed one shows a `LanceScan` feeding the join.

<Warning>
Avoid selecting blob or vector columns you do not need on either side of a join.
The join multiplies rows before projection is applied in some plans, so a wide
column can be materialized many more times than the result has rows.
</Warning>