| undefined
return Total users: {data.length}
}
```
#### Error Handling
Combine with Error Boundaries to handle loading errors:
```tsx
import { ErrorBoundary } from 'react-error-boundary'
function App() {
return (
Failed to load users}>
Loading users...}>
)
}
```
#### Reactive Updates
After the initial load, data updates stream in without re-suspending:
```tsx
function UserList() {
const { data } = useLiveSuspenseQuery((q) =>
q.from({ user: usersCollection })
)
// Suspends once during initial load
// After that, data updates automatically when users change
// UI never re-suspends for live updates
return (
{data.map(user => (
- {user.name}
))}
)
}
```
#### Re-suspending on Dependency Changes
When dependencies change, the hook re-suspends to load new data:
```tsx
function FilteredUsers({ minAge }: { minAge: number }) {
const { data } = useLiveSuspenseQuery(
(q) =>
q
.from({ user: usersCollection })
.where(({ user }) => gt(user.age, minAge)),
[minAge] // Re-suspend when minAge changes
)
return (
{data.map(user => (
- {user.name} - {user.age}
))}
)
}
```
#### When to Use Which Hook
- **Use `useLiveSuspenseQuery`** when:
- You want to use React Suspense for loading states
- You prefer handling loading/error states with `` and `` components
- You want guaranteed non-undefined data types
- The query always needs to run (not conditional)
- **Use `useLiveQuery`** when:
- You need conditional/disabled queries
- You prefer handling loading/error states within your component
- You want to show loading states inline without Suspense
- You need access to `status` and `isLoading` flags
- **You're using a router with loaders** (React Router, TanStack Router, etc.) - preload in the loader and use `useLiveQuery` in the component
```tsx
// useLiveQuery - handle states in component
function UserList() {
const { data, status, isLoading } = useLiveQuery((q) =>
q.from({ user: usersCollection })
)
if (isLoading) return Loading...
if (status === 'error') return Error loading users
return {data?.map(user => - {user.name}
)}
}
// useLiveSuspenseQuery - handle states with Suspense/ErrorBoundary
function UserList() {
const { data } = useLiveSuspenseQuery((q) =>
q.from({ user: usersCollection })
)
return {data.map(user => - {user.name}
)}
}
// useLiveQuery with router loader - recommended pattern
// In your route configuration:
const route = {
path: '/users',
loader: async () => {
// Preload the collection in the loader
await usersCollection.preload()
return null
},
component: UserList,
}
// In your component:
function UserList() {
// Collection is already loaded, so data is immediately available
const { data } = useLiveQuery((q) =>
q.from({ user: usersCollection })
)
return {data?.map(user => - {user.name}
)}
}
```
### Conditional Queries
In React, you can conditionally disable a query by returning `undefined` or `null` from the `useLiveQuery` callback. When disabled, the hook returns a special state indicating the query is not active.
```tsx
import { useLiveQuery } from '@tanstack/react-db'
function TodoList({ userId }: { userId?: string }) {
const { data, isEnabled, status } = useLiveQuery((q) => {
// Disable the query when userId is not available
if (!userId) return undefined
return q
.from({ todos: todosCollection })
.where(({ todos }) => eq(todos.userId, userId))
}, [userId])
if (!isEnabled) {
return Please select a user
}
return (
{data?.map(todo => (
- {todo.text}
))}
)
}
```
When the query is disabled (callback returns `undefined` or `null`):
- `status` is `'disabled'`
- `data`, `state`, and `collection` are `undefined`
- `isEnabled` is `false`
- `isLoading`, `isReady`, `isIdle`, and `isError` are all `false`
This pattern is useful for "wait until inputs exist" flows without needing to conditionally render the hook itself or manage an external enabled flag.
### Alternative Callback Return Types
The `useLiveQuery` callback can return different types depending on your use case:
#### Returning a Query Builder (Standard)
The most common pattern is to return a query builder:
```tsx
const { data } = useLiveQuery((q) =>
q.from({ todos: todosCollection })
.where(({ todos }) => eq(todos.completed, false))
)
```
#### Returning a Pre-created Collection
You can return an existing collection directly:
```tsx
const activeUsersCollection = createLiveQueryCollection((q) =>
q.from({ users: usersCollection })
.where(({ users }) => eq(users.active, true))
)
function UserList({ usePrebuilt }: { usePrebuilt: boolean }) {
const { data } = useLiveQuery((q) => {
// Toggle between pre-created collection and ad-hoc query
if (usePrebuilt) return activeUsersCollection
return q.from({ users: usersCollection })
}, [usePrebuilt])
return {data?.map(user => - {user.name}
)}
}
```
#### Returning a LiveQueryCollectionConfig
You can return a configuration object to specify additional options like a custom ID:
```tsx
const { data } = useLiveQuery((q) => {
return {
query: q.from({ items: itemsCollection })
.select(({ items }) => ({ id: items.id })),
id: 'items-view', // Custom ID for debugging
gcTime: 10000 // Custom garbage collection time
}
})
```
This is particularly useful when you need to:
- Attach a stable ID for debugging or logging
- Configure collection-specific options like `gcTime` or `getKey`
- Conditionally switch between different collection configurations
## From Clause
The foundation of every query is the `from` method, which specifies the source collection or subquery. You can alias the source using object syntax.
### Method Signature
```ts
from({
[alias]: Collection | Query,
}): Query
```
**Parameters:**
- `[alias]` - A Collection or Query instance. Note that only a single aliased collection or subquery is allowed in the `from` clause.
### Basic Usage
Start with a basic query that selects all records from a collection:
```ts
const allUsers = createCollection(liveQueryCollectionOptions({
query: (q) => q.from({ user: usersCollection })
}))
```
The result contains all users with their full schema. You can iterate over the results or access them by key:
```ts
// Get all users as an array
const users = allUsers.toArray
// Get a specific user by ID
const user = allUsers.get(1)
// Check if a user exists
const hasUser = allUsers.has(1)
```
Use aliases to make your queries more readable, especially when working with multiple collections:
```ts
const users = createCollection(liveQueryCollectionOptions({
query: (q) => q.from({ u: usersCollection })
}))
// Access fields using the alias
const userNames = createCollection(liveQueryCollectionOptions({
query: (q) =>
q
.from({ u: usersCollection })
.select(({ u }) => ({
name: u.name,
email: u.email,
}))
}))
```
## Where Clauses
Use `where` clauses to filter your data based on conditions. You can chain multiple `where` calls - they are combined with `and` logic.
The `where` method takes a callback function that receives an object containing your table aliases and returns a boolean expression. You build these expressions using comparison functions like `eq()`, `gt()`, and logical operators like `and()` and `or()`. This declarative approach allows the query system to optimize your filters efficiently. These are described in more detail in the [Expression Functions Reference](#expression-functions-reference) section. This is very similar to how you construct queries using Kysely or Drizzle.
It's important to note that the `where` method is not a function that is executed on each row or the results, its a way to describe the query that will be executed. This declarative approach works well for almost all use cases, but if you need to use a more complex condition, there is the functional variant as `fn.where` which is described in the [Functional Variants](#functional-variants) section.
### Method Signature
```ts
where(
condition: (row: TRow) => Expression
): Query
```
**Parameters:**
- `condition` - A callback function that receives the row object with table aliases and returns a boolean expression
### Basic Filtering
Filter users by a simple condition:
```ts
import { eq } from '@tanstack/db'
const activeUsers = createCollection(liveQueryCollectionOptions({
query: (q) =>
q
.from({ user: usersCollection })
.where(({ user }) => eq(user.active, true))
}))
```
### Multiple Conditions
Chain multiple `where` calls for AND logic:
```ts
import { eq, gt } from '@tanstack/db'
const adultActiveUsers = createCollection(liveQueryCollectionOptions({
query: (q) =>
q
.from({ user: usersCollection })
.where(({ user }) => eq(user.active, true))
.where(({ user }) => gt(user.age, 18))
}))
```
### Complex Conditions
Use logical operators to build complex conditions:
```ts
import { eq, gt, or, and } from '@tanstack/db'
const specialUsers = createLiveQueryCollection((q) =>
q
.from({ user: usersCollection })
.where(({ user }) =>
and(
eq(user.active, true),
or(
gt(user.age, 25),
eq(user.role, 'admin')
)
)
)
)
```
### Available Operators
The query system provides several comparison operators:
```ts
import { eq, gt, gte, lt, lte, like, ilike, inArray, and, or, not } from '@tanstack/db'
// Equality
eq(user.id, 1)
// Comparisons
gt(user.age, 18) // greater than
gte(user.age, 18) // greater than or equal
lt(user.age, 65) // less than
lte(user.age, 65) // less than or equal
// String matching
like(user.name, 'John%') // case-sensitive pattern matching
ilike(user.name, 'john%') // case-insensitive pattern matching
// Array membership
inArray(user.id, [1, 2, 3])
// Logical operators
and(condition1, condition2)
or(condition1, condition2)
not(condition)
```
For a complete reference of all available functions, see the [Expression Functions Reference](#expression-functions-reference) section.
## Select
Use `select` to specify which fields to include in your results and transform your data. Without `select`, you get the full schema.
Similar to the `where` clause, the `select` method takes a callback function that receives an object containing your table aliases and returns an object with the fields you want to include in your results. These can be combined with functions from the [Expression Functions Reference](#expression-functions-reference) section to create computed fields. You can also use the spread operator to include all fields from a table.
### Method Signature
```ts
select(
projection: (row: TRow) => Record
): Query
```
**Parameters:**
- `projection` - A callback function that receives the row object with table aliases and returns the selected fields object
### Basic Selects
Select specific fields from your data:
````ts
const userNames = createLiveQueryCollection((q) =>
q
.from({ user: usersCollection })
.select(({ user }) => ({
id: user.id,
name: user.name,
email: user.email,
}))
)
/*
Result type: { id: number, name: string, email: string }
```ts
for (const row of userNames) {
console.log(row.name)
}
```
*/
````
### Field Renaming
Rename fields in your results:
```ts
const userProfiles = createLiveQueryCollection((q) =>
q
.from({ user: usersCollection })
.select(({ user }) => ({
userId: user.id,
fullName: user.name,
contactEmail: user.email,
}))
)
```
### Computed Fields
Create computed fields using expressions:
```ts
import { gt, length } from '@tanstack/db'
const userStats = createLiveQueryCollection((q) =>
q
.from({ user: usersCollection })
.select(({ user }) => ({
id: user.id,
name: user.name,
isAdult: gt(user.age, 18),
nameLength: length(user.name),
}))
)
```
### Using Functions and Including All Fields
Transform your data using built-in functions:
````ts
import { concat, upper, gt } from '@tanstack/db'
const formattedUsers = createCollection(liveQueryCollectionOptions({
query: (q) =>
q
.from({ user: usersCollection })
.select(({ user }) => ({
...user, // Include all user fields
displayName: upper(concat(user.firstName, ' ', user.lastName)),
isAdult: gt(user.age, 18),
}))
}))
/*
Result type:
{
id: number,
name: string,
email: string,
displayName: string,
isAdult: boolean,
}
*/
````
For a complete list of available functions, see the [Expression Functions Reference](#expression-functions-reference) section.
## Joins
Use `join` to combine data from multiple collections. Joins default to `left` join type and only support equality conditions.
Joins in TanStack DB are a way to combine data from multiple collections, and are conceptually very similar to SQL joins. When two collections are joined, the result is a new collection that contains the combined data as single rows. The new collection is a live query collection, and will automatically update when the underlying data changes.
A `join` without a `select` will return row objects that are namespaced with the aliases of the joined collections.
The result type of a join will take into account the join type, with the optionality of the joined fields being determined by the join type.
> [!TIP]
> If you need hierarchical results instead of flat joined rows (e.g., each project with its nested issues), see [Includes](#includes) below.
### Method Signature
```ts
join(
{ [alias]: Collection | Query },
condition: (row: TRow) => Expression, // Must be an `eq` condition
joinType?: 'left' | 'right' | 'inner' | 'full'
): Query
```
**Parameters:**
- `aliases` - An object where keys are alias names and values are collections or subqueries to join
- `condition` - A callback function that receives the combined row object and returns an equality condition
- `joinType` - Optional join type: `'left'` (default), `'right'`, `'inner'`, or `'full'`
### Basic Joins
Join users with their posts:
````ts
const userPosts = createLiveQueryCollection((q) =>
q
.from({ user: usersCollection })
.join({ post: postsCollection }, ({ user, post }) =>
eq(user.id, post.userId)
)
)
/*
Result type:
{
user: User,
post?: Post, // post is optional because it is a left join
}
```ts
for (const row of userPosts) {
console.log(row.user.name, row.post?.title)
}
```
*/
````
### Join Types
Specify the join type as the third parameter:
```ts
const activeUserPosts = createLiveQueryCollection((q) =>
q
.from({ user: usersCollection })
.join(
{ post: postsCollection },
({ user, post }) => eq(user.id, post.userId),
'inner', // `inner`, `left`, `right` or `full`
)
)
```
Or using the aliases `leftJoin`, `rightJoin`, `innerJoin` and `fullJoin` methods:
### Left Join
```ts
// Left join - all users, even without posts
const allUsers = createLiveQueryCollection((q) =>
q
.from({ user: usersCollection })
.leftJoin(
{ post: postsCollection },
({ user, post }) => eq(user.id, post.userId),
)
)
/*
Result type:
{
user: User,
post?: Post, // post is optional because it is a left join
}
*/
```
### Right Join
```ts
// Right join - all posts, even without users
const allPosts = createLiveQueryCollection((q) =>
q
.from({ user: usersCollection })
.rightJoin(
{ post: postsCollection },
({ user, post }) => eq(user.id, post.userId),
)
)
/*
Result type:
{
user?: User, // user is optional because it is a right join
post: Post,
}
*/
```
### Inner Join
```ts
// Inner join - only matching records
const activeUserPosts = createLiveQueryCollection((q) =>
q
.from({ user: usersCollection })
.innerJoin(
{ post: postsCollection },
({ user, post }) => eq(user.id, post.userId),
)
)
/*
Result type:
{
user: User,
post: Post,
}
*/
```
### Full Join
```ts
// Full join - all users and all posts
const allUsersAndPosts = createLiveQueryCollection((q) =>
q
.from({ user: usersCollection })
.fullJoin(
{ post: postsCollection },
({ user, post }) => eq(user.id, post.userId),
)
)
/*
Result type:
{
user?: User, // user is optional because it is a full join
post?: Post, // post is optional because it is a full join
}
*/
```
### Multiple Joins
Chain multiple joins in a single query:
```ts
const userPostComments = createLiveQueryCollection((q) =>
q
.from({ user: usersCollection })
.join({ post: postsCollection }, ({ user, post }) =>
eq(user.id, post.userId)
)
.join({ comment: commentsCollection }, ({ post, comment }) =>
eq(post.id, comment.postId)
)
.select(({ user, post, comment }) => ({
userName: user.name,
postTitle: post.title,
commentText: comment.text,
}))
)
```
## Subqueries
Subqueries allow you to use the result of one query as input to another, they are embedded within the query itself and are compile to a single query pipeline. They are very similar to SQL subqueries that are executed as part of a single operation.
Note that subqueries are not the same as using a live query result in a `from` or `join` clause in a new query. When you do that the intermediate result is fully computed and accessible to you, subqueries are internal to their parent query and not materialised to a collection themselves and so are more efficient.
See the [Caching Intermediate Results](#caching-intermediate-results) section for more details on using live query results in a `from` or `join` clause in a new query.
### Subqueries in `from` Clauses
Use a subquery as the main source:
```ts
const activeUserPosts = createCollection(liveQueryCollectionOptions({
query: (q) => {
// Build the subquery first
const activeUsers = q
.from({ user: usersCollection })
.where(({ user }) => eq(user.active, true))
// Use the subquery in the main query
return q
.from({ activeUser: activeUsers })
.join({ post: postsCollection }, ({ activeUser, post }) =>
eq(activeUser.id, post.userId)
)
}
}))
```
### Subqueries in `join` Clauses
Join with a subquery result:
```ts
const userRecentPosts = createCollection(liveQueryCollectionOptions({
query: (q) => {
// Build the subquery first
const recentPosts = q
.from({ post: postsCollection })
.where(({ post }) => gt(post.createdAt, '2024-01-01'))
.orderBy(({ post }) => post.createdAt, 'desc')
.limit(1)
// Use the subquery in the main query
return q
.from({ user: usersCollection })
.join({ recentPost: recentPosts }, ({ user, recentPost }) =>
eq(user.id, recentPost.userId)
)
}
}))
```
### Subquery deduplication
When the same subquery is used multiple times within a query, it's automatically deduplicated and executed only once:
```ts
const complexQuery = createCollection(liveQueryCollectionOptions({
query: (q) => {
// Build the subquery once
const activeUsers = q
.from({ user: usersCollection })
.where(({ user }) => eq(user.active, true))
// Use the same subquery multiple times
return q
.from({ activeUser: activeUsers })
.join({ post: postsCollection }, ({ activeUser, post }) =>
eq(activeUser.id, post.userId)
)
.join({ comment: commentsCollection }, ({ activeUser, comment }) =>
eq(activeUser.id, comment.userId)
)
}
}))
```
In this example, the `activeUsers` subquery is used twice but executed only once, improving performance.
### Complex Nested Subqueries
Build complex queries with multiple levels of nesting:
```ts
import { count } from '@tanstack/db'
const topUsers = createCollection(liveQueryCollectionOptions({
query: (q) => {
// Build the post count subquery
const postCounts = q
.from({ post: postsCollection })
.groupBy(({ post }) => post.userId)
.select(({ post }) => ({
userId: post.userId,
count: count(post.id),
}))
// Build the user stats subquery
const userStats = q
.from({ user: usersCollection })
.join({ postCount: postCounts }, ({ user, postCount }) =>
eq(user.id, postCount.userId)
)
.select(({ user, postCount }) => ({
id: user.id,
name: user.name,
postCount: postCount.count,
}))
.orderBy(({ userStats }) => userStats.postCount, 'desc')
.limit(10)
// Use the user stats subquery in the main query
return q.from({ userStats })
}
}))
```
## Includes
Includes let you nest subqueries inside `.select()` to produce hierarchical results. Instead of joins that flatten 1:N relationships into repeated rows, each parent row gets a nested collection of its related items.
```ts
import { createLiveQueryCollection, eq } from '@tanstack/db'
const projectsWithIssues = createLiveQueryCollection((q) =>
q.from({ p: projectsCollection }).select(({ p }) => ({
id: p.id,
name: p.name,
issues: q
.from({ i: issuesCollection })
.where(({ i }) => eq(i.projectId, p.id))
.select(({ i }) => ({
id: i.id,
title: i.title,
})),
})),
)
```
Each project's `issues` field is a live `Collection` that updates incrementally as the underlying data changes.
### Correlation Condition
The child query's `.where()` must contain an `eq()` that links a child field to a parent field — this is the **correlation condition**. It tells the system how children relate to parents.
```ts
// The correlation condition: links issues to their parent project
.where(({ i }) => eq(i.projectId, p.id))
```
The correlation condition can appear as a standalone `.where()`, or inside an `and()`:
```ts
// Also valid — correlation is extracted from inside and()
.where(({ i }) => and(eq(i.projectId, p.id), eq(i.status, 'open')))
```
The correlation field does not need to be included in the parent's `.select()`.
### Additional Filters
Child queries support additional `.where()` clauses beyond the correlation condition, including filters that reference parent fields:
```ts
q.from({ p: projectsCollection }).select(({ p }) => ({
id: p.id,
name: p.name,
issues: q
.from({ i: issuesCollection })
.where(({ i }) => eq(i.projectId, p.id)) // correlation
.where(({ i }) => eq(i.createdBy, p.createdBy)) // parent-referencing filter
.where(({ i }) => eq(i.status, 'open')) // pure child filter
.select(({ i }) => ({
id: i.id,
title: i.title,
})),
}))
```
Parent-referencing filters are fully reactive — if a parent's field changes, the child results update automatically.
### Ordering and Limiting
Child queries support `.orderBy()` and `.limit()`, applied per parent:
```ts
q.from({ p: projectsCollection }).select(({ p }) => ({
id: p.id,
name: p.name,
issues: q
.from({ i: issuesCollection })
.where(({ i }) => eq(i.projectId, p.id))
.orderBy(({ i }) => i.createdAt, 'desc')
.limit(5)
.select(({ i }) => ({
id: i.id,
title: i.title,
})),
}))
```
Each project gets its own top-5 issues, not 5 issues shared across all projects.
### toArray
By default, each child result is a live `Collection`. If you want a plain array instead, wrap the child query with `toArray()`:
```ts
import { createLiveQueryCollection, eq, toArray } from '@tanstack/db'
const projectsWithIssues = createLiveQueryCollection((q) =>
q.from({ p: projectsCollection }).select(({ p }) => ({
id: p.id,
name: p.name,
issues: toArray(
q
.from({ i: issuesCollection })
.where(({ i }) => eq(i.projectId, p.id))
.select(({ i }) => ({
id: i.id,
title: i.title,
})),
),
})),
)
```
With `toArray()`, the project row is re-emitted whenever its issues change. Without it, the child `Collection` updates independently.
### Aggregates
You can use aggregate functions in child queries. Aggregates are computed per parent:
```ts
import { createLiveQueryCollection, eq, count } from '@tanstack/db'
const projectsWithCounts = createLiveQueryCollection((q) =>
q.from({ p: projectsCollection }).select(({ p }) => ({
id: p.id,
name: p.name,
issueCount: q
.from({ i: issuesCollection })
.where(({ i }) => eq(i.projectId, p.id))
.select(({ i }) => ({ total: count(i.id) })),
})),
)
```
Each project gets its own count. The count updates reactively as issues are added or removed.
### Nested Includes
Includes nest arbitrarily. For example, projects can include issues, which include comments:
```ts
const tree = createLiveQueryCollection((q) =>
q.from({ p: projectsCollection }).select(({ p }) => ({
id: p.id,
name: p.name,
issues: q
.from({ i: issuesCollection })
.where(({ i }) => eq(i.projectId, p.id))
.select(({ i }) => ({
id: i.id,
title: i.title,
comments: q
.from({ c: commentsCollection })
.where(({ c }) => eq(c.issueId, i.id))
.select(({ c }) => ({
id: c.id,
body: c.body,
})),
})),
})),
)
```
Each level updates independently and incrementally — adding a comment to an issue does not re-process other issues or projects.
### Using Includes with React
When using includes with React, each child `Collection` needs its own `useLiveQuery` subscription to receive reactive updates. Pass the child collection to a subcomponent that calls `useLiveQuery(childCollection)`:
```tsx
import { useLiveQuery } from '@tanstack/react-db'
import { eq } from '@tanstack/db'
function ProjectList() {
const { data: projects } = useLiveQuery((q) =>
q.from({ p: projectsCollection }).select(({ p }) => ({
id: p.id,
name: p.name,
issues: q
.from({ i: issuesCollection })
.where(({ i }) => eq(i.projectId, p.id))
.select(({ i }) => ({
id: i.id,
title: i.title,
})),
})),
)
return (
{projects.map((project) => (
-
{project.name}
{/* Pass the child collection to a subcomponent */}
))}
)
}
function IssueList({ issuesCollection }) {
// Subscribe to the child collection for reactive updates
const { data: issues } = useLiveQuery(issuesCollection)
return (
{issues.map((issue) => (
- {issue.title}
))}
)
}
```
Each `IssueList` component independently subscribes to its project's issues. When an issue is added or removed, only the affected `IssueList` re-renders — the parent `ProjectList` does not.
> [!NOTE]
> You must pass the child collection to a subcomponent and subscribe with `useLiveQuery`. Reading `project.issues` directly in the parent without subscribing will give you the collection object, but the component won't re-render when the child data changes.
## groupBy and Aggregations
Use `groupBy` to group your data and apply aggregate functions. When you use aggregates in `select` without `groupBy`, the entire result set is treated as a single group.
### Method Signature
```ts
groupBy(
grouper: (row: TRow) => Expression | Expression[]
): Query
```
**Parameters:**
- `grouper` - A callback function that receives the row object and returns the grouping key(s). Can return a single value or an array for multi-column grouping
### Basic Grouping
Group users by their department and count them:
```ts
import { count, avg } from '@tanstack/db'
const departmentStats = createCollection(liveQueryCollectionOptions({
query: (q) =>
q
.from({ user: usersCollection })
.groupBy(({ user }) => user.departmentId)
.select(({ user }) => ({
departmentId: user.departmentId,
userCount: count(user.id),
avgAge: avg(user.age),
}))
}))
```
> [!NOTE]
> In `groupBy` queries, the properties in your `select` clause must either be:
> - An aggregate function (like `count`, `sum`, `avg`)
> - A property that was used in the `groupBy` clause
>
> You cannot select properties that are neither aggregated nor grouped.
> [!WARNING]
> `fn.select()` cannot be used with `groupBy()`. The `groupBy` operator needs to statically analyze the `select` clause to discover which aggregate functions (`count`, `sum`, `max`, etc.) to compute for each group. Since `fn.select()` is an opaque JavaScript function, the compiler cannot inspect it. Use the standard `.select()` API when combining with `groupBy()`.
### Multiple Column Grouping
Group by multiple columns by returning an array from the callback:
```ts
const userStats = createCollection(liveQueryCollectionOptions({
query: (q) =>
q
.from({ user: usersCollection })
.groupBy(({ user }) => [user.departmentId, user.role])
.select(({ user }) => ({
departmentId: user.departmentId,
role: user.role,
count: count(user.id),
avgSalary: avg(user.salary),
}))
}))
```
### Aggregate Functions
Use various aggregate functions to summarize your data:
```ts
import { count, sum, avg, min, max } from '@tanstack/db'
const orderStats = createCollection(liveQueryCollectionOptions({
query: (q) =>
q
.from({ order: ordersCollection })
.groupBy(({ order }) => order.customerId)
.select(({ order }) => ({
customerId: order.customerId,
totalOrders: count(order.id),
totalAmount: sum(order.amount),
avgOrderValue: avg(order.amount),
minOrder: min(order.amount),
maxOrder: max(order.amount),
}))
}))
```
See the [Aggregate Functions](#aggregate-functions) section for a complete list of available aggregate functions.
### Having Clauses
Filter aggregated results using `having` - this is similar to the `where` clause, but is applied after the aggregation has been performed.
#### Method Signature
```ts
having(
condition: (row: TRow) => Expression
): Query
```
**Parameters:**
- `condition` - A callback function that receives table references (and `$selected` if the query contains a `select()` clause) and returns a boolean expression
```ts
// Using aggregate functions directly
const highValueCustomers = createLiveQueryCollection((q) =>
q
.from({ order: ordersCollection })
.groupBy(({ order }) => order.customerId)
.having(({ order }) => gt(sum(order.amount), 1000))
)
// Using SELECT fields via $selected (recommended when select() is used)
const highValueCustomersWithSelect = createLiveQueryCollection((q) =>
q
.from({ order: ordersCollection })
.groupBy(({ order }) => order.customerId)
.select(({ order }) => ({
customerId: order.customerId,
totalSpent: sum(order.amount),
orderCount: count(order.id),
}))
.having(({ $selected }) => gt($selected.totalSpent, 1000))
)
```
### Implicit Single-Group Aggregation
When you use aggregates without `groupBy`, the entire result set is grouped:
```ts
const overallStats = createLiveQueryCollection((q) =>
q
.from({ user: usersCollection })
.select(({ user }) => ({
totalUsers: count(user.id),
avgAge: avg(user.age),
maxSalary: max(user.salary),
}))
)
```
This is equivalent to grouping the entire collection into a single group.
### Accessing Grouped Data
Grouped results can be accessed by the group key:
```ts
const deptStats = createCollection(liveQueryCollectionOptions({
query: (q) =>
q
.from({ user: usersCollection })
.groupBy(({ user }) => user.departmentId)
.select(({ user }) => ({
departmentId: user.departmentId,
count: count(user.id),
}))
}))
// Access by department ID
const engineeringStats = deptStats.get(1)
```
> **Note**: Grouped results are keyed differently based on the grouping:
> - **Single column grouping**: Keyed by the actual value (e.g., `deptStats.get(1)`)
> - **Multiple column grouping**: Keyed by a JSON string of the grouped values (e.g., `userStats.get('[1,"admin"]')`)
## findOne
Use `findOne` to return a single result instead of an array. This is useful when you expect to find at most one matching record, such as when querying by a unique identifier.
The `findOne` method changes the return type from an array to a single object or `undefined`. When no matching record is found, the result is `undefined`.
### Method Signature
```ts
findOne(): Query
```
### Basic Usage
Find a specific user by ID:
```ts
const user = createLiveQueryCollection((q) =>
q
.from({ users: usersCollection })
.where(({ users }) => eq(users.id, 1))
.findOne()
)
// Result type: User | undefined
// If user with id=1 exists: { id: 1, name: 'John', ... }
// If not found: undefined
```
### With React Hooks
Use `findOne` with `useLiveQuery` to get a single record:
```tsx
import { useLiveQuery } from '@tanstack/react-db'
import { eq } from '@tanstack/db'
function UserProfile({ userId }: { userId: string }) {
const { data: user, isLoading } = useLiveQuery((q) =>
q
.from({ users: usersCollection })
.where(({ users }) => eq(users.id, userId))
.findOne()
, [userId])
if (isLoading) return Loading...
if (!user) return User not found
return {user.name}
}
```
### With Select
Combine `findOne` with `select` to project specific fields:
```ts
const userEmail = createLiveQueryCollection((q) =>
q
.from({ users: usersCollection })
.where(({ users }) => eq(users.id, 1))
.select(({ users }) => ({
id: users.id,
email: users.email,
}))
.findOne()
)
// Result type: { id: number, email: string } | undefined
```
### Return Type Behavior
The return type changes based on whether `findOne` is used:
```ts
// Without findOne - returns array
const users = createLiveQueryCollection((q) =>
q.from({ users: usersCollection })
)
// Type: Array
// With findOne - returns single object or undefined
const user = createLiveQueryCollection((q) =>
q.from({ users: usersCollection }).findOne()
)
// Type: User | undefined
```
### Best Practices
**Use when:**
- Querying by unique identifiers (ID, email, etc.)
- You expect at most one result
- You want type-safe single-record access without array indexing
**Avoid when:**
- You might have multiple matching records (use regular queries instead)
- You need to iterate over results
## Distinct
Use `distinct` to remove duplicate rows from your query results based on the selected columns. The `distinct` operator ensures that each unique combination of selected values appears only once in the result set.
> [!IMPORTANT]
> The `distinct` operator requires a `select` clause. You cannot use `distinct` without specifying which columns to select.
### Method Signature
```ts
distinct(): Query
```
### Basic Usage
Get unique values from a single column:
```ts
const uniqueCountries = createLiveQueryCollection((q) =>
q
.from({ user: usersCollection })
.select(({ user }) => ({ country: user.country }))
.distinct()
)
// Result contains only unique countries
// If you have users from USA, Canada, and UK, the result will have 3 items
```
### Multiple Column Distinct
Get unique combinations of multiple columns:
```ts
const uniqueRoleSalaryPairs = createLiveQueryCollection((q) =>
q
.from({ user: usersCollection })
.select(({ user }) => ({
role: user.role,
salary: user.salary,
}))
.distinct()
)
// Result contains only unique role-salary combinations
// e.g., Developer-75000, Developer-80000, Manager-90000
```
### Edge Cases
#### Null Values
Null values are treated as distinct values:
```ts
const uniqueValues = createLiveQueryCollection((q) =>
q
.from({ user: usersCollection })
.select(({ user }) => ({ department: user.department }))
.distinct()
)
// If some users have null departments, null will appear as a distinct value
// Result might be: ['Engineering', 'Marketing', null]
```
## Order By, Limit, and Offset
Use `orderBy`, `limit`, and `offset` to control the order and pagination of your results. Ordering is performed incrementally for optimal performance.
### Method Signatures
```ts
orderBy(
selector: (row: TRow) => Expression,
direction?: 'asc' | 'desc'
): Query
limit(count: number): Query
offset(count: number): Query
```
**Parameters:**
- `selector` - A callback function that receives the row object and returns the value to sort by
- `direction` - Sort direction: `'asc'` (default) or `'desc'`
- `count` - Number of rows to limit or skip
### Basic Ordering
Sort results by a single column:
```ts
const sortedUsers = createLiveQueryCollection((q) =>
q
.from({ user: usersCollection })
.orderBy(({ user }) => user.name)
.select(({ user }) => ({
id: user.id,
name: user.name,
}))
)
```
### Multiple Column Ordering
Order by multiple columns:
```ts
const sortedUsers = createLiveQueryCollection((q) =>
q
.from({ user: usersCollection })
.orderBy(({ user }) => user.departmentId, 'asc')
.orderBy(({ user }) => user.name, 'asc')
.select(({ user }) => ({
id: user.id,
name: user.name,
departmentId: user.departmentId,
}))
)
```
### Ordering by SELECT Fields
When you use `select()` with aggregates or computed values, you can order by those fields using the `$selected` namespace:
```ts
const topCustomers = createLiveQueryCollection((q) =>
q
.from({ order: ordersCollection })
.groupBy(({ order }) => order.customerId)
.select(({ order }) => ({
customerId: order.customerId,
totalSpent: sum(order.amount),
orderCount: count(order.id),
latestOrder: max(order.createdAt),
}))
.orderBy(({ $selected }) => $selected.totalSpent, 'desc')
.limit(10)
)
```
### Descending Order
Use `desc` for descending order:
```ts
const recentPosts = createLiveQueryCollection((q) =>
q
.from({ post: postsCollection })
.orderBy(({ post }) => post.createdAt, 'desc')
.select(({ post }) => ({
id: post.id,
title: post.title,
createdAt: post.createdAt,
}))
)
```
### Pagination with `limit` and `offset`
Skip results using `offset`:
```ts
const page2Users = createLiveQueryCollection((q) =>
q
.from({ user: usersCollection })
.orderBy(({ user }) => user.name, 'asc')
.limit(20)
.offset(20) // Skip first 20 results
.select(({ user }) => ({
id: user.id,
name: user.name,
}))
)
```
## Composable Queries
Build complex queries by composing smaller, reusable parts. This approach makes your queries more maintainable and allows for better performance through caching.
### Conditional Query Building
Build queries based on runtime conditions:
```ts
import { Query, eq } from '@tanstack/db'
function buildUserQuery(options: { activeOnly?: boolean; limit?: number }) {
let query = new Query().from({ user: usersCollection })
if (options.activeOnly) {
query = query.where(({ user }) => eq(user.active, true))
}
if (options.limit) {
query = query.limit(options.limit)
}
return query.select(({ user }) => ({
id: user.id,
name: user.name,
}))
}
const activeUsers = createLiveQueryCollection(buildUserQuery({ activeOnly: true, limit: 10 }))
```
### Caching Intermediate Results
The result of a live query collection is a collection itself, and will automatically update when the underlying data changes. This means that you can use the result of a live query collection as a source in another live query collection. This pattern is useful for building complex queries where you want to cache intermediate results to make further queries faster.
```ts
// Base query for active users
const activeUsers = createLiveQueryCollection((q) =>
q
.from({ user: usersCollection })
.where(({ user }) => eq(user.active, true))
)
// Query that depends on active users
const activeUserPosts = createLiveQueryCollection((q) =>
q
.from({ user: activeUsers })
.join({ post: postsCollection }, ({ user, post }) =>
eq(user.id, post.userId)
)
.select(({ user, post }) => ({
userName: user.name,
postTitle: post.title,
}))
)
```
### Reusable Query Definitions
You can use the `Query` class to create reusable query definitions. This is useful for building complex queries where you want to reuse the same query builder instance multiple times throughout your application.
```ts
import { Query, eq } from '@tanstack/db'
// Create a reusable query builder
const userQuery = new Query()
.from({ user: usersCollection })
.where(({ user }) => eq(user.active, true))
// Use it in different contexts
const activeUsers = createLiveQueryCollection({
query: userQuery.select(({ user }) => ({
id: user.id,
name: user.name,
}))
})
// Or as a subquery
const userPosts = createLiveQueryCollection((q) =>
q
.from({ activeUser: userQuery })
.join({ post: postsCollection }, ({ activeUser, post }) =>
eq(activeUser.id, post.userId)
)
)
```
### Reusable Callback Functions
Creating reusable query logic is a common pattern that improves code organization and maintainability. The recommended approach is to use callback functions with the `Ref` type rather than trying to type `QueryBuilder` instances directly.
#### The Recommended Pattern
Use `Ref` to create reusable filter and transform functions:
```ts
import type { Ref } from '@tanstack/db'
import { eq, gt, and } from '@tanstack/db'
// Create reusable filter callbacks
const isActiveUser = ({ user }: { user: Ref }) =>
eq(user.active, true)
const isAdultUser = ({ user }: { user: Ref }) =>
gt(user.age, 18)
const isActiveAdult = ({ user }: { user: Ref }) =>
and(isActiveUser({ user }), isAdultUser({ user }))
// Use them in queries - they work seamlessly with .where()
const activeAdults = createCollection(liveQueryCollectionOptions({
query: (q) =>
q
.from({ user: usersCollection })
.where(isActiveUser)
.where(isAdultUser)
.select(({ user }) => ({
id: user.id,
name: user.name,
age: user.age,
}))
}))
```
The callback signature `({ user }: { user: Ref }) => Expression` matches exactly what `.where()` expects, making it type-safe and composable.
#### Chaining Multiple Filters
You can chain multiple reusable filters:
```tsx
import { useLiveQuery } from '@tanstack/react-db'
const { data } = useLiveQuery((q) => {
return q
.from({ item: itemsCollection })
.where(({ item }) => eq(item.id, 1))
.where(activeItemFilter) // Reusable filter 1
.where(verifiedItemFilter) // Reusable filter 2
.select(({ item }) => ({ ...item }))
}, [])
```
#### Using with Different Aliases
The pattern works with any table alias:
```ts
const activeFilter = ({ item }: { item: Ref- }) =>
eq(item.active, true)
// Works with any alias name
const query1 = new Query()
.from({ item: itemsCollection })
.where(activeFilter)
const query2 = new Query()
.from({ i: itemsCollection })
.where(({ i }) => activeFilter({ item: i })) // Map the alias
```
#### Callbacks with Multiple Tables
For queries with joins, create callbacks that accept multiple refs:
```ts
const isHighValueCustomer = ({ user, order }: {
user: Ref
order: Ref
}) => and(
eq(user.active, true),
gt(order.amount, 1000)
)
// Use directly in where clause
const highValueCustomers = createCollection(liveQueryCollectionOptions({
query: (q) =>
q
.from({ user: usersCollection })
.join({ order: ordersCollection }, ({ user, order }) =>
eq(user.id, order.userId)
)
.where(isHighValueCustomer)
.select(({ user, order }) => ({
userName: user.name,
orderAmount: order.amount,
}))
}))
```
#### Why Not Type QueryBuilder?
You might be tempted to create functions that accept and return `QueryBuilder`:
```ts
// ❌ Not recommended - overly complex typing
const applyFilters = >(query: T): T => {
return query.where(({ item }) => eq(item.active, true))
}
```
This approach has several issues:
1. **Complex Types**: `QueryBuilder` generic represents the entire query context including base schema, current schema, joins, result types, etc.
2. **Type Inference**: The type changes with every method call, making it impractical to type manually
3. **Limited Flexibility**: Hard to compose multiple filters or use with different table aliases
Instead, use callback functions that work with the `.where()`, `.select()`, and other query methods directly.
#### Reusable Select Transformations
You can also create reusable select projections:
```ts
const basicUserInfo = ({ user }: { user: Ref }) => ({
id: user.id,
name: user.name,
email: user.email,
})
const userWithStats = ({ user }: { user: Ref }) => ({
...basicUserInfo({ user }),
isAdult: gt(user.age, 18),
isActive: eq(user.active, true),
})
const users = createLiveQueryCollection((q) =>
q
.from({ user: usersCollection })
.select(userWithStats)
)
```
This approach makes your query logic more modular, testable, and reusable across your application.
## Reactive Effects (createEffect)
While live query collections materialise query results into a collection you can subscribe to and iterate over, **reactive effects** let you respond to query result *changes* without materialising the full result set. Effects fire callbacks when rows enter, exit, or update within a query result.
This is useful for triggering side effects — sending notifications, syncing to external systems, generating AI responses, updating counters — whenever your data changes.
### When to Use Effects vs Live Query Collections
| Use case | Approach |
|----------|----------|
| Display query results in UI | Live query collection + `useLiveQuery` |
| React to changes (side effects) | `createEffect` / `useLiveQueryEffect` |
| Track new items entering a result set | `createEffect` with `onEnter` |
| Monitor items leaving a result set | `createEffect` with `onExit` |
| Respond to updates within a result set | `createEffect` with `onUpdate` |
### Basic Usage
```ts
import { createEffect, eq } from '@tanstack/db'
const effect = createEffect({
query: (q) =>
q
.from({ msg: messagesCollection })
.where(({ msg }) => eq(msg.role, 'user')),
onEnter: async (event) => {
console.log('New user message:', event.value)
await generateResponse(event.value)
},
})
// Later: stop the effect
await effect.dispose()
```
### Configuration
`createEffect` accepts an `EffectConfig` object:
```ts
const effect = createEffect({
id: 'my-effect', // Optional: auto-generated if not provided
query: (q) => q.from(...), // Query to watch
onEnter: (event, ctx) => { ... }, // Per-enter callback
onUpdate: (event, ctx) => { ... }, // Per-update callback
onExit: (event, ctx) => { ... }, // Per-exit callback
onBatch: (events, ctx) => { ... }, // Full batch callback
onError: (error, event) => { ... }, // Callback error handler
onSourceError: (error) => { ... }, // Source collection error callback
skipInitial: false, // Skip deltas during initial load
})
```
| Option | Type | Description |
|--------|------|-------------|
| `id` | `string` (optional) | Identifier for debugging/tracing. Auto-generated as `live-query-effect-{n}` if not provided. |
| `query` | `QueryBuilder` or function | The query to watch. Accepts the same builder function or `QueryBuilder` instance as live query collections. |
| `onEnter` | `(event, ctx) => void \| Promise` (optional) | Called once for each row entering the query result. |
| `onUpdate` | `(event, ctx) => void \| Promise` (optional) | Called once for each row updating within the query result. |
| `onExit` | `(event, ctx) => void \| Promise` (optional) | Called once for each row exiting the query result. |
| `onBatch` | `(events, ctx) => void \| Promise` (optional) | Called once per graph run with the full unfiltered batch of delta events. |
| `onError` | `(error, event) => void` (optional) | Called when `onEnter`, `onUpdate`, `onExit`, or `onBatch` throws or rejects. |
| `onSourceError` | `(error) => void` (optional) | Called when a source collection enters an error or cleaned-up state. The effect is automatically disposed after this fires. If not provided, the error is logged to `console.error`. |
| `skipInitial` | `boolean` (optional) | When `true`, deltas from the initial data load are suppressed. Only subsequent changes fire handlers. Defaults to `false`. |
### Delta Events
Each delta event describes a single row change within the query result:
```ts
interface DeltaEvent {
type: 'enter' | 'exit' | 'update'
key: TKey
value: TRow
previousValue?: TRow // Only present for 'update' events
}
```
| Event type | Meaning | `value` | `previousValue` |
|------------|---------|---------|------------------|
| `enter` | Row entered the query result | The new row | — |
| `exit` | Row left the query result | The exiting row | — |
| `update` | Row changed but stayed in the result | The new row | The row before the change |
### Named Callbacks
Use the callback that matches the query-result transition you care about:
```ts
// Only new rows entering the result
createEffect({ onEnter: (event) => { ... }, ... })
// Only rows leaving the result
createEffect({ onExit: (event) => { ... }, ... })
// Only rows that changed but stayed in the result
createEffect({ onUpdate: (event) => { ... }, ... })
// Inspect the full mixed batch for a graph run
createEffect({ onBatch: (events) => { ... }, ... })
```
### Per-Row Callbacks vs `onBatch`
You can provide per-row callbacks, `onBatch`, or both:
```ts
createEffect({
query: (q) => q.from({ user: usersCollection }),
onEnter: (event, ctx) => {
console.log(`enter: ${event.key}`)
},
onExit: (event, ctx) => {
console.log(`exit: ${event.key}`)
},
onBatch: (events, ctx) => {
console.log(`Batch of ${events.length} events`)
},
})
```
Both handlers receive an `EffectContext`:
```ts
interface EffectContext {
effectId: string // The effect's ID
signal: AbortSignal // Aborted when effect.dispose() is called
}
```
The `signal` is useful for cancelling in-flight async work when the effect is disposed:
```ts
createEffect({
query: (q) => q.from({ task: tasksCollection }),
onEnter: async (event, ctx) => {
const result = await fetch('/api/process', {
method: 'POST',
body: JSON.stringify(event.value),
signal: ctx.signal, // Cancelled on dispose
})
// ...
},
})
```
### Skipping Initial Data
By default, effects process all data including the initial load. Set `skipInitial: true` to only respond to changes that happen after the initial sync:
```ts
// Only react to NEW messages, not existing ones
const effect = createEffect({
query: (q) =>
q.from({ msg: messagesCollection })
.where(({ msg }) => eq(msg.role, 'user')),
skipInitial: true,
onEnter: async (event) => {
await sendNotification(event.value)
},
})
```
### Error Handling
Errors thrown by `onEnter`, `onUpdate`, `onExit`, or `onBatch` (sync or async) are caught and routed to `onError`. If no `onError` is provided, they are logged to `console.error`:
```ts
createEffect({
query: (q) => q.from({ order: ordersCollection }),
onEnter: async (event) => {
await processOrder(event.value)
},
onError: (error, event) => {
console.error(`Failed to process order ${event.key}:`, error)
reportToErrorTracker(error)
},
})
```
If a source collection enters an error or cleaned-up state, the effect automatically disposes itself. Use `onSourceError` to handle this:
```ts
createEffect({
query: (q) => q.from({ data: dataCollection }),
onBatch: (events) => { ... },
onSourceError: (error) => {
console.warn('Data source failed, effect disposed:', error.message)
},
})
```
### Disposal
`createEffect` returns an `Effect` handle with a `dispose()` method:
```ts
const effect = createEffect({ ... })
// Check if disposed
console.log(effect.disposed) // false
// Dispose: unsubscribes from sources, aborts the signal,
// and waits for in-flight async handlers to settle
await effect.dispose()
console.log(effect.disposed) // true
```
`dispose()` is idempotent — calling it multiple times is safe. It returns a promise that resolves when all in-flight async handlers have settled (via `Promise.allSettled`).
### Query Features
Effects support the full query system — everything you can do with live query collections works with effects:
```ts
// Joins
createEffect({
query: (q) =>
q
.from({ user: usersCollection })
.join({ post: postsCollection }, ({ user, post }) =>
eq(user.id, post.userId)
)
.select(({ user, post }) => ({
userName: user.name,
postTitle: post.title,
})),
onEnter: (event) => {
console.log(`${event.value.userName} published "${event.value.postTitle}"`)
},
})
// Filters
createEffect({
query: (q) =>
q
.from({ user: usersCollection })
.where(({ user }) => eq(user.role, 'admin')),
onEnter: (event) => {
console.log(`New admin: ${event.value.name}`)
},
})
// OrderBy + Limit (top-K window)
createEffect({
query: (q) =>
q
.from({ score: scoresCollection })
.orderBy(({ score }) => score.points, 'desc')
.limit(10),
onBatch: (events) => {
// Fires once per graph run with all enter/update/exit events
for (const event of events) {
console.log(`${event.type}: ${event.value.name} (${event.value.points} pts)`)
}
},
})
```
When using `orderBy` with `limit`, effects track a top-K window. You receive `enter` events when items enter the window and `exit` events when they're displaced.
### Transaction Coalescing
When multiple changes occur within a single transaction, effects coalesce them into a single batch. This means your handlers are called once with all the changes from that transaction, not once per individual write:
```ts
createEffect({
query: (q) => q.from({ item: itemsCollection }),
onBatch: (events) => {
// If 3 items are inserted in one transaction,
// this fires once with all 3 events
console.log(`${events.length} items added`)
},
})
```
### Using with React
The `useLiveQueryEffect` hook manages the effect lifecycle automatically — creating on mount, disposing on unmount, and recreating when dependencies change:
```tsx
import { useLiveQueryEffect } from '@tanstack/react-db'
import { eq } from '@tanstack/db'
function ChatComponent({ channelId }: { channelId: string }) {
useLiveQueryEffect(
{
query: (q) =>
q
.from({ msg: messagesCollection })
.where(({ msg }) => eq(msg.channelId, channelId)),
skipInitial: true,
onEnter: async (event) => {
await playNotificationSound()
},
},
[channelId] // Recreate effect when channelId changes
)
return
...
}
```
The second argument is a dependency array (like `useEffect`). When dependencies change, the old effect is disposed and a new one is created with the updated config.
### Complete Example
Here's a more complete example showing an effect that monitors order status changes and sends notifications:
```ts
import { createEffect, eq } from '@tanstack/db'
const orderEffect = createEffect({
id: 'order-status-monitor',
query: (q) =>
q
.from({ order: ordersCollection })
.join({ customer: customersCollection }, ({ order, customer }) =>
eq(order.customerId, customer.id)
)
.where(({ order }) => eq(order.status, 'shipped'))
.select(({ order, customer }) => ({
orderId: order.id,
customerEmail: customer.email,
trackingNumber: order.trackingNumber,
})),
skipInitial: true,
onEnter: async (event, ctx) => {
await sendShipmentEmail({
to: event.value.customerEmail,
orderId: event.value.orderId,
tracking: event.value.trackingNumber,
signal: ctx.signal,
})
},
onError: (error, event) => {
console.error(`Failed to notify for order ${event.key}:`, error)
},
onSourceError: (error) => {
alertOpsTeam('Order monitoring effect failed', error)
},
})
// On application shutdown
await orderEffect.dispose()
```
## Expression Functions Reference
The query system provides a comprehensive set of functions for filtering, transforming, and aggregating data.
### Comparison Operators
#### `eq(left, right)`
Equality comparison:
```ts
eq(user.id, 1)
eq(user.name, 'John')
```
#### `gt(left, right)`, `gte(left, right)`, `lt(left, right)`, `lte(left, right)`
Numeric, string and date comparisons:
```ts
gt(user.age, 18)
gte(user.salary, 50000)
lt(user.createdAt, new Date('2024-01-01'))
lte(user.rating, 5)
```
#### `inArray(value, array)`
Check if a value is in an array:
```ts
inArray(user.id, [1, 2, 3])
inArray(user.role, ['admin', 'moderator'])
```
#### `like(value, pattern)`, `ilike(value, pattern)`
String pattern matching:
```ts
like(user.name, 'John%') // Case-sensitive
ilike(user.email, '%@gmail.com') // Case-insensitive
```
#### `isUndefined(value)`, `isNull(value)`
Check for missing vs null values:
```ts
// Check if a property is missing/undefined
isUndefined(user.profile)
// Check if a value is explicitly null
isNull(user.profile)
```
These functions are particularly important when working with joins and optional properties, as they distinguish between:
- `undefined`: The property is absent or not present
- `null`: The property exists but is explicitly set to null
**Example with joins:**
```ts
// Find users without a matching profile (left join resulted in undefined)
const usersWithoutProfiles = createLiveQueryCollection((q) =>
q
.from({ user: usersCollection })
.leftJoin(
{ profile: profilesCollection },
({ user, profile }) => eq(user.id, profile.userId)
)
.where(({ profile }) => isUndefined(profile))
)
// Find users with explicitly null bio field
const usersWithNullBio = createLiveQueryCollection((q) =>
q
.from({ user: usersCollection })
.where(({ user }) => isNull(user.bio))
)
```
### Logical Operators
#### `and(...conditions)`
Combine conditions with AND logic:
```ts
and(
eq(user.active, true),
gt(user.age, 18),
eq(user.role, 'user')
)
```
#### `or(...conditions)`
Combine conditions with OR logic:
```ts
or(
eq(user.role, 'admin'),
eq(user.role, 'moderator')
)
```
#### `not(condition)`
Negate a condition:
```ts
not(eq(user.active, false))
```
### String Functions
#### `upper(value)`, `lower(value)`
Convert case:
```ts
upper(user.name) // 'JOHN'
lower(user.email) // 'john@example.com'
```
#### `length(value)`
Get string or array length:
```ts
length(user.name) // String length
length(user.tags) // Array length
```
#### `concat(...values)`
Concatenate strings:
```ts
concat(user.firstName, ' ', user.lastName)
concat('User: ', user.name, ' (', user.id, ')')
```
### Mathematical Functions
#### `add(left, right)`
Add two numbers:
```ts
add(user.salary, user.bonus)
```
#### `coalesce(...values)`
Return the first non-null value:
```ts
coalesce(user.displayName, user.name, 'Unknown')
```
### Aggregate Functions
#### `count(value)`
Count non-null values:
```ts
count(user.id) // Count all users
count(user.postId) // Count users with posts
```
#### `sum(value)`
Sum numeric values:
```ts
sum(order.amount)
sum(user.salary)
```
#### `avg(value)`
Calculate average:
```ts
avg(user.salary)
avg(order.amount)
```
#### `min(value)`, `max(value)`
Find minimum and maximum values:
```ts
min(user.salary)
max(order.amount)
```
### Function Composition
Functions can be composed and chained:
```ts
// Complex condition
and(
eq(user.active, true),
or(
gt(user.age, 25),
eq(user.role, 'admin')
),
not(inArray(user.id, bannedUserIds))
)
// Complex transformation
concat(
upper(user.firstName),
' ',
upper(user.lastName),
' (',
user.id,
')'
)
// Complex aggregation
avg(add(user.salary, coalesce(user.bonus, 0)))
```
## Functional Variants
The functional variant API provides an alternative to the standard API, offering more flexibility for complex transformations. With functional variants, the callback functions contain actual code that gets executed to perform the operation, giving you the full power of JavaScript at your disposal.
> [!WARNING]
> The functional variant API cannot be optimized by the query optimizer or use collection indexes. It is intended for use in rare cases where the standard API is not sufficient.
### Functional Select
> [!WARNING]
> `fn.select()` cannot be used with `groupBy()`. The `groupBy` operator needs to statically analyze the `select` clause to discover which aggregate functions to compute, which is not possible with an opaque JavaScript function. Use the standard `.select()` API for grouped queries.
Use `fn.select()` for complex transformations with JavaScript logic:
```ts
const userProfiles = createLiveQueryCollection((q) =>
q
.from({ user: usersCollection })
.fn.select((row) => ({
id: row.user.id,
displayName: `${row.user.firstName} ${row.user.lastName}`,
salaryTier: row.user.salary > 100000 ? 'senior' : 'junior',
emailDomain: row.user.email.split('@')[1],
isHighEarner: row.user.salary > 75000,
}))
)
```
### Functional Where
Use `fn.where()` for complex filtering logic:
```ts
const specialUsers = createLiveQueryCollection((q) =>
q
.from({ user: usersCollection })
.fn.where((row) => {
const user = row.user
return user.active &&
(user.age > 25 || user.role === 'admin') &&
user.email.includes('@company.com')
})
)
```
### Functional Having
Use `fn.having()` for complex aggregation filtering:
```ts
const highValueCustomers = createLiveQueryCollection((q) =>
q
.from({ order: ordersCollection })
.groupBy(({ order }) => order.customerId)
.select(({ order }) => ({
customerId: order.customerId,
totalSpent: sum(order.amount),
orderCount: count(order.id),
}))
.fn.having(({ $selected }) => {
return $selected.totalSpent > 1000 && $selected.orderCount >= 3
})
)
```
### Complex Transformations
Functional variants excel at complex data transformations:
```ts
const userProfiles = createLiveQueryCollection((q) =>
q
.from({ user: usersCollection })
.fn.select((row) => {
const user = row.user
const fullName = `${user.firstName} ${user.lastName}`.trim()
const emailDomain = user.email.split('@')[1]
const ageGroup = user.age < 25 ? 'young' : user.age < 50 ? 'adult' : 'senior'
return {
userId: user.id,
displayName: fullName || user.name,
contactInfo: {
email: user.email,
domain: emailDomain,
isCompanyEmail: emailDomain === 'company.com'
},
demographics: {
age: user.age,
ageGroup: ageGroup,
isAdult: user.age >= 18
},
status: user.active ? 'active' : 'inactive',
profileStrength: fullName && user.email && user.age ? 'complete' : 'incomplete'
}
})
)
```
### Type Inference
Functional variants maintain full TypeScript support:
```ts
const processedUsers = createLiveQueryCollection((q) =>
q
.from({ user: usersCollection })
.fn.select((row): ProcessedUser => ({
id: row.user.id,
name: row.user.name.toUpperCase(),
age: row.user.age,
ageGroup: row.user.age < 25 ? 'young' : row.user.age < 50 ? 'adult' : 'senior',
}))
)
```
### When to Use Functional Variants
Use functional variants when you need:
- Complex JavaScript logic that can't be expressed with built-in functions
- Integration with external libraries or utilities
- Full JavaScript power for custom operations
The callbacks in functional variants are actual JavaScript functions that get executed, unlike the standard API which uses declarative expressions. This gives you complete control over the logic but comes with the trade-off of reduced optimization opportunities.
However, prefer the standard API when possible, as it provides better performance and optimization opportunities.