Queueing Guide

Unlike Rate Limiting, Throttling, and Debouncing which drop executions when they occur too frequently, queuers ensure that every operation is processed. They provide a way to manage and control the flow of operations without losing any requests. This makes them ideal for scenarios where data loss is unacceptable. This guide will cover the Queueing concepts of TanStack Pacer.

Queueing Concept

Queueing ensures that every operation is eventually processed, even if they come in faster than they can be handled. Unlike the other execution control techniques that drop excess operations, queueing buffers operations in an ordered list and processes them according to specific rules. This makes queueing the only "lossless" execution control technique in TanStack Pacer.

Queueing Visualization

text

Queueing (processing one item every 2 ticks)
Timeline: [1 second per tick]
Calls:        ⬇️  ⬇️  ⬇️     ⬇️  ⬇️     ⬇️  ⬇️  ⬇️
Queue:       [ABC]   [BC]    [BCDE]    [DE]    [E]    []
Executed:     ✅     ✅       ✅        ✅      ✅     ✅
             [=================================================================]
             ^ Unlike rate limiting/throttling/debouncing,
               ALL calls are eventually processed in order

             [Items queue up]   [Process steadily]   [Empty]
              when busy          one by one           queue

Queueing (processing one item every 2 ticks)
Timeline: [1 second per tick]
Calls:        ⬇️  ⬇️  ⬇️     ⬇️  ⬇️     ⬇️  ⬇️  ⬇️
Queue:       [ABC]   [BC]    [BCDE]    [DE]    [E]    []
Executed:     ✅     ✅       ✅        ✅      ✅     ✅
             [=================================================================]
             ^ Unlike rate limiting/throttling/debouncing,
               ALL calls are eventually processed in order

             [Items queue up]   [Process steadily]   [Empty]
              when busy          one by one           queue

When to Use Queueing

Queueing is particularly important when you need to ensure that every operation is processed, even if it means introducing some delay. This makes it ideal for scenarios where data consistency and completeness are more important than immediate execution.

Common use cases include:

Processing user interactions in a UI where every action must be recorded
Handling database operations that need to maintain data consistency
Managing API requests that must all complete successfully
Coordinating background tasks that can't be dropped
Animation sequences where every frame matters
Form submissions where every entry needs to be saved

When Not to Use Queueing

Queueing might not be the best choice when:

Immediate feedback is more important than processing every operation
You only care about the most recent value (use debouncing instead)

Tip

If you're currently using rate limiting, throttling, or debouncing but finding that dropped operations are causing problems, queueing is likely the solution you need.

Queueing in TanStack Pacer

TanStack Pacer provides queueing through the simple queue function and the more powerful Queuer class. While other execution control techniques typically favor their function-based APIs, queueing often benefits from the additional control provided by the class-based API.

Basic Usage with queue

The queue function provides a simple way to create an always-running queue that processes items as they're added:

import { queue } from '@tanstack/pacer'

// Create a queue that processes items every second
const processItems = queue<number>({
  wait: 1000,
  onItemsChange: (queuer) => {
    console.log('Current queue:', queuer.getAllItems())
  }
})

// Add items to be processed
processItems(1) // Processed immediately
processItems(2) // Processed after 1 second
processItems(3) // Processed after 2 seconds

import { queue } from '@tanstack/pacer'

// Create a queue that processes items every second
const processItems = queue<number>({
  wait: 1000,
  onItemsChange: (queuer) => {
    console.log('Current queue:', queuer.getAllItems())
  }
})

// Add items to be processed
processItems(1) // Processed immediately
processItems(2) // Processed after 1 second
processItems(3) // Processed after 2 seconds

While the queue function is simple to use, it only provides a basic always-running queue through the addItem method. For most use cases, you'll want the additional control and features provided by the Queuer class.

Advanced Usage with Queuer Class

The Queuer class provides complete control over queue behavior and processing:

import { Queuer } from '@tanstack/pacer'

// Create a queue that processes items every second
const queue = new Queuer<number>({
  wait: 1000, // Wait 1 second between processing items
  onItemsChange: (queuer) => {
    console.log('Current queue:', queuer.getAllItems())
  }
})

// Start processing
queue.start()

// Add items to be processed
queue.addItem(1)
queue.addItem(2)
queue.addItem(3)

// Items will be processed one at a time with 1 second delay between each
// Output:
// Processing: 1 (immediately)
// Processing: 2 (after 1 second)
// Processing: 3 (after 2 seconds)

import { Queuer } from '@tanstack/pacer'

// Create a queue that processes items every second
const queue = new Queuer<number>({
  wait: 1000, // Wait 1 second between processing items
  onItemsChange: (queuer) => {
    console.log('Current queue:', queuer.getAllItems())
  }
})

// Start processing
queue.start()

// Add items to be processed
queue.addItem(1)
queue.addItem(2)
queue.addItem(3)

// Items will be processed one at a time with 1 second delay between each
// Output:
// Processing: 1 (immediately)
// Processing: 2 (after 1 second)
// Processing: 3 (after 2 seconds)

Queue Types and Ordering

What makes TanStack Pacer's Queuer unique is its ability to adapt to different use cases through its position-based API. The same Queuer can behave as a traditional queue, a stack, or a double-ended queue, all through the same consistent interface.

FIFO Queue (First In, First Out)

The default behavior where items are processed in the order they were added. This is the most common queue type and follows the principle that the first item added should be the first one processed.

text

FIFO Queue Visualization:

Entry →  [A][B][C][D] → Exit
         ⬇️         ⬆️
      New items   Items are
      added here  processed here

Timeline: [1 second per tick]
Calls:        ⬇️  ⬇️  ⬇️     ⬇️
Queue:       [ABC]   [BC]    [C]    []
Processed:    A       B       C

FIFO Queue Visualization:

Entry →  [A][B][C][D] → Exit
         ⬇️         ⬆️
      New items   Items are
      added here  processed here

Timeline: [1 second per tick]
Calls:        ⬇️  ⬇️  ⬇️     ⬇️
Queue:       [ABC]   [BC]    [C]    []
Processed:    A       B       C

FIFO queues are ideal for:

Task processing where order matters
Message queues where messages need to be processed in sequence
Print queues where documents should be printed in the order they were sent
Event handling systems where events must be processed in chronological order

const queue = new Queuer<number>({
  addItemsTo: 'back', // default
  getItemsFrom: 'front', // default
})
queue.addItem(1) // [1]
queue.addItem(2) // [1, 2]
// Processes: 1, then 2

const queue = new Queuer<number>({
  addItemsTo: 'back', // default
  getItemsFrom: 'front', // default
})
queue.addItem(1) // [1]
queue.addItem(2) // [1, 2]
// Processes: 1, then 2

LIFO Stack (Last In, First Out)

By specifying 'back' as the position for both adding and retrieving items, the queuer behaves like a stack. In a stack, the most recently added item is the first one to be processed.

text

LIFO Stack Visualization:

     ⬆️ Process
    [D] ← Most recently added
    [C]
    [B]
    [A] ← First added
     ⬇️ Entry

Timeline: [1 second per tick]
Calls:        ⬇️  ⬇️  ⬇️     ⬇️
Queue:       [ABC]   [AB]    [A]    []
Processed:    C       B       A

LIFO Stack Visualization:

     ⬆️ Process
    [D] ← Most recently added
    [C]
    [B]
    [A] ← First added
     ⬇️ Entry

Timeline: [1 second per tick]
Calls:        ⬇️  ⬇️  ⬇️     ⬇️
Queue:       [ABC]   [AB]    [A]    []
Processed:    C       B       A

Stack behavior is particularly useful for:

Undo/redo systems where the most recent action should be undone first
Browser history navigation where you want to go back to the most recent page
Function call stacks in programming language implementations
Depth-first traversal algorithms

const stack = new Queuer<number>({
  addItemsTo: 'back', // default
  getItemsFrom: 'back', // override default for stack behavior
})
stack.addItem(1) // [1]
stack.addItem(2) // [1, 2]
// Items will process in order: 2, then 1

stack.getNextItem('back') // get next item from back of queue instead of front

const stack = new Queuer<number>({
  addItemsTo: 'back', // default
  getItemsFrom: 'back', // override default for stack behavior
})
stack.addItem(1) // [1]
stack.addItem(2) // [1, 2]
// Items will process in order: 2, then 1

stack.getNextItem('back') // get next item from back of queue instead of front

Priority Queue

Priority queues add another dimension to queue ordering by allowing items to be sorted based on their priority rather than just their insertion order. Each item is assigned a priority value, and the queue automatically maintains the items in priority order.

text

Priority Queue Visualization:

Entry →  [P:5][P:3][P:2][P:1] → Exit
          ⬇️           ⬆️
     High Priority   Low Priority
     items here      processed last

Timeline: [1 second per tick]
Calls:        ⬇️(P:2)  ⬇️(P:5)  ⬇️(P:1)     ⬇️(P:3)
Queue:       [2]      [5,2]    [5,2,1]    [3,2,1]    [2,1]    [1]    []
Processed:              5         -          3         2        1

Priority Queue Visualization:

Entry →  [P:5][P:3][P:2][P:1] → Exit
          ⬇️           ⬆️
     High Priority   Low Priority
     items here      processed last

Timeline: [1 second per tick]
Calls:        ⬇️(P:2)  ⬇️(P:5)  ⬇️(P:1)     ⬇️(P:3)
Queue:       [2]      [5,2]    [5,2,1]    [3,2,1]    [2,1]    [1]    []
Processed:              5         -          3         2        1

Priority queues are essential for:

Task schedulers where some tasks are more urgent than others
Network packet routing where certain types of traffic need preferential treatment
Event systems where high-priority events should be handled before lower-priority ones
Resource allocation where some requests are more important than others

const priorityQueue = new Queuer<number>({
  getPriority: (n) => n // Higher numbers have priority
})
priorityQueue.addItem(1) // [1]
priorityQueue.addItem(3) // [3, 1]
priorityQueue.addItem(2) // [3, 2, 1]
// Processes: 3, 2, then 1

const priorityQueue = new Queuer<number>({
  getPriority: (n) => n // Higher numbers have priority
})
priorityQueue.addItem(1) // [1]
priorityQueue.addItem(3) // [3, 1]
priorityQueue.addItem(2) // [3, 2, 1]
// Processes: 3, 2, then 1

Starting and Stopping

The Queuer class supports starting and stopping processing through the start() and stop() methods, and can be configured to start automatically with the started option:

const queue = new Queuer<number>({ 
  wait: 1000,
  started: false // Start paused
})

// Control processing
queue.start() // Begin processing items
queue.stop()  // Pause processing

// Check processing state
console.log(queue.getIsRunning()) // Whether the queue is currently processing
console.log(queue.getIsIdle())    // Whether the queue is running but empty

const queue = new Queuer<number>({ 
  wait: 1000,
  started: false // Start paused
})

// Control processing
queue.start() // Begin processing items
queue.stop()  // Pause processing

// Check processing state
console.log(queue.getIsRunning()) // Whether the queue is currently processing
console.log(queue.getIsIdle())    // Whether the queue is running but empty

If you are using a framework adapter where the queuer options are reactive, you can set the started option to a conditional value:

const queue = useQueuer(
  processItem, 
  { 
    wait: 1000,
    started: isOnline // Start/stop based on connection status IF using a framework adapter that supports reactive options
  }
)

const queue = useQueuer(
  processItem, 
  { 
    wait: 1000,
    started: isOnline // Start/stop based on connection status IF using a framework adapter that supports reactive options
  }
)

Additional Features

The Queuer provides several helpful methods for queue management:

// Queue inspection
queue.getPeek()           // View next item without removing it
queue.getSize()          // Get current queue size
queue.getIsEmpty()       // Check if queue is empty
queue.getIsFull()        // Check if queue has reached maxSize
queue.getAllItems()   // Get copy of all queued items

// Queue manipulation
queue.clear()         // Remove all items
queue.reset()         // Reset to initial state
queue.getExecutionCount() // Get number of processed items

// Event handling
queue.onItemsChange((item) => {
  console.log('Processed:', item)
})

// Queue inspection
queue.getPeek()           // View next item without removing it
queue.getSize()          // Get current queue size
queue.getIsEmpty()       // Check if queue is empty
queue.getIsFull()        // Check if queue has reached maxSize
queue.getAllItems()   // Get copy of all queued items

// Queue manipulation
queue.clear()         // Remove all items
queue.reset()         // Reset to initial state
queue.getExecutionCount() // Get number of processed items

// Event handling
queue.onItemsChange((item) => {
  console.log('Processed:', item)
})

Rejection Handling

When a queue reaches its maximum size (set by maxSize option), new items will be rejected. The Queuer provides ways to handle and monitor these rejections:

const queue = new Queuer<number>({
  maxSize: 2, // Only allow 2 items in queue
  onReject: (item, queuer) => {
    console.log('Queue is full. Item rejected:', item)
  }
})

queue.addItem(1) // Accepted
queue.addItem(2) // Accepted
queue.addItem(3) // Rejected, triggers onReject callback

console.log(queue.getRejectionCount()) // 1

const queue = new Queuer<number>({
  maxSize: 2, // Only allow 2 items in queue
  onReject: (item, queuer) => {
    console.log('Queue is full. Item rejected:', item)
  }
})

queue.addItem(1) // Accepted
queue.addItem(2) // Accepted
queue.addItem(3) // Rejected, triggers onReject callback

console.log(queue.getRejectionCount()) // 1

Initial Items

You can pre-populate a queue with initial items when creating it:

const queue = new Queuer<number>({
  initialItems: [1, 2, 3],
  started: true // Start processing immediately
})

// Queue starts with [1, 2, 3] and begins processing

const queue = new Queuer<number>({
  initialItems: [1, 2, 3],
  started: true // Start processing immediately
})

// Queue starts with [1, 2, 3] and begins processing

Dynamic Configuration

The Queuer's options can be modified after creation using setOptions() and retrieved using getOptions():

const queue = new Queuer<number>({
  wait: 1000,
  started: false
})

// Change configuration
queue.setOptions({
  wait: 500, // Process items twice as fast
  started: true // Start processing
})

// Get current configuration
const options = queue.getOptions()
console.log(options.wait) // 500

const queue = new Queuer<number>({
  wait: 1000,
  started: false
})

// Change configuration
queue.setOptions({
  wait: 500, // Process items twice as fast
  started: true // Start processing
})

// Get current configuration
const options = queue.getOptions()
console.log(options.wait) // 500

Performance Monitoring

The Queuer provides methods to monitor its performance:

const queue = new Queuer<number>()

// Add and process some items
queue.addItem(1)
queue.addItem(2)
queue.addItem(3)

console.log(queue.getExecutionCount()) // Number of items processed
console.log(queue.getRejectionCount()) // Number of items rejected

const queue = new Queuer<number>()

// Add and process some items
queue.addItem(1)
queue.addItem(2)
queue.addItem(3)

console.log(queue.getExecutionCount()) // Number of items processed
console.log(queue.getRejectionCount()) // Number of items rejected

Asynchronous Queueing

For handling asynchronous operations with multiple workers, see the Async Queueing Guide which covers the AsyncQueuer class.

Framework Adapters

Each framework adapter builds convenient hooks and functions around the queuer classes. Hooks like useQueuer or useQueueState are small wrappers that can cut down on the boilerplate needed in your own code for some common use cases.

Queueing Concept

Queueing Visualization

When to Use Queueing

When Not to Use Queueing

Queueing in TanStack Pacer

Basic Usage with queue

Advanced Usage with Queuer Class

Queue Types and Ordering

FIFO Queue (First In, First Out)

LIFO Stack (Last In, First Out)

Priority Queue

Starting and Stopping

Additional Features

Rejection Handling

Initial Items

Dynamic Configuration

Performance Monitoring

Asynchronous Queueing

Framework Adapters

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