Redux Toolkit's createSelector: Advanced Performance Optimization Techniques

Anton Ioffe - January 13th 2024 - 10 minutes read

In the ceaseless quest for performance refinement in modern web applications, the Redux Toolkit's createSelector stands as an indispensable architect of state efficiency. Journey with us as we dissect createSelector's advanced faculties, elevating selectors from mere computational entities to masterful conduits of memoization and state transformation. Through the looking glass of sophisticated memoization strategies and modular design patterns, we'll navigate the labyrinth of complex state management and sidestep the treacherous pitfalls that even seasoned developers might overlook. Engage in the nuanced debate between useSelector and connect, unraveling the performance narratives that could redefine your React components' responsiveness. This article promises to equip you with the granular optimization techniques that are the hallmarks of a trailblazing developer, setting the stage for you to sculpt Redux applications that stand resilient in the face of ever-evolving web demands.

Deep Dive into createSelector and State Derivation

In redux-based applications, the efficiency of state management hinges on how well we design and utilize selectors. The createSelector function from Redux Toolkit harnesses the concept of memoization to conserve computational resources by caching the results of selectors that compute derived state. This is particularly crucial when we extend our state derivation logic to transformational duties such as filtering, aggregating, or combining data segments from the global store. By focusing on the derivation of state inside selectors, developers are able to maintain a lean store, reducing bloat and complexity at the source.

Memoization provided by createSelector ensures that derived state is recalculated only when the relevant slices of the global state change. This approach mitigates unnecessary re-renders and computations that are commonplace in large applications, directly impacting the application's performance. With Redux advocating for a single source of truth, the ability to selectively compute and cache derived state without cluttering the central store moves the needle towards more predictable and easier-to-debug applications. By using selectors to encapsulate the logic for derived state, we keep state transformations declarative and neatly isolated.

The design of createSelector entails a further refinement in the granularity of state access. It permits the chaining of selectors such that the output of one selector can seamlessly serve as the input for another. This empowers developers to build complex derived states in an incremental and easily understandable manner. For instance, one might create a selector to extract a list of items, another to filter this list based on criteria, and a third one to compute a final value such as a subtotal. The decoupling of these stages not only enhances code readability and maintenance but also ensures that only the minimum necessary recalculations occur, thus preserving application responsiveness.

Moreover, memoization dovetails with best practices of state management by keeping the Redux store minimal. Rather than storing every conceivable piece of derived state, developers are encouraged to calculate these as needed from the minimal store representation. createSelector plays a pivotal role by facilitating this principle, ensuring that heavy computations for derived state are offloaded from the components to the selectors themselves. This, in turn, leads to a more stable and consistent approach to handling dynamic data while keeping the essential complexity of the state itself to a minimum.

As a closing touch, it's worth pondering the inherent consequences of memoization on your application logic. Overly broad selectors might seem beneficial but can lead to performance bottlenecks, given their extensive dependency tree. It is thus essential to tailor selectors to be as specific as necessary—striking a balance between granularity and expansiveness. Embracing createSelector with an informed strategy enables developers to create high-performance applications that efficiently compute derived states only when truly needed, embodying the philosophy of performing heavy lifting only when the load changes.

Optimizing Selector Performance: Memoization Strategies

When optimizing the performance of selectors with createSelector, advanced memoization strategies are paramount to achieving efficient state updates and rendering. The efficacy of memoization can significantly depend on the complexity and the precision of the input selectors. Tailoring input selectors to be as specific as possible, calculating only the necessary slices of state, ensures cache efficiency and prevents unnecessary cache invalidation. An incorrectly broad selector will capture more state changes than necessary, resulting in wasteful recomputations. Crafting succinct and targeted selectors might look like this:

const selectUser = state => state.users;
const selectUserId = (state, userId) => selectUser(state)[userId];
const selectUserDetails = createSelector(
    [selectUser, selectUserId],
    (users, user) => users[]

With selectUserDetails, only the relevant user data is accessed, minimizing unwarranted recalculations.

Managing the cache size in selectors is crucial for preventing memory bloat and optimizing performance. By default, createSelector uses a single-entry cache, but in some scenarios, increasing the cache size can be beneficial, especially when the selector is used with various arguments. To modify cache behavior, we can utilize a custom memoization function that extends the cache capacity:

import { createSelectorCreator, defaultMemoize } from '@reduxjs/toolkit';

const customMemoize = func => defaultMemoize(func, {
    maxSize: 5 // customize cache size as needed
const customCreateSelector = createSelectorCreator(customMemoize);

// Usage of customCreateSelector as an enhanced createSelector with extended cache

This adjusted memoization caches multiple results, making selectors more efficient across varying computations.

Advanced memoization also entails regulating selector complexity by decomposing cumbersome selectors into smaller, manageable ones. This decomposition facilitates precise memoization and streamlines maintenance and debugging processes. Here's how to deconstruct a complex calculation into modular selectors:

const selectComplexData = state => state.complexData;
const selectIntermediateResult = createSelector(
    complexData => performIntermediateCalculation(complexData)
const selectFinalResult = createSelector(
    intermediateResult => finalizeCalculation(intermediateResult)

This breakdown allows intermediateResult to be memoized separately, preventing needless recalculations when sources for intermediateResult remain unchanged.

A frequent coding error is to inadvertently mutate references within selectors, triggering unnecessary re-renders. To avoid this, selectors should maintain reference equality through structural sharing, allowing for the previous computation results to be reused whenever possible, as demonstrated below:

const selectAllUsers = state => state.users;
const selectAllUsersOptimized = createSelector(
    users => {
        const computedUsers =;
        return computedUsers.every((user, index) => user === users[index])
            ? users // Use the old reference
            : computedUsers; // Only return new reference if changed

function computeUserData(user) {
    // Perform necessary user data transformation while avoiding mutation
    return { ...user, computedField: computeField(user) };

In this example, selectAllUsersOptimized employs structural sharing to enhance performance.

For optimal memoization, assess how selectors correlate with anticipated state changes by re-evaluating their efficiency periodically. This ensures that selectors evolve congruent with application scaling and state mutation, thereby enhancing their longevity and agility in dynamic environments. Consistently refining the design of selectors is crucial as your application's complexity grows, ensuring they remain efficient and relevant.

createSelector in Complex State Scenarios: Modularity and Reusability

In modern web applications, particularly those that have nested or non-linear state structures, the createSelector function becomes invaluable. Consider a React-Redux application handling state for a user profile, with nested structures for biographical data, preferences, and security settings. Instead of creating monolithic selectors, createSelector encourages developers to sculpt their selectors to match the shape and complexity of the state.

For example, a simple selector for retrieving user preferences might look like this:

const selectUser = state => state.user;
const selectUserPreferences = createSelector(
    user => user.preferences

This function modularizes the state selection, abstracting the complexity of the state structure away from the components that consume it. As a result, you can readily reuse selectUserPreferences across various components, enhancing code readability and simplifying maintenance.

When dealing with more intricate scenarios, such as displaying a user's preferred theme settings only if they have certain permissions, createSelector shines by enabling the chaining of selectors. Here, chaining not only promotes reusability but also encapsulates logic like a matryoshka doll, with each selector nesting within the next.

const selectUserPermissions = createSelector(
    user => user.permissions
const selectUserTheme = createSelector(
    [selectUserPreferences, selectUserPermissions],
    (preferences, permissions) => permissions.includes('THEME_ACCESS') ? preferences.theme : defaultTheme

This pattern organizes the derivation of state within each selector function, thus enabling each layer of complexity to be individually tested and debugged without entanglement.

To further enhance modularity, developers can abstain from mapping the entire state to props in their components. Instead, by selectively mapping only the segments of the state relevant to the component's functionality, createSelector allows non-related renders to bypass the more granitic state details. This targeted approach minimizes component re-renders and extraneous computations.

Developers frequently find themselves restructuring large applications to adapt to new requirements or improve performance. In this context, createSelector provides flexibility, as developers can refactor selectors without altering the components relying on them. It reduces the impact that changes to the state shape—and the corresponding selectors—have on the overall application code base, thus adhering to the principle of least astonishment for developers both familiar and new to the code base. Consider regular scrutiny of your selectors to ensure they remain streamlined, focusing on reusability without compromising specificity.

Pitfalls and Anti-Patterns in Selector Usage

One prevalent mistake in using createSelector emerges from improper handling of output selectors. Developers often craft output selectors that do nothing more than return their inputs. This not only forfeits memoization benefits but also adds unnecessary computation. A robust output selector ought to involve logic that derives new data, contributing to the effectiveness of memoization. To illustrate, consider an output selector designed to simply return whatever it receives:

const unoptimizedSelector = createSelector(
  state => state.items,
  items => items

Instead, refine this selector to achieve its intended purpose, such as calculating the total quantity of items:

const optimizedTotalSelector = createSelector(
  state => state.items,
  items => items.reduce((total, item) => total + item.quantity, 0)

Excessive reliance on memoization can sometimes backfire, particularly when selectors are parameterized incorrectly. A common blunder is the use of non-primitive arguments in selectors, which can lead to frequent cache invalidations. Such issues typically arise when an object is passed with each invocation, creating a new reference that bypasses memoization:

// Incorrect:
const mapStateToProps = state => ({
  items: selectItemsInCategory(state, { category: 'books' })

To leverage memoization effectively, one should use primitives for argument passing, or memoize the factory arguments elsewhere:

// Correct:
const selectItemsInCategoryFactory = memoize(category => createSelector(
  state => state.items,
  items => items.filter(item => item.category === category)
const mapStateToProps = state => ({
  items: selectItemsInCategoryFactory('books')(state)

Another anti-pattern is using a global state => state input selector, which triggers recalculations whenever the state updates, undermining memoization's benefits. To enhance performance, selectors should focus on the smallest possible slice of state pertinent to the computation. Instead of a global state selector, opt for a more targeted approach:

// Incorrect:
const poorSelector = createSelector(
  state => state,
  state => computeExpensiveValue(state)

// Correct:
const efficientSelector = createSelector(
  state => state.specificSubState,
  specificSubState => computeExpensiveValue(specificSubState)

Moreover, createSelector should not be overused for simple selections. Doing so introduces unnecessary complexity without tangible performance gains. For directly accessing state properties without additional computation, simple selector functions will suffice:

// Unnecessary createSelector usage:
const complexAccess = createSelector(
  state => state.simpleValue,
  simpleValue => simpleValue

// Simplified direct selection:
const simpleAccess = state => state.simpleValue;

Lastly, as createSelector's selectors are designed to be pure functions, integrating side effects can disrupt the predictable flow, leading to unexpected behaviors. Ensure selectors are devoid of side effects and purely focus on deriving state. By adhering to these guidelines, developers can steer clear of common pitfalls, cultivating selectors that enhance performance and maintainability. Consider reflecting on the selectors in your application; are there places where they've grown too large or your input selectors too broad, inadvertently slowing down your app? How might you refactor these instances to restore or even improve their efficacy?

Evaluating useSelector Hook Versus Connect: Performance Considerations

When comparing useSelector with connect for integrating selectors within React components, a primary aspect to consider is how each approach affects performance. The useSelector hook, introduced with React Redux version 7.1.0, provides a more direct and hook-based way to map state to a component's props, which aligns with the modern functional component paradigm. In contrast, the connect HOC has long been used to bind state and dispatch to React components, but with the advent of hooks, useSelector has become more prevalent. One significant performance consideration is the frequency of re-renders. useSelector will cause a component to re-render whenever the selector's result changes, while connect can be fine-tuned with mapStateToProps and areStatesEqual to minimize re-renders.

Memory usage also differentiates useSelector from connect. The useSelector hook may lead to creating multiple selector instances if not properly memoized outside the component or improperly used within event handlers or callbacks, potentially resulting in more garbage collection overhead. The connect HOC, on the other hand, tends to encourage the definition of selectors outside component scope, which can help in managing memory usage more effectively by reducing the number of instances.

In terms of actual re-render behavior, the connect HOC is more predictable as it associates a static list of props to watch for changes, whereas useSelector may trigger more re-renders if the selector is not tightly scoped or if it is re-created on each render. Consider the following well-commented code snippet demonstrating a basic usage of useSelector:

function MyComponent(){
    // Good practice: Selector is defined outside of the component's render scope
    const selectNumOfTodos = state => state.todos.length;

    // The useSelector hook uses the selector to get the number of todos
    const numOfTodos = useSelector(selectNumOfTodos);

    // Rendering logic for the component
    return <div>Number of todos: {numOfTodos}</div>;

On the other side, here is how a similar component might be set up using connect:

// mapStateToProps connects the state to props with a pre-defined selector
const mapStateToProps = state => ({
    numOfTodos: state.todos.length

// The connect HOC then links mapStateToProps to MyComponent
const MyComponentWithConnect = connect(mapStateToProps)(MyComponent);

function MyComponent({ numOfTodos }){
    // Rendering logic for the component with props from connect
    return <div>Number of todos: {numOfTodos}</div>;

Reflecting on the example, how might different use cases in your application influence your choice between useSelector and connect? How do the trade-offs between ease of use, performance considerations, and adherence to modern React paradigms align with your development practices?

When evaluating the practical implications of useSelector versus connect, consider the complexity of the selectors involved and the specific dynamics of your components. It demands a careful balancing act to maintain performance while leveraging the advantages of the latest React features.


The article "Redux Toolkit's createSelector: Advanced Performance Optimization Techniques" explores how the createSelector function in Redux Toolkit can optimize the performance of JavaScript in modern web development. It explains how createSelector uses memoization to efficiently compute derived states, reduce unnecessary re-renders, and keep the Redux store minimal. The article also discusses memoization strategies, modularity and reusability in complex state scenarios, and common pitfalls to avoid. The key takeaway is the importance of using createSelector effectively to enhance application performance and maintainability. A challenging task for readers could be to assess their own selectors and refactor them to improve efficiency and specificity.

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