Request memoization in NextJS - Performance & Optimization

Performance: Request memoization

MEDIUM IMPACT

Request memoization improves page load speed by avoiding repeated data fetching and reduces server load and client wait times.

Fetching data multiple times for the same request in Next.js components

NextJS

export async function getServerSideProps(context) {
  const res = await fetch('https://api.example.com/data');
  const data = await res.json();
  return { props: { data1: data, data2: data } };
}

Fetch data once and reuse it, reducing network calls and server load.

📈 Performance GainSingle network request; halves data fetching time and server processing.

Fetching data multiple times for the same request in Next.js components

NextJS

export async function getServerSideProps(context) {
  const res1 = await fetch('https://api.example.com/data');
  const data1 = await res1.json();
  const res2 = await fetch('https://api.example.com/data');
  const data2 = await res2.json();
  return { props: { data1, data2 } };
}

Fetching the same data twice causes duplicate network requests, increasing load time and server work.

📉 Performance CostBlocks rendering until both fetches complete; doubles network latency and server processing.

Performance Comparison

Pattern	DOM Operations	Reflows	Paint Cost	Verdict
Duplicate fetch calls	Multiple fetch triggers	Multiple reflows due to delayed data	Higher paint cost from repeated updates	[X] Bad
Single fetch with memoization	Single fetch triggers	Single reflow after data arrives	Lower paint cost with stable data	[OK] Good

Rendering Pipeline

Request memoization reduces the number of network requests, which decreases blocking time during the critical rendering path. It minimizes layout recalculations and repaints caused by delayed data arrival.

→Network

→JavaScript Execution

→Layout

→Paint

⚠️ BottleneckNetwork latency and JavaScript execution waiting on fetch responses

Core Web Vital Affected

LCP

Request memoization improves page load speed by avoiding repeated data fetching and reduces server load and client wait times.

Optimization Tips

1Always cache or reuse identical fetch requests to reduce network overhead.

2Avoid multiple fetch calls for the same data within the same render cycle.

3Use memoization to improve Largest Contentful Paint by speeding data availability.

Performance Quiz - 3 Questions

What is the main performance benefit of request memoization in Next.js?

A Increases the number of server requests for better caching

B Reduces duplicate network requests and speeds up page load

C Delays rendering until all requests complete

D Adds extra JavaScript to bundle size

DevTools: Network

How to check: Open DevTools, go to Network tab, reload page, and look for repeated identical requests to the same URL.

What to look for: Multiple identical fetch requests indicate missing memoization; a single request reused is optimal.

Practice

1. What is the main purpose of request memoization in Next.js?

easy

A. To increase the number of server requests

B. To save repeated fetches by remembering previous results

C. To disable caching for all requests

D. To make fetch requests slower

Solution

1. Step 1: Understand request memoization concept

   Request memoization stores the results of previous fetches to avoid repeating the same network calls.

2. Step 2: Identify the effect on performance

   By remembering previous results, it reduces server load and speeds up response times.

3. Final Answer:

   To save repeated fetches by remembering previous results -> Option B

4. Quick Check:

   Request memoization = Save repeated fetches [OK]

Hint: Memoization means remembering past results to avoid repeats [OK]

Common Mistakes:

• Thinking memoization increases server requests
• Confusing memoization with disabling cache
• Assuming memoization slows down fetches

2. Which of the following is the correct way to memoize a fetch function in Next.js using the built-in cache?

easy

A. const cachedFetch = fetch.cache('/api/data')

B. const cachedFetch = async cache(() => fetch('/api/data'))

C. const cachedFetch = cache(async () => await fetch('/api/data'))

D. const cachedFetch = cache.fetch('/api/data')

Solution

1. Step 1: Recall Next.js cache usage

   Next.js provides a cache function that wraps async functions to memoize their results.

2. Step 2: Check correct syntax

   The correct syntax is cache(async () => await fetch(...)), which matches const cachedFetch = cache(async () => await fetch('/api/data')).

3. Final Answer:

   const cachedFetch = cache(async () => await fetch('/api/data')) -> Option C

4. Quick Check:

   cache wraps async fetch function = const cachedFetch = cache(async () => await fetch('/api/data')) [OK]

Hint: Use cache() to wrap async fetch functions correctly [OK]

Common Mistakes:

• Placing cache inside async incorrectly
• Using non-existent fetch.cache method
• Calling cache.fetch which does not exist

3. Given this code snippet in Next.js, what will be logged on the second call to getData()?

import { cache } from 'react';

const getData = cache(async () => {
  console.log('Fetching data');
  return await fetch('/api/data').then(res => res.json());
});

await getData();
await getData();

medium

A. Fetching data

B. Fetching data
Fetching data

C. No output

D. Error: cache is not a function

Solution

1. Step 1: Understand cache behavior on repeated calls

   The cache function memoizes the async function result, so the fetch and console.log run only once.

2. Step 2: Analyze the second call effect

   On the second call, the cached result is returned without running the function body again, so no console.log output.

3. Final Answer:

   Fetching data -> Option A

4. Quick Check:

   cache memoizes, so console.log runs once [OK]

Hint: cache runs function once, returns cached result later [OK]

Common Mistakes:

• Expecting console.log to run twice
• Thinking cache disables function execution
• Confusing cache with normal fetch calls

4. Identify the error in this Next.js memoized fetch code:

import { cache } from 'react';

const getData = async cache(() => {
  return await fetch('/api/data').then(res => res.json());
});

medium

A. TypeError: cache is not a function

B. RuntimeError: fetch is not defined

C. No error, code works fine

D. SyntaxError: 'cache' must wrap the async function, not be called inside it

Solution

1. Step 1: Check cache usage syntax

   The cache function must wrap the async function, not be called inside the async declaration.

2. Step 2: Identify the syntax mistake

   Writing async cache(() => ...) is invalid syntax; it should be cache(async () => ...).

3. Final Answer:

   SyntaxError: 'cache' must wrap the async function, not be called inside it -> Option D

4. Quick Check:

   cache wraps async function syntax = SyntaxError: 'cache' must wrap the async function, not be called inside it [OK]

Hint: cache wraps async function, not inside async declaration [OK]

Common Mistakes:

• Placing async before cache call incorrectly
• Assuming fetch is undefined without context
• Thinking cache is not imported

5. You want to memoize a fetch function in Next.js that depends on a dynamic URL parameter. Which approach correctly memoizes requests per unique URL?

hard

A. Use cache with a function that takes the URL as argument and memoizes internally

B. Use a single cached function without parameters for all URLs

C. Memoize only the first URL and ignore others

D. Do not use cache; fetch every time for dynamic URLs

Solution

1. Step 1: Understand memoization with parameters

   To memoize requests per unique URL, the cache must consider the URL argument to store separate results.

2. Step 2: Use cache with parameterized function

   Wrapping a function that takes URL as input with cache memoizes each unique URL separately.

3. Final Answer:

   Use cache with a function that takes the URL as argument and memoizes internally -> Option A

4. Quick Check:

   cache with parameters memoizes per input [OK]

Hint: Memoize functions with parameters to cache per input [OK]

Common Mistakes:

• Using single cache for all URLs causing wrong data
• Ignoring memoization for dynamic inputs
• Assuming cache disables dynamic fetching