Long-running operations (async responses) in Rest API - Time & Space Complexity

Time Complexity: Long-running operations (async responses)

O(n)

Understanding Time Complexity

When dealing with long-running operations in APIs, it's important to understand how the time to complete grows as the work increases.

We want to know how waiting for async responses affects the total time as input size changes.

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

async function fetchData(ids) {
  const results = [];
  for (const id of ids) {
    const response = await fetch(`/api/data/${id}`);
    const data = await response.json();
    results.push(data);
  }
  return results;
}

This code fetches data for each id one after another, waiting for each response before starting the next.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: Fetching data from the API for each id.
• How many times: Once per id in the input list, sequentially.

How Execution Grows With Input

Each id causes a separate fetch call that waits for a response before moving on.

Input Size (n)	Approx. Operations
10	10 fetch calls, done one after another
100	100 fetch calls, each waiting for the previous
1000	1000 fetch calls, total time grows with each call

Pattern observation: Total time grows roughly in direct proportion to the number of ids because calls happen one after another.

Final Time Complexity

Time Complexity: O(n)

This means the total time grows linearly with the number of requests because each waits for the previous to finish.

Common Mistake

[X] Wrong: "Since the calls are async, all requests happen at the same time, so time stays constant regardless of input size."

[OK] Correct: In this code, each fetch waits for the previous one to finish before starting, so calls happen one after another, not in parallel.

Interview Connect

Understanding how async calls affect total time helps you design APIs and clients that handle many requests efficiently and shows you can reason about real-world performance.

Self-Check

What if we changed the code to start all fetch calls at once and then wait for all to finish? How would the time complexity change?

Practice

1. What is the main purpose of using long-running operations with async responses in REST APIs?

easy

A. To make the server process all requests instantly.

B. To let clients start a task and check its progress later without waiting.

C. To block the client until the task finishes.

D. To avoid using URLs for task status.

Solution

1. Step 1: Understand client-server interaction in async operations

   Clients start a task and receive a URL to check progress later, avoiding waiting.

2. Step 2: Identify the benefit of async responses

   This approach keeps apps responsive and user-friendly by not blocking clients.

3. Final Answer:

   To let clients start a task and check its progress later without waiting. -> Option B

4. Quick Check:

   Async responses = clients check progress later [OK]

Hint: Async means start task, check later URL [OK]

Common Mistakes:

• Thinking server processes all requests instantly
• Assuming client waits for task completion
• Ignoring the use of status URLs

2. Which HTTP status code is typically returned immediately by a REST API to indicate a long-running operation has started asynchronously?

easy

A. 200 OK

B. 404 Not Found

C. 202 Accepted

D. 500 Internal Server Error

Solution

1. Step 1: Recall HTTP status codes for async start

   202 Accepted means the request is accepted but processing is not complete yet.

2. Step 2: Compare with other codes

   200 OK means completed, 404 means missing resource, 500 means server error.

3. Final Answer:

   202 Accepted -> Option C

4. Quick Check:

   Async start = 202 Accepted [OK]

Hint: 202 means accepted but not done yet [OK]

Common Mistakes:

• Using 200 OK for async start
• Confusing 404 with async status
• Assuming 500 means task started

3. Given this REST API response after starting a long-running task:

{"status": "accepted", "status_url": "/tasks/123/status"}

What should the client do next to get the task result?

medium

A. Send a DELETE request to /tasks/123/status to cancel the task.

B. Send a POST request to /tasks/123/status to get the result.

C. Wait for the server to push the result automatically.

D. Send a GET request to /tasks/123/status to check progress.

Solution

1. Step 1: Identify the purpose of status_url

   The status_url is provided for the client to check the task progress or result.

2. Step 2: Determine correct HTTP method to check status

   GET requests are used to retrieve information, so client should GET the status URL.

3. Final Answer:

   Send a GET request to /tasks/123/status to check progress. -> Option D

4. Quick Check:

   Check progress = GET status URL [OK]

Hint: Use GET on status URL to check progress [OK]

Common Mistakes:

• Using POST instead of GET to check status
• Expecting server to push result without polling
• Using DELETE to check or cancel unintentionally

4. A developer wrote this code to start a long-running task and check its status:

response = start_task()
if response.status_code == 202:
    status_url = response.json()["status_url"]
    result = requests.post(status_url)
    print(result.json())

What is the error in this code?

medium

A. Using POST instead of GET to check the status URL.

B. Not checking if status_url exists in the response.

C. Not handling the case when status_code is not 202.

D. Printing result without parsing JSON.

Solution

1. Step 1: Review HTTP method used to check status

   The code uses POST to check status, but status URLs require GET requests.

2. Step 2: Confirm other parts of code

   Checking status_url existence and status_code handling are good practices but not the main error here.

3. Final Answer:

   Using POST instead of GET to check the status URL. -> Option A

4. Quick Check:

   Status check = GET, not POST [OK]

Hint: Status check always uses GET method [OK]

Common Mistakes:

• Using POST instead of GET for status check
• Ignoring missing status_url key
• Not handling unexpected status codes

5. You want to design a REST API endpoint for a long-running image processing task. Which approach best follows async response principles?

hard

A. Client POSTs image, server returns 202 Accepted with a status URL; client polls status URL until done.

B. Client POSTs image, server processes image immediately and returns 200 OK with result.

C. Client POSTs image, server returns 404 Not Found if task is slow.

D. Client POSTs image, server holds connection open until processing finishes.

Solution

1. Step 1: Understand async response design

   Server accepts task, returns 202 with status URL for client to poll progress.

2. Step 2: Evaluate other options

   Immediate processing (200 OK) blocks client; 404 is wrong status; holding connection open blocks client.

3. Final Answer:

   Client POSTs image, server returns 202 Accepted with a status URL; client polls status URL until done. -> Option A

4. Quick Check:

   Async design = 202 + status URL + polling [OK]

Hint: Async = 202 + status URL + client polls [OK]

Common Mistakes:

• Returning 200 OK immediately for slow tasks
• Using 404 for slow processing
• Keeping connection open until done