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You need to perform heavy computations on a large dataset in Node.js without blocking the main thread. Which strategy best utilizes worker threads for this task?

hard📝 Application Q8 of 15
Node.js - Worker Threads
You need to perform heavy computations on a large dataset in Node.js without blocking the main thread. Which strategy best utilizes worker threads for this task?
AAvoid worker threads and rely solely on setTimeout to defer computations
BRun all computations sequentially on the main thread using async/await
CUse a single worker thread to process the entire dataset synchronously
DDivide the dataset into chunks and assign each chunk to a separate worker thread for parallel processing
Step-by-Step Solution
Solution:
  1. Step 1: Understand worker thread usage

    Worker threads enable parallel execution of CPU-intensive tasks.
  2. Step 2: Efficient parallelization

    Splitting data into chunks and processing in multiple workers maximizes concurrency and reduces blocking.
  3. Step 3: Evaluate options

    Divide the dataset into chunks and assign each chunk to a separate worker thread for parallel processing describes this approach; others either block or underutilize workers.
  4. Final Answer:

    Divide the dataset into chunks and assign each chunk to a separate worker thread for parallel processing -> Option D
  5. Quick Check:

    Chunk data and process in parallel workers for best performance [OK]
Quick Trick: Split data and use multiple workers for parallel processing [OK]
Common Mistakes:
  • Running heavy tasks sequentially on main thread
  • Using only one worker thread for all data
  • Relying on setTimeout to avoid blocking

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