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How to Avoid Deadlocks When Using Goroutines for Parallel Processing and Result Gathering?

Barbara Streisand
Barbara StreisandOriginal
2024-11-07 02:09:03484browse

How to Avoid Deadlocks When Using Goroutines for Parallel Processing and Result Gathering?

Understanding Goroutines for Parallel Processing and Result Gathering

Background

Your goal is to utilize goroutines in Go to process items in parallel, collecting their results into a slice. However, you encountered a perplexing deadlock error: "all goroutines are asleep - deadlock!"

Solution

The error stems from two issues in your code:

  1. Delayed Collection: You're waiting for all goroutines to complete before collecting results, which is incorrect.
  2. Premature Channel Closure: The channel is closed after the result collection loop finishes, prematurely terminating the iteration.

Revised Code

To rectify these issues, introduce a goroutine that asynchronously closes the channel when the workers finish:

for i, line := range contents {
  wg.Add(1)
  go newSample(line, *replicatePtr, *timePtr, sampleChan, &wg)
}

go func() {
  wg.Wait()
  close(sampleChan)
}()

for s := range sampleChan {
  ..
}

Explanation

  • Asynchronous Channel Closure: The anonymous goroutine closes the channel after all workers have completed, avoiding premature loop termination.
  • Style Recommendation: Consider using a synchronous helper function (newSample) that doesn't take the channel and waitgroup, simplifying the code and enhancing testability.

Refactoring for Efficiency

If you need a fixed number of workers for optimal efficiency, refactor the code as follows:

for i, line := range contents {
  wg.Add(1)
  go func(line string) {
    defer wg.Done()
    sampleChan <- newSample(line, *replicatePtr, *timePtr)
  }(line)
}

This keeps the concurrency primitives together and simplifies refactoring for various concurrency patterns.

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