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Best practices and principles of golang function concurrency control

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Release: 2024-04-24 10:12:01
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Best practices for concurrency control in Go language functions: Limit concurrency: Use mutexes or semaphores to avoid data races. Using channels: Control asynchronous communication between functions through channels. Use goroutine groups: ensure resources are not released until all goroutines have completed. Exception handling: Safely handle exceptions to prevent unexpected termination. Practical example: using goroutine groups and channels to query the database in parallel while limiting concurrency and handling exceptions.

Best practices and principles of golang function concurrency control

The best practices and principles of Go language function concurrency control

In the Go language, function concurrency control is important for managing concurrent execution function is crucial. Listed below are some best practices and principles to help you control function concurrency effectively:

Limit Concurrency

  • Use sync. Mutex or sync.RWMutex to limit concurrent access to shared resources and avoid data competition.
  • Use Semaphore or RateLimiter to adjust the execution rate of concurrent functions to prevent system overload.

Use channels

  • Use channels to control concurrency between functions. Channels provide a buffering mechanism that allows functions to communicate asynchronously.
  • Use the select statement to monitor multiple channels to implement selective wait or timeout operations.

Use goroutine group

  • Use sync.WaitGroup or context.Context to wait for a Group goroutine completed.
  • Ensure that shared resources are not released or critical operations are performed before all goroutines are completed.

Exception handling

  • Ensure that the function can safely handle exceptions, such as panic.
  • Use error handling mechanism to return and report errors to prevent unexpected termination of concurrent execution.

Practical case: Concurrent query of database

Consider a scenario of querying multiple databases in parallel. We can implement this efficiently using the Go language and best practices:

package main

import (
    "context"
    "database/sql"
    "fmt"
    "sync"
)

func main() {
    db1 := connectToDB1()
    db2 := connectToDB2()

    var wg sync.WaitGroup
    resultCh := make(chan []string)

    wg.Add(2)
    go queryDB(db1, &wg, resultCh)
    go queryDB(db2, &wg, resultCh)

    go func() {
        // 等待 goroutine 完成并合并结果
        wg.Wait()
        close(resultCh)
    }()

    for results := range resultCh {
        fmt.Println(results)
    }
}

func queryDB(db *sql.DB, wg *sync.WaitGroup, resultCh chan<- []string) {
    defer wg.Done()
    rows, err := db.Query("SELECT * FROM table")
    if err != nil {
        log.Fatal(err)
    }
    var results []string
    for rows.Next() {
        var name string
        if err := rows.Scan(&name); err != nil {
            log.Fatal(err)
        }
        results = append(results, name)
    }
    rows.Close()
    resultCh <- results
}
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This code demonstrates how to use goroutine groups and channels to query a database in parallel while limiting concurrency and handling exceptions.

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