Detailed explanation of Go language and usage scenarios

In Go,It's oneConcurrently safeMapping structure, specially used to process key-value pair data in high concurrency scenarios. Its concurrency safety is throughInternal implementation mechanismto ensure that, rather than relying on external lock mechanisms (such asor) to manually protect the operation.

The principle of concurrent security implementation

A more complex data structure and operation strategy are adopted to achieve concurrent security. Its core design can be divided into the following aspects:

1. Read and write separation mechanism

The internal structure is throughRead and write separationImplemented mainly consists of two parts:

• Read-only part (read map): Used to store stable data. The read operation is mainly carried out from this read-only part to avoid the use of locks.
• Dirty map: When the data is modified (write or deleted), it will be moved to the dirty data area, and locked while writing to ensure concurrency security.

2. Quickly read paths

• Lockless reading: If the data already exists inread map(i.e. stable data), read operation does not require locking, which makesThe read operation is very efficient.
• Copy on writing: When the data isread mapWhen it does not exist, it may exist indirty mapmiddle. At this time, you need to upgrade the lock and get it fromdirty mapRead or write data.

3. Lock protection during writing

• When writing to (StoreorDelete)hour,Will be heredirty mapPerform the operation. Write operations are locked to ensure security during concurrent writes.
• Each time you write,All checkread mapanddirty mapWhether the data between them needs to be synchronized (such as when the amount of data exceeds a certain threshold), and clean and migrate the dirty data parts.

4. Lazy Synchronization

When read operations are frequent,Some dirty data will be gradually migrated toread map, thereby reducing the dependence of read operations on locks. ThisDelay synchronizationThe strategy ensures that read operations can avoid lock competition as much as possible, thereby improving read performance.

5. Atomic operation

Partial operations (such asLoadOrStore、LoadAndDeleteetc.) Atomic operations are adopted. Their implementation uses the underlying atomicity check and assignment operations to ensure that these operations can remain consistent in a concurrent environment.

Key Operation Instructions

• Read operation (Load)：

  • First fromread mapRead in  , if found, return directly.
  • Ifread mapNot found in  , then try todirty mapRead in  and may trigger a lock operation.

• Write operation (Store)：

  • The write operation will be lockedto ensure that thedirty mapSafe writing.
  • If dirty data becomes more or is written frequently, it may triggerread mapSynchronization, migrate some dirty data toread map。

• Delete operation (Delete)：

  • The deletion operation will also be locked and deleteddirty mapdata in  .

• Batch operation (Range)：

  • RangeOperation traversalAll data in it ensures that there is no concurrent conflict during the traversal.

Code Example

package main

import (
    "fmt"
    "sync"
)

func main() {
    var m 

    // Write data    ("foo", 42)
    ("bar", 100)

    // Read data    value, ok := ("foo")
    if ok {
        ("foo:", value)
    }

    // Delete data    ("foo")

    // Use Range to traverse all elements    (func(key, value interface{}) bool {
        (key, value)
        return true
    })
}

Advantages

• High reading performance: Performance is very excellent in scenarios where more reads and less writes, becauseread mapThere is no need to add locks when reading, reducing lock competition.
• Automatic concurrency control：There is no need to manually manage lock mechanisms, which reduces the complexity of writing concurrent security code.
• Suitable for high concurrency scenarios: Especially in the case of large amounts of reading,The performance is better than that of traditionalmap + The plan.

When to use

• Read more and write less scenarios: When concurrent access is mainly read operation and write operation is small,The read and write separation mechanism makes it highly performant.
• Requires simple concurrent access: When concurrent access is requiredmapand do not want to manually manage locks,It is a very convenient tool.

When not to use

• Very frequent writing operations：Locking is required in writing operations. If the write operations account for a high proportion, it may not be as good as the traditional way of manually locking.mapThe solution is efficient.

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