


What are the key differences between sync.Pool and simply creating objects as needed?
Jun 04, 2025 pm 04:33 PMThe biggest difference between sync.Pool and directly creating objects is the difference in performance optimization goals, which are mainly reflected in memory allocation, life cycle management and applicable scenarios. 1. In terms of memory allocation, directly create objects to frequently allocate and release memory, increasing GC pressure, while sync.Pool reduces the number of heap memory allocations by multiplexing objects and reduces the burden on GC. 2. In life cycle management, the objects created directly are controlled by the developer, while the objects in the Pool are automatically cleaned by the system during GC, which is not suitable for saving the persistent state. 3. Different applicable scenarios. sync.Pool is suitable for frequent creation of temporary objects with high concurrency and high initialization costs, but is not suitable for long-term holding of states or small objects and unconfirmed performance bottlenecks. 4. Usage techniques include unifying the object types in the pool, initializing using New fields, judging the type after obtaining, and cleaning the status before putting it back, ensuring reasonable and efficient use of Pool.
The biggest difference between sync.Pool
in Go and creating objects directly is that the performance optimization goals are different . If you frequently create and destroy temporary objects (such as buffers, structure instances, etc.) in your program, using sync.Pool
can effectively reduce garbage collection (GC) pressure, thereby improving performance.
1. Memory allocation and GC pressure
When you need an object directly new or make, for example:
buf := make([]byte, 1024)
This can lead to frequent memory allocation and release, especially in high concurrency scenarios. These temporary objects will be quickly created and discarded, turning into short-lived "garbage", increasing the burden on GC.
sync.Pool
provides an object multiplexing mechanism . It allows you to take an existing object from the pool and put it back after using it, avoiding reassignment every time:
buf := pool.Get().([]byte) // Use buf pool.Put(buf)
The benefit of doing this is: it reduces the number of heap memory allocations and reduces the workload of GC .
2. Different life cycle management methods
- Objects created directly : The life cycle is controlled by you, and as long as it is no longer referenced, it will be recycled in the next GC.
- Objects in sync.Pool : Their life cycle is not controlled by you. Pool will automatically clean up the contents in it at appropriate times, such as clearing all objects after each GC.
This means:
-
sync.Pool
is not suitable for saving states that need to be persisted. - If the Pool is empty, you need to initialize a new object yourself.
- Pool objects may disappear at any time and cannot be relied on to exist.
3. Different performance scenarios
Not all cases are suitable for using sync.Pool
. The following are several common applicable scenarios:
? Recommended use of sync.Pool
:
- Need to frequently create and destroy temporary objects (such as buffers, JSON decoders, etc.)
- Object creation costs are high (such as large chunks of memory or complex initialization)
- High concurrency, high GC pressure
? Deprecated use cases:
- Objects need to hold state for a long time
- The object itself is very small and cheap (such as small structures, int types, etc.), which will increase maintenance overhead
- Not sure if there is really a performance bottleneck, do benchmark tests first
4. Actual usage skills
There are several details to pay attention to when using sync.Pool
:
- The object types in the pool must be unified, usually operated through
.Get()
and.Put()
. - Initialization can use the
New
function field, such as:
var pool = sync.Pool{ New: func() interface{} { return make([]byte, 1024) }, }
- After obtaining the object, you must judge the type (if type assertion is used) to prevent errors.
- Make sure the state is clean before putting back the object and do not leave the data you used last time.
Basically that's it. Rational use of sync.Pool
can significantly reduce GC pressure, but you should also pay attention to its limitations and scope of application.
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The biggest difference between sync.Pool and directly creating objects is the difference in performance optimization goals, which are mainly reflected in memory allocation, life cycle management and applicable scenarios. 1. In terms of memory allocation, directly create objects to frequently allocate and release memory, increasing GC pressure, while sync.Pool reduces the number of heap memory allocations by multiplexing objects and reduces the burden on GC. 2. In terms of life cycle management, the objects created directly are controlled by the developer, while the objects in the Pool are automatically cleaned by the system during GC, which is not suitable for saving the persistent state. 3. Different applicable scenarios. sync.Pool is suitable for frequent creation of temporary objects with high concurrency and high initialization costs, but is not suitable for long-term holding of states or small objects and unconfirmed performance bottlenecks. 4. Usage skills

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