Adjusting Go's garbage collector (GC) can be achieved through the following steps: 1. Understand the current GC behavior, analyze the GC frequency, pause time and heap size changes through the GODEBUG=gctrace=1 and pprof tools; 2. Adjust the GOGC parameters to control the GC frequency, such as set to 200 to reduce the number of GCs to increase throughput, or set to 50 to increase the recycling frequency to reduce latency; 3. Use GOMEMLIMIT to control the heap memory limit (Go 1.19), such as set to 8GB to limit overall memory usage; 4. Reduce object allocation, reduce GC pressure by multiplexing objects in sync.Pool, avoiding the creation of variables in loops, and pre-allocating slice capacity. The core of tuning is to understand application characteristics and select appropriate strategies. Reducing allocation is often more effective than parameter adjustment.
Adjusting Go's garbage collector (GC) does not actually require too complicated operations, especially when the default configuration is already very efficient. However, if your application has special needs, such as latency sensitivity, memory limitation or high throughput requirements, proper tuning of GC can bring real benefits.
Below are some common scenarios and corresponding tuning suggestions.
Understand current GC behavior
Before doing any tuning, you must first understand the current GC behavior of your program. It can be done by:
- Check out
GODEBUG=gctrace=1output, which prints statistics after each GC cycle is over. - Use the pprof tool to analyze GC frequency, pause time (STW), and heap size changes.
- Observe whether the GC pause affects your service response delay.
This data can tell you whether the GC is currently a performance bottleneck and whether further tuning is necessary.
Adjust GOGC parameters to control GC frequency
Go's GC is designed throughput first by default, but you can control its behavior by setting the environment variable GOGC .
-
GOGC=100is the default value, indicating that the next round of GC is triggered when the heap grows to 100% after the last GC. - If you want to reduce the number of GCs and increase the throughput, you can set it to a higher value, such as
GOGC=200. - If you pay more attention to low latency, you can lower this value, such as
GOGC=50, so that GC is more frequent, but there is less data recycled each time.
Note: This parameter only affects the trigger frequency of concurrent GC in the background and will not significantly change the operating mechanism of GC.
Controlling heap memory upper limit (Go 1.19)
Starting from Go 1.19, an experimental memory limiting function ( GOMEMLIMIT ) has been introduced, allowing you to set the maximum memory used by the entire process (including heap, stack, code segment, etc.).
- Setting method:
GOMEMLIMIT=8589934592(unit is bytes, for example 8GB). - Function: Prevent memory usage from growing unlimitedly, especially suitable for container environments or resource-constrained deployment scenarios.
- Notes:
- It is not recommended to set it too tightly, otherwise it may lead to frequent GC or OOM.
- It can be used with
GOGC=offto allow GC to be scheduled entirely according to memory restrictions.
This approach is suitable for services that are sensitive to total memory, such as microservices or edge computing nodes.
Reduce object allocation and fundamentally reduce GC pressure
Another idea of tuning GC is to "not create problems" - reduce unnecessary memory allocation:
- Reuse objects, such as using sync.Pool to cache temporary objects.
- Avoid creating temporary variables in loops.
- Try to preallocate slice capacity to avoid dynamic expansion.
- Use object pools to manage connections, buffers and other resources.
You can use go build -gcflags=-m to view escape analysis to find out which variables are allocated to the heap.
Basically that's it. Tuning Go's GC does not require too many fancy operations. The key is to understand the behavioral characteristics of the application and then choose the right strategy. Sometimes, reducing allocations can solve the problem better than adjusting parameters.
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