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Reflection brings memory overhead and performance loss: Reflection stores type information in the reflect.Type structure, resulting in memory overhead. Reflection operations are slower than direct access to type information, increasing performance overhead. Practical examples demonstrate the memory overhead and performance differences of reflection.
Reflection is a powerful tool that allows you to dynamically inspect and manipulate runtime type information. However, reflection also brings some memory overhead and performance losses.
Reflection stores type information in a reflect.Type
structure, which contains all necessary information about the type, such as fields, methods, and implementations Interface. Each reflect.Type
structure requires additional memory overhead, which may become significant when dealing with large numbers of types.
Reflected operations are generally slower than direct access to type information. This is because reflection involves an extra layer of indirection, which incurs a performance overhead. For example, getting the field values of a structure through reflection is slower than accessing the field values directly.
The following code example demonstrates the memory overhead and performance penalty of reflection:
package main import ( "reflect" "runtime" "testing" ) type Example struct { Field1 string Field2 int } func BenchmarkReflectType(b *testing.B) { e := Example{} for i := 0; i < b.N; i++ { _ = reflect.TypeOf(e) } } func BenchmarkDirectType(b *testing.B) { e := Example{} for i := 0; i < b.N; i++ { _ = reflect.Type(e) } }
Running this benchmark will show the use of reflect.TypeOf
The performance difference between getting the reflected value of a type and getting the type directly.
Reflection is a useful tool, but it will bring some memory overhead and performance losses. When using reflection, be sure to weigh these overheads against the benefits.
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