优化

上一次实验 代码写的较为随意，本次穷尽所学，优化了一把，

不过果然还是没 比过 Dapper aot， 虽然没使用 Interceptor， 但理论上其优化不该有这么大差距

知识差距不少呀，都看不懂 Dapper aot 利用了什么姿势领先， 有大神们能教教吗？

优化点

减少类型判断

提前 做类型判断，并在生成时利用 switch case 减少判断

之前

 var needConvert = typeof(string) != reader.GetFieldType(i);
s.Add((d,r) => d.Name = DBExtensions.ReadToString(r,j,needConvert));

之后

     switch (name)
    {
        
    case "age":
        s.Add(type == typeof(int) ? 1 : 2); 
        break;


    switch (ss[j])
    {
        
    case 1:
        d.Age = EntitiesGenerator.ReadToInt32Nullable(reader,j);
        break;
    case 2:
        d.Age = EntitiesGenerator.ReadToInt32NullableConvert(reader,j);
        break;

避免生成委托

去除委托生成使用

之前

var s = new List<Action<BenchmarkTest.Dog, IDataReader>>(reader.FieldCount);
for (int i = 0; i < reader.FieldCount; i++)
{
    var j = i;
    switch (reader.GetName(j).ToLower())
    {
        
        case "age": 
        {
            // int?
            
            var needConvert = typeof(int) != reader.GetFieldType(i);
            s.Add((d,r) => d.Age = DBExtensions.ReadToInt32Nullable(r,j,needConvert));
             
        }
        break;
        case "name": 
        {
            // string
            
            var needConvert = typeof(string) != reader.GetFieldType(i);
            s.Add((d,r) => d.Name = DBExtensions.ReadToString(r,j,needConvert));
             
        }
        break;
        case "weight": 
        {
            // float?
            
            var needConvert = typeof(float) != reader.GetFieldType(i);
            s.Add((d,r) => d.Weight = DBExtensions.ReadToFloatNullable(r,j,needConvert));
             
        }
        break;
        default:
            break;
    }
}
while (reader.Read())
{
    var d = new BenchmarkTest.Dog();
    foreach (var item in s)
    {
        item?.Invoke(d,reader);
    }
    yield return d;
}

之后

var s = new List<int>(reader.FieldCount);
for (int i = 0; i < reader.FieldCount; i++)
{
    var name = reader.GetName(i).ToLower();
    var type = reader.GetFieldType(i);
    switch (name)
    {
        
    case "age":
        s.Add(type == typeof(int) ? 1 : 2); 
        break;

    case "name":
        s.Add(type == typeof(string) ? 3 : 4); 
        break;

    case "weight":
        s.Add(type == typeof(float) ? 5 : 6); 
        break;

        default:
            break;
    }
}
ss = s.ToArray();

var d = new BenchmarkTest.Dog();
for (int j = 0; j < ss.Length; j++)
{
    switch (ss[j])
    {
        
    case 1:
        d.Age = EntitiesGenerator.ReadToInt32Nullable(reader,j);
        break;
    case 2:
        d.Age = EntitiesGenerator.ReadToInt32NullableConvert(reader,j);
        break;

    case 3:
        d.Name = EntitiesGenerator.ReadToString(reader,j);
        break;
    case 4:
        d.Name = EntitiesGenerator.ReadToStringConvert(reader,j);
        break;

    case 5:
        d.Weight = EntitiesGenerator.ReadToFloatNullable(reader,j);
        break;
    case 6:
        d.Weight = EntitiesGenerator.ReadToFloatNullableConvert(reader,j);
        break;

        default:
            break;
    }
}

添加 reader 字段判断缓存

添加缓存，减少重复生成

   var h = reader.GetColumnHash();
   if (!tokenCache.TryGetValue(h, out var ss))
   {
       var s = new List<int>(reader.FieldCount);
       for (int i = 0; i < reader.FieldCount; i++)

结果

BenchmarkDotNet v0.13.12, Windows 10 (10.0.19045.4651/22H2/2022Update)
Intel Core i7-10700 CPU 2.90GHz, 1 CPU, 16 logical and 8 physical cores
.NET SDK 9.0.100-preview.5.24307.3
  [Host]     : .NET 8.0.6 (8.0.624.26715), X64 RyuJIT AVX2
  DefaultJob : .NET 8.0.6 (8.0.624.26715), X64 RyuJIT AVX2

Method	Categories	Mean	Error	StdDev	Ratio	RatioSD	Gen0	Gen1	Gen2	Allocated	Alloc Ratio
SourceGeneratorMappingFirst	1	434.7 ns	8.67 ns	7.69 ns	0.84	0.02	0.0401	0.0396	-	336 B	1.20
SetClassFirst	1	516.8 ns	9.86 ns	10.55 ns	1.00	0.00	0.0334	0.0324	0.0019	280 B	1.00
DapperMappingFirst AOT	1	1,333.4 ns	2.49 ns	2.33 ns	2.58	0.06	0.0324	-	-	280 B	1.00
DapperMappingFirst	1	1,421.4 ns	3.08 ns	2.88 ns	2.84	0.12	0.0496	-	-	416 B	1.49
SetClass	1000	8,139.8 ns	130.22 ns	115.43 ns	1.00	0.00	6.7902	1.6937	-	56840 B	1.00
DapperMapping AOT	1000	16,373.8 ns	275.34 ns	244.08 ns	2.01	0.05	6.7749	0.9460	-	56840 B	1.00
SourceGeneratorMapping	1000	20,911.5 ns	77.69 ns	60.65 ns	2.57	0.04	6.7749	1.6785	-	56896 B	1.00
DapperMapping	1000	48,707.3 ns	430.05 ns	381.23 ns	5.67	0.29	12.5122	2.0752	-	105120 B	1.85