本文参考资料
一段废话
之前我已经介绍了这个方案的名称为JsonBuilder，这套方案最大的好处在于它的灵活可扩展性上，所以我可以很方便的对他进行优化和扩展！
性能优化
JsonBuilder第一版对一般对象的是进行实时反射的，所以性能不会很好，所以我首先想到的是优化他的性能
看我前几天发表过一篇《[源码]Literacy 快速反射读写对象属性,字段》的文章，这东西的效率不错，用来代替反射正好。
我把优化后的类取名QuickJsonBuilder
在继承JsonBuilder的基础上,我仅仅需要重写一个方法
public class QuickJsonBuilder : JsonBuilder
{
protected override void AppendOther(object obj)
{
Literacy lit = new Literacy(obj.GetType());
string fix = "";
Buff.Append('{');
foreach (var p in lit.Property)
{
Buff.Append(fix);
AppendKey(p.Name, false);
AppendObject(p.GetValue(obj));
fix = ',';
}
Buff.Append('}');
}
}
像这样我很简单的将原来的实时反射改成了Literacy
但是这样显然并不能保证性能,所以我还要加一个缓存
static Dictionary<Type, Literacy> _LitCache = new Dictionary<Type, Literacy>(); protected override void AppendOther(object obj)
{
Literacy lit;
Type type = obj.GetType(); if (_LitCache.TryGetValue(type, out lit) == false)
{
lock (_LitCache)
{
if (_LitCache.TryGetValue(type, out lit) == false)
{
lit = new Literacy(type);
_LitCache.Add(type, lit);
}
}
} string fix = "";
Buff.Append('{');
foreach (var p in lit.Property)
{
Buff.Append(fix);
AppendKey(p.Name, false);
AppendObject(p.GetValue(obj));
fix = ',';
}
Buff.Append('}');
}
缓存本身是全局静态的,所以为了防止多线程并发的问题,特别加了锁
再为了它能性能能够好上那么一点点(更多的是为了自己的强迫症吧....),再修改一些地方
static Dictionary<Type, Literacy> _LitCache = new Dictionary<Type, Literacy>(); protected override void AppendOther(object obj)
{
Literacy lit;
Type type = obj.GetType(); if (_LitCache.TryGetValue(type, out lit) == false)
{
lock (_LitCache)
{
if (_LitCache.TryGetValue(type, out lit) == false)
{
lit = new Literacy(type);
_LitCache.Add(type, lit);
}
}
} Buff.Append('{');
var ee = lit.Property.GetEnumerator(); if (ee.MoveNext())
{
AppendKey(ee.Current.Name, false);
AppendObject(ee.Current.GetValue(obj));
while (ee.MoveNext())
{
Buff.Append(',');
AppendKey(ee.Current.Name, false);
AppendObject(ee.Current.GetValue(obj));
}
} Buff.Append('}');
}
好了来看看他和他父亲在性能上的差异:
测试代码和《几个常用Json组件的性能测试》中的是一样的,
I7- 4核8线程 主频2. 内存 4G* 没有显卡 硬盘 闪迪 msata r:500m/s w:350m/s
测试机配置
不过今天在自己的电脑上运行了,感觉和昨天的测试结果的差异还是有些大的,所以还是那句话:测试结果因配置不同会有所出入,此结果仅供参考
功能扩展
相比较性能优化来说 这个要更重要一些，随着现在硬件各种不值钱，性能上的问题绝对可以在硬件上解决，而功能不足却是大多数时候我们放弃一个现成类库的原因
在这个时候一个类库是否可扩展就显得尤为重要了。
先来看一个栗子
将DataSet转为Json对象
随便来个简单个DataSet
DataTable dt1 = new DataTable("User");
dt1.Columns.Add("UID", typeof(Guid));
dt1.Columns.Add("Name", typeof(string));
dt1.Columns.Add("Birthday", typeof(DateTime));
dt1.Columns.Add("Sex", typeof(int));
dt1.Columns.Add("IsDeleted", typeof(bool));
dt1.Rows.Add(Guid.NewGuid(), "blqw", DateTime.Parse("1986-10-29"), , false);
dt1.Rows.Add(Guid.NewGuid(), "小明", DateTime.Parse("1990-1-1"), , false);
dt1.Rows.Add(Guid.NewGuid(), "小华", DateTime.Parse("1990-2-2"), , false);
DataTable dt2 = new DataTable("UserInfo");
dt2.Columns.Add("ID", typeof(int));
dt2.Columns.Add("UID", typeof(Guid));
dt2.Columns.Add("Address", typeof(string));
dt2.Columns.Add("ZipCode", typeof(int));
dt2.Rows.Add(, dt1.Rows[][], "广州", );
dt2.Rows.Add(, dt1.Rows[][], "上海", );
dt2.Rows.Add(, dt1.Rows[][], "背景", );
DataSet ds = new DataSet();
ds.Tables.Add(dt1);
ds.Tables.Add(dt2);
C#代码
再来看看每个组件的转换结果
//JsonBuilder
var a = {"User":{"columns":["UID","Name","Birthday","Sex","IsDeleted"],"rows":[["58cc6573-cb34-4d82-9343-166a3d23f518","blqw","1986-10-29 00:00:00",1,false],["c1ce
27aa-383c-4a90-b180-4f8827ef64a9","小明","1990-01-01 00:00:00",1,false],["79d24a02-7d90-4ade-80c5-93b57314f55b","小华","1990-02-02 00:00:00",0,false]]},"UserInf
o":{"columns":["ID","UID","Address","ZipCode"],"rows":[[1,"58cc6573-cb34-4d82-9343-166a3d23f518","广州",100000],[2,"c1ce27aa-383c-4a90-b180-4f8827ef64a9","上海"
,200000],[3,"79d24a02-7d90-4ade-80c5-93b57314f55b","背景",300000]]}}
//==============================================
//QuickJsonBuilder
var a = {"User":{"columns":["UID","Name","Birthday","Sex","IsDeleted"],"rows":[["58cc6573-cb34-4d82-9343-166a3d23f518","blqw","1986-10-29 00:00:00",1,false],["c1ce
27aa-383c-4a90-b180-4f8827ef64a9","小明","1990-01-01 00:00:00",1,false],["79d24a02-7d90-4ade-80c5-93b57314f55b","小华","1990-02-02 00:00:00",0,false]]},"UserInf
o":{"columns":["ID","UID","Address","ZipCode"],"rows":[[1,"58cc6573-cb34-4d82-9343-166a3d23f518","广州",100000],[2,"c1ce27aa-383c-4a90-b180-4f8827ef64a9","上海"
,200000],[3,"79d24a02-7d90-4ade-80c5-93b57314f55b","背景",300000]]}}
//==============================================
//fastJSON.NET
var a = {"User":[["f1a4f526-e723-4fb4-930e-0b5250ee3309","blqw","1986-10-29 00:00:00",1,false],["32b289a2-f116-47c3-99cc-0a7804706490","小明","1990-01-01 00:00:00"
,1,false],["a2ca668f-151e-4863-8979-d5a5e7c83a35","小华","1990-02-02 00:00:00",0,false]],"UserInfo":[[1,"f1a4f526-e723-4fb4-930e-0b5250ee3309","广州",100000],[2
,"32b289a2-f116-47c3-99cc-0a7804706490","上海",200000],[3,"a2ca668f-151e-4863-8979-d5a5e7c83a35","背景",300000]]}
==============================================
//Jayrock.Json
var a = {"User":[{"UID":"58cc6573-cb34-4d82-9343-166a3d23f518","Name":"blqw","Birthday":"1986-10-29T00:00:00.0000000+08:00","Sex":1,"IsDeleted":false},{"UID":"c1ce
27aa-383c-4a90-b180-4f8827ef64a9","Name":"小明","Birthday":"1990-01-01T00:00:00.0000000+08:00","Sex":1,"IsDeleted":false},{"UID":"79d24a02-7d90-4ade-80c5-93b573
14f55b","Name":"小华","Birthday":"1990-02-02T00:00:00.0000000+08:00","Sex":0,"IsDeleted":false}],"UserInfo":[{"ID":1,"UID":"58cc6573-cb34-4d82-9343-166a3d23f518
","Address":"广州","ZipCode":100000},{"ID":2,"UID":"c1ce27aa-383c-4a90-b180-4f8827ef64a9","Address":"上海","ZipCode":200000},{"ID":3,"UID":"79d24a02-7d90-4ade-8
0c5-93b57314f55b","Address":"背景","ZipCode":300000}]}
//==============================================
//Newtonsoft.Json
var a = {"User":[{"UID":"58cc6573-cb34-4d82-9343-166a3d23f518","Name":"blqw","Birthday":"\/Date(530899200000+0800)\/","Sex":1,"IsDeleted":false},{"UID":"c1ce27aa-3
83c-4a90-b180-4f8827ef64a9","Name":"小明","Birthday":"\/Date(631123200000+0800)\/","Sex":1,"IsDeleted":false},{"UID":"79d24a02-7d90-4ade-80c5-93b57314f55b","Nam
e":"小华","Birthday":"\/Date(633888000000+0800)\/","Sex":0,"IsDeleted":false}],"UserInfo":[{"ID":1,"UID":"58cc6573-cb34-4d82-9343-166a3d23f518","Address":"广州"
,"ZipCode":100000},{"ID":2,"UID":"c1ce27aa-383c-4a90-b180-4f8827ef64a9","Address":"上海","ZipCode":200000},{"ID":3,"UID":"79d24a02-7d90-4ade-80c5-93b57314f55b",
"Address":"背景","ZipCode":300000}]}
//==============================================
//ServiceStack.Text 报错
//TestJavaScriptSerializer 报错
各组件转换结果
我们可以很清楚的发现每个组件都有各自的转换方式,结果都不相同
- fastJSON.NET 结果中每列的"列名"丢失了
- Jayrock.Json 算是比较标准的格式了
- Newtonsoft.Json 数据格式和Jayrock.Json类似,但是时间格式太蛋疼了，造成的结果就是这个字符串直接在网页js中运行是不可能的，需要2次转换
- TestJavaScriptSerializer 报错，无法转换
- TestServiceStack 报错，无法转换
- JsonBuilder,因为是我自己写的,所以有自己的格式,我习惯将Table转换为2个部分一个columns,一个rows，因为在行数多的情况下，列名每次都重复会增加数据大小
以上几个组件的结果 可能可以通过参数设置，我不确定 但即使是参数设定，也只不过是选择几种预置的格式罢了。
这时候JsonBuilder灵活性就显现出来了
假设我现在的项目有以下需求:
- DataTable转换需要可以在,Jayrock.Json和JsonBuilder格式之间切换
- DateTime可以在 Data,Time,DataTime 3种模式中切换
- Guid要去掉中间的连字符(-)
- true,false要转换为1,0
OK 现在我需要重写4个方法 AppendDataTable(如果有必要也一起重写AppendDataView),AppendDateTime,AppendGuid,AppendBoolean
using System;
using System.Collections.Generic;
using System.Data;
using System.Linq;
using System.Text; namespace blqw
{
class MyJsonBuilder : QuickJsonBuilder
{
/// <summary> 表风格
/// <para> 默认 { columns:[colname,colname2],rows:[[x,x],[y,y]] } </para>
/// <para> 1 [{ colname:x,colname2:x },{ colname:y,colname2:y }] </para>
/// </summary>
public int TableStyle { get; set; }
/// <summary> 时间风格
/// <para> 默认 yyyy-MM-dd HH:mm:ss </para>
/// <para> 1 yyyy-MM-dd </para>
/// <para> 2 HH:mm:ss </para>
/// </summary>
public int DateTimeStyle { get; set; } protected override void AppendDateTime(DateTime value)
{
switch (DateTimeStyle)
{
case :
Buff.Append('"');
Buff.Append(value.ToString("yyyy-MM-dd"));
Buff.Append('"');
break;
case :
Buff.Append('"');
Buff.Append(value.ToString("HH:mm:ss"));
Buff.Append('"');
break;
default:
base.AppendDateTime(value);
break;
}
} protected override void AppendGuid(Guid value)
{
Buff.Append('"');
Buff.Append(value.ToString("N"));
Buff.Append('"');
} protected override void AppendBoolean(bool value)
{
base.AppendNumber(value.GetHashCode());
} protected override void AppendDataTable(System.Data.DataTable table)
{
if (TableStyle == )
{
Buff.Append('[');
var fix = ""; foreach (DataRow row in table.Rows)
{
Buff.Append(fix);
var fix2 = "";
Buff.Append('{');
foreach (DataColumn col in table.Columns)
{
Buff.Append(fix2);
AppendKey(col.ColumnName,false);
AppendObject(row[col]);
fix2 = ",";
}
Buff.Append('}');
fix = ",";
}
Buff.Append(']');
}
else
{
base.AppendDataTable(table);
}
} }
}
C#代码
然后就可以调用了
MyJsonBuilder jb = new MyJsonBuilder();
Console.WriteLine("TableStyle=1 ; DateTimeStyle=1");
jb.TableStyle = ;
jb.DateTimeStyle = ;
Console.WriteLine(jb.ToJsonString(ds)); Console.WriteLine("");
Console.WriteLine("TableStyle=0 ; DateTimeStyle=2");
jb.TableStyle = ;
jb.DateTimeStyle = ;
Console.WriteLine(jb.ToJsonString(ds));
结果
TableStyle=1 ; DateTimeStyle=1
{"User":[{"UID":"0f3f70f0939546d8803d8cd0ef4de8ec","Name":"blqw","Birthday":"1986-10-29","Sex":1,"IsDeleted":0},{"UID":"72489efcbc694801a358b697414892ee","Name":"小明","Birthday":"1990-01-01","Sex":1,"IsDeleted":0},{"UID":"865cddbb1f0c427e97a724844c35a83d","Name":"小华","Birthday":"1990-02-02","Sex":0,"IsDeleted":0}],"UserInfo":[{"ID":1,"UID":"0f3f70f0939546d8803d8cd0ef4de8ec","Address":"广州","ZipCode":100000},{"ID":2,"UID":"72489efcbc694801a358b697414892ee","Address":"上海","ZipCode":200000},{"ID":3,"UID":"865cddbb1f0c427e97a724844c35a83d","Address":"背景","ZipCode":300000}]} TableStyle=0 ; DateTimeStyle=2
{"User":{"columns":["UID","Name","Birthday","Sex","IsDeleted"],"rows":[["0f3f70f0939546d8803d8cd0ef4de8ec","blqw","00:00:00",1,0],["72489efcbc694801a358b697414892ee","小明","00:00:00",1,0],["865cddbb1f0c427e97a724844c35a83d","小华","00:00:00",0,0]]},"UserInfo":{"columns":["ID","UID","Address","ZipCode"],"rows":[[1,"0f3f70f0939546d8803d8cd0ef4de8ec","广州",100000],[2,"72489efcbc694801a358b697414892ee","上海",200000],[3,"865cddbb1f0c427e97a724844c35a83d","背景",300000]]}}
请按任意键继续. . .
比完整Demo还要完整的Demo下载
ps 此Demo中包含了一些我下一篇文章会写的内容,如果里面的代码和文章中的不完全一样,以Demo中可运行代码为准