我想使用protobuf-net来序列化股票市场数据。我正在玩以下消息模型：
1st message: Meta Data describing what data to expect and some other info.
2nd message: DataBegin
3rd message: DataItem
4th message: DataItem
...
nth message: EndData
以下是数据项的示例：
class Bar{
DateTime DateTime{get;set;}
float Open{get;set}
float High{get;set}
float Low{get;set}
float Close{get;set}
intVolume{get;set}
}
现在我正在使用TypeModel.SerializeWithLengthPrefix（...）来序列化每条消息（TypeModel已编译）。哪个效果很好，但它比使用BinaryWriter手动序列化每条消息慢大约10倍。当然，重要的不是元数据，而是每个DataItem的序列化。我有很多数据，在某些情况下，它可以读/写到文件中，并且性能至关重要。
提高每个DataItem的序列化和反序列化性能的好方法是什么？
我应该直接在这里使用ProtoWriter吗？如果是，我将如何做到这一点（我对协议缓冲区有点新意）。
答案 0 :(得分：3)
是的，如果您的数据是一组非常简单的同类记录，没有其他要求（例如，它不需要向前兼容或版本优雅，或者可以从不完全了解所有的客户端使用数据），不需要方便可移植，并且您不介意手动实现所有序列化，然后是：您可以手动更高效地执行它。在快速测试中：
protobuf-net serialize: 55ms, 3581680 bytes
protobuf-net deserialize: 65ms, 100000 items
BinaryFormatter serialize: 443ms, 4200629 bytes
BinaryFormatter deserialize: 745ms, 100000 items
manual serialize: 26ms, 2800004 bytes
manual deserialize: 32ms, 100000 items
额外的空间可能是字段标记（如果手动打包记录则不需要，并且不需要担心同时使用的API的不同版本）。
我当然不会重现“10x”;我得到2x，考虑到protobuf提供的东西，这也不错。肯定比BinaryFormatter更好，更像是20倍！这是一些的功能：
听起来就像你的场景手册序列化一样;那很好 - 我没有被冒犯; p序列化库的目的是以不需要手动编写代码的方式解决更一般的问题。< / p>
我的测试台：
using System;
using System.Collections.Generic;
using System.Diagnostics;
using System.IO;
using System.Linq;
using ProtoBuf;
using ProtoBuf.Meta;
using System.Runtime.Serialization.Formatters.Binary;
public static class Program
{
static void Main()
{
var model = RuntimeTypeModel.Create();
model.Add(typeof(BarWrapper), true);
model.Add(typeof(Bar), true);
model.CompileInPlace();
var data = CreateBar(100000).ToList();
RunTest(model, data);
}
private static void RunTest(RuntimeTypeModel model, List<Bar> data)
{
using(var ms = new MemoryStream())
{
var watch = Stopwatch.StartNew();
model.Serialize(ms, new BarWrapper {Bars = data});
watch.Stop();
Console.WriteLine("protobuf-net serialize: {0}ms, {1} bytes", watch.ElapsedMilliseconds, ms.Length);
ms.Position = 0;
watch = Stopwatch.StartNew();
var bars = ((BarWrapper) model.Deserialize(ms, null, typeof (BarWrapper))).Bars;
watch.Stop();
Console.WriteLine("protobuf-net deserialize: {0}ms, {1} items", watch.ElapsedMilliseconds, bars.Count);
}
using (var ms = new MemoryStream())
{
var bf = new BinaryFormatter();
var watch = Stopwatch.StartNew();
bf.Serialize(ms, new BarWrapper { Bars = data });
watch.Stop();
Console.WriteLine("BinaryFormatter serialize: {0}ms, {1} bytes", watch.ElapsedMilliseconds, ms.Length);
ms.Position = 0;
watch = Stopwatch.StartNew();
var bars = ((BarWrapper)bf.Deserialize(ms)).Bars;
watch.Stop();
Console.WriteLine("BinaryFormatter deserialize: {0}ms, {1} items", watch.ElapsedMilliseconds, bars.Count);
}
byte[] raw;
using (var ms = new MemoryStream())
{
var watch = Stopwatch.StartNew();
WriteBars(ms, data);
watch.Stop();
raw = ms.ToArray();
Console.WriteLine("manual serialize: {0}ms, {1} bytes", watch.ElapsedMilliseconds, raw.Length);
}
using(var ms = new MemoryStream(raw))
{
var watch = Stopwatch.StartNew();
var bars = ReadBars(ms);
watch.Stop();
Console.WriteLine("manual deserialize: {0}ms, {1} items", watch.ElapsedMilliseconds, bars.Count);
}
}
static IList<Bar> ReadBars(Stream stream)
{
using(var reader = new BinaryReader(stream))
{
int count = reader.ReadInt32();
var bars = new List<Bar>(count);
while(count-- > 0)
{
var bar = new Bar();
bar.DateTime = DateTime.FromBinary(reader.ReadInt64());
bar.Open = reader.ReadInt32();
bar.High = reader.ReadInt32();
bar.Low = reader.ReadInt32();
bar.Close = reader.ReadInt32();
bar.Volume = reader.ReadInt32();
bars.Add(bar);
}
return bars;
}
}
static void WriteBars(Stream stream, IList<Bar> bars )
{
using(var writer = new BinaryWriter(stream))
{
writer.Write(bars.Count);
foreach (var bar in bars)
{
writer.Write(bar.DateTime.ToBinary());
writer.Write(bar.Open);
writer.Write(bar.High);
writer.Write(bar.Low);
writer.Write(bar.Close);
writer.Write(bar.Volume);
}
}
}
static IEnumerable<Bar> CreateBar(int count)
{
var rand = new Random(12345);
while(count-- > 0)
{
var bar = new Bar();
bar.DateTime = new DateTime(
rand.Next(2008,2011), rand.Next(1,13), rand.Next(1, 29),
rand.Next(0,24), rand.Next(0,60), rand.Next(0,60));
bar.Open = (float) rand.NextDouble();
bar.High = (float)rand.NextDouble();
bar.Low = (float)rand.NextDouble();
bar.Close = (float)rand.NextDouble();
bar.Volume = rand.Next(-50000, 50000);
yield return bar;
}
}
}
[ProtoContract]
[Serializable] // just for BinaryFormatter test
public class BarWrapper
{
[ProtoMember(1, DataFormat = DataFormat.Group)]
public List<Bar> Bars { get; set; }
}
[ProtoContract]
[Serializable] // just for BinaryFormatter test
public class Bar
{
[ProtoMember(1)]
public DateTime DateTime { get; set; }
[ProtoMember(2)]
public float Open { get; set; }
[ProtoMember(3)]
public float High { get; set; }
[ProtoMember(4)]
public float Low { get; set; }
[ProtoMember(5)]
public float Close { get; set; }
// use zigzag if it can be -ve/+ve, or default if non-negative only
[ProtoMember(6, DataFormat = DataFormat.ZigZag)]
public int Volume { get; set; }
}