打开数据库并写入数据

using (StorageEngine engine = new StorageEngine("stsdb4.sys", "stsdb4.dat"))
{
    XIndex<int, string> table = engine.OpenXIndex<int, string>("table");
  
    for (int i = 0; i < 1000000; i++)
    {
        table[i] = i.ToString();
    }
  
    table.Flush();
    engine.Commit();
}

读取数据

using (StorageEngine engine = new StorageEngine("stsdb4.sys", "stsdb4.dat"))
{
    XIndex<int, string> table = engine.OpenXIndex<int, string>("table");
  
    foreach (var row in table) //table.Forward(), table.Backward()
    {
        Console.WriteLine("{0} {1}", row.Key, row.Value);
    }
}

更多例子

可以访问这里查看更多的例子,或者下载类库或代码,里面有pdf文档。

XIndex<TKey, TRecord> table;

The supported types for both TKey and TRecord are:

  • 1.1. Primitive types – Boolean, Char, SByte, Byte, Int16, UInt16, Int32, UInt32, Int64, UInt64, Single, Double, Decimal, DateTime, String, byte[];
  • 1.2. Classes and structures with default constructor, containing public read/write properties and/or fields with types from 1.1;
  • 1.3. Classes and structures with default constructor, containing public read/write properties and/or fields with types from 1.1 and/or from 1.2;
  • 1.4.Types that can be transformed to one of the IData successors, available in STSdb4 (described later).

For example, if we have the following two types:

    public class Key
    {
        public string Symbol { get; set; }
        public DateTime Timestamp { get; set; }
    }
    
    public class Tick
    {
        public double Bid { get; set; }
        public double Ask { get; set; }
        public long Volume { get; set; }
        public string Provider { get; set; }
    }

We can open different table types:

  
    IIndex<long, Tick> table1 = engine.OpenXIndex<long, Tick>("table1"); 
    IIndex<DateTime, Tick> table2 = engine.OpenXIndex<DateTime, Tick>("table2");
    
    IIndex<Key, Tick> table3 = engine.OpenXIndex<Key, Tick>("table3");

Or even:

    IIndex<Tick, Tick> table3 = engine.OpenXIndex<Tick, Tick>("table4");

In the case of composite keys the engine compares sub-keys in the order in which they are declared as properties.

Data Transformer

Data transformers are responsible for converting application types to and from IData types. They constitute the transformation layer between XIndex<TKey,TRecord> and XIndex table. All transformers look like:

    public interface IDataTransformer<T>
    {
        IData ToIData(T item);
        T FromIData(IData data);
        DataType DataType { get; }
    }

Each XIndex<TKey,TRecord> instance automatically generates two
data transformers – one for the keys and one for the records. In that
way every input TKey/TRecord instance is transformed to appropriate
IData instance. Similarly, every IData instance from the XIndex is
transformed back to TKey/TRecord. (For highly sophisticated types custom
transformers can be provided.)

Suppose again that we have the following class:

    public class Tick
    {
        public string Symbol { get; set; }
        public DateTime Timestamp { get; set; }
        public double Bid { get; set; }
        public double Ask { get; set; }
        public long Volume { get; set; }
        public string Provider { get; set; }
    }

If we have XIndex<long, Tick>

IIndex<long, Tick> table = engine.OpenXIndex<long, Tick>("table");

Then the backend XIndex table will be opened with the following two types for the keys and for the records:

Data<long>
Data<string, DateTime, double, double, long, string>

We can open simultaneously the backend XIndex table:

    DataType keyType = DataType.Int64;

    DataType recordType = DataType.Slotes(
        DataType.String,
        DataType.DateTime,
        DataType.Double,
        DataType.Double,
        DataType.Int64,
        DataType.String);     IIndex<IData, IData> table2 = engine.OpenXIndex(keyType, recordType, "table");

In this case table and table2 will refer to the same data.

If we decide to extend the Tick class with property of non-primitive type (Provider):

    public class Provider
    {
        public string Name { get; set; }
        public string Website { get; set; }
    }     public class Tick
    {
        public string Symbol { get; set; }
        public DateTime Timestamp { get; set; }
        public double Bid { get; set; }
        public double Ask { get; set; }
        public long Volume { get; set; }
        public Provider Provider { get; set; }
    }

Then the backend XIndex will be opened with the types:

 Data<long>
 Data<string, DateTime, double, double, long, bool, string, string>

We can decide to exclude Symbol and Timestamp and use them as composite key:

public class Key
    {
        public string Symbol { get; set; }
        public DateTime Timestamp { get; set; }
    }
    
    public class Provider
    {
        public string Name { get; set; }
        public string Website { get; set; }
    }     public class Tick
    {
        //public string Symbol { get; set; }
        //public DateTime Timestamp { get; set; }
        public double Bid { get; set; }
        public double Ask { get; set; }
        public long Volume { get; set; }
        public Provider Provider { get; set; }
    }
IIndex<Key, Tick> table = engine.OpenXIndex<Key, Tick>("table");

Then the backend XIndex will be with types:

Data<string, DateTime>
Data<double, double, long, bool, string, string>

Because data slots can be from primitive types only, an additional
Boolean slot is added to indicate whether the Provider property of the
current object is null. Thus we decompose user types.

Note: In the future releases slots will be extended to support IData recursively, so the additional slots will be eliminated.

If a XIndex uses composite keys with more than one slot in its Data,
the engine compares sub-keys in BigEndian order – from small slot
indexes to big one. (The engine automatically generates appropriate
comparers for the relevant Data type.)

Transformed to IData user data is very suitable for compression. The
engine again automatically generates compression classes for each XIndex
type. These classes use parallel vertical compressions for each slot,
depending on its primitive type. In that way the compressions are fast,
while keeping high compression ratio. By default
XIndex<TKey,TRecord> and XIndex keeps the data in compressed
format.

XFile

STSdb 4.0 supports sparse files called XFile. We can work with XFile as we are with a standard .NET stream.

using (IStorageEngine engine = STSdb.FromFile("stsdb4.sys", "stsdb4.dat"))
    {
        XFile file = engine.OpenXFile("file");         Random random = new Random();
        byte[] buffer = new byte[] { 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 };         for (int i = 0; i < 100; i++)
        {
            long position = random.Next();             //writes some data on random positions
            file.Seek(position, SeekOrigin.Begin);
            file.Write(buffer, 0, buffer.Length);
        }         file.Flush();
        engine.Commit();
    }

XFile uses special XIndex<long, byte[]> implementation and
provides effective sparse file functionality. Thus, in one storage
engine developers can combine using of XIndex tables and of XFile sparse
files.

Client/Server

From the client side, creating a client connection:

using (IStorageEngine engine = STSdb.FromNetwork("localhost", 7182))
    {
        IIndex<int, string> table = engine.OpenXIndex<int, string>("table");         for (int i = 0; i < 1000; i++)
        {
            table[i] = i.ToString();
        }         table.Flush();
        engine.Commit();
    }

From the server side, starting the server:

  using (IStorageEngine engine = STSdb.FromFile("stsdb4.sys", "stsdb4.dat"))
    {
        var server = STSdb.CreateServer(engine, 7182);         server.Start();         //server is ready for connections         server.Stop();
    }

The created server instance will listen on the specified port and receive/send data from/to the clients.

STSdb的更多相关文章

  1. STSDB、NDataBase 对象数据库在不同.net framework下无法读取的解决办法

    STSDB.NDataBase 等对象数据库将对象保存在文件中后,如果在不同的windows平台.不同的.net frameWork下总是无法读取,原因是对象模式已经不同了. 解决的办法也很简单,就是 ...

  2. 基于STSdb和fastJson的磁盘/内存缓存

    更新 1. 增加了对批量处理的支持,写操作速度提升5倍,读操作提升100倍 2. 增加了对并发的支持 需求 业务系统用的是数据库,数据量大,部分只读或相对稳定业务查询复杂,每次页面加载都要花耗不少时间 ...

  3. STSdb,最强纯C#开源NoSQL和虚拟文件系统 4.0 RC2 支持C/S架构

    STSdb是什么 再来说明一下STSdb是什么:STSdb是C#写的开源嵌入式数据库和虚拟文件系统,支持实时索引,性能是同类产品的几倍到几十倍,访问官方网站. 温故知新 之前发了文章<STSdb ...

  4. stsdb开发指南

    摘自:http://www.iopenworks.com/Products/ProductDetails/DevelopmentGuide?proID=387 多线程问题,请参见线程安全小结 1 ST ...

  5. 一个基于STSdb和fastJson的磁盘/内存缓存

    一个基于STSdb和fastJson的磁盘/内存缓存 需求 业务系统用的是数据库,数据量大,部分只读或相对稳定业务查询复杂,每次页面加载都要花耗不少时间(不讨论异步),觉得可以做一下高速缓存,譬如用n ...

  6. STSdb数据库的实现使用类

    STSdb 3.5是一个开源的key-value存储形式的数据库,它是用微软.net框架C#语言编写的.STSdb 3.5尤其使用于紧急任务或实时系统,如:股市交易,电子通信,实验室数据等,它的主要功 ...

  7. STSDB 一

    STSdb 4.0 是一个开源的NoSQL 数据库和虚拟文件系统,支持实时索引,完全用c#开发的. 引擎原理基于WaterfallTree(瀑布树)数据结构搭建 以下内容基于stsdb4.dll(4. ...

  8. ENode 2.0 - 整体架构介绍

    前言 今天是个开心的日子,又是周末,可以轻轻松松的写写文章了.去年,我写了ENode 1.0版本,那时我也写了一个分析系列.经过了大半年的时间,我对第一个版本做了很多架构上的改进,最重要的就是让ENo ...

  9. WaterfallTree(瀑布树) 详细技术分析系列

    前言 WaterfallTree(瀑布树) 是最强纯C#开源NoSQL和虚拟文件系统-STSdb专有的(版权所有/专利)算法/存储结构. 参考 关于STSdb,我之前写过几篇文章,譬如: STSdb, ...

随机推荐

  1. centos coreseek 快速安装

    CoreSeek快速安装: 安装前,建议查看:源码包说明README:4.0/4.1版可参考3.2版本安装,步骤相同:如遇到问题,请看详细安装说明. ##下载coreseek:coreseek 3.2 ...

  2. hdu 5094 Maze 状态压缩dp+广搜

    作者:jostree 转载请注明出处 http://www.cnblogs.com/jostree/p/4092176.html 题目链接:hdu 5094 Maze 状态压缩dp+广搜 使用广度优先 ...

  3. Ajax跨域请求——PHP服务端处理

    header('Access-Control-Allow-Origin:*'); // 响应类型 header('Access-Control-Allow-Methods:POST'); // 响应头 ...

  4. jQuery Mobile里xxx怎么用呀?(控件篇)

    jQuery Mobile里都有什么控件? http://api.jquerymobile.com/category/widgets/ jQuery Mobile里slider控件的change事件怎 ...

  5. Eat that Frog

    Eat that Frog,中文翻译过来就是“吃掉那只青蛙”.不过这里并不是讨论怎么去吃青蛙,而是一种高效的方法. Eat that Frog是Brian Tracy写的一本书(推荐阅读).这是一个很 ...

  6. HIVE中内连接和左半连接不一致问题

    一.理论 HIVE中都是按等值连接来统计的,理论上两种写法统计结果应该是一致的: 二.实际情况 但实际使用中发现两种写法会返回的结果,总会有一些差距虽然差别不大,但让人很是困惑. 三.原因 当使用jo ...

  7. .net 访问远程的MSSQL报System.AccessViolationException错误的解决方法

    访问远程的数据库时 报错,本地数据库正常 netsh winsock reset   --运行此命令,解决. netsh winsock reset命令,作用是重置 Winsock 目录.如果一台机器 ...

  8. python与编码

    Python中的文字对象 Python 3.x中处理文字的对象有str, bytes, bytearray. bytes和bytearray可以使用除了用作格式化的方法(format, format_ ...

  9. Python 学习日志(一)

    第一天: (一)安装Python3.3: (二)试运行: 1.在IDLE中输入:print("Hello,world"); //回车查看结果 2.使用"File" ...

  10. Java中的数组问题

    java.util.Arrays  This class deals with 'real' arrays in java, in the form of T[]. Thus it doesn't d ...