LevelDB

  LevelDB is a fast key-value storage library that provides an ordered mapping from string keys to string values.

  • Keys and values are arbitrary byte arrays.
  • Data is stored sorted by key.
  • Callers can provide a custom comparison function to override the sort order. 自定义Comparator。
  • The basic operations are Put(key,value)Get(key)Delete(key).
  • Multiple changes can be made in one atomic batch. 批处理,原子化,高效。
  • Users can create a transient snapshot to get a consistent view of data.
  • Forward and backward iteration is supported over the data.
  • Data is automatically compressed using the Snappy compression library.
  • External activity (file system operations etc.) is relayed through a virtual interface so users can customize the operating system interactions.

性能

  LevelDB性能非常突出,官方网站报道其随机写性能达到40万条记录每秒,而随机读性能达到6万条记录每秒。总体来说,LevelDb的写操作要大大快于读操作,而顺序读写操作则大大快于随机读写操作。

Limitations

  • This is not a SQL database. It does not have a relational data model, it does not support SQL queries, and it has no support for indexes. 不支持结SQL查询。
  • Only a single process (possibly multi-threaded) can access a particular database at a time. 一个数据库只能被单进程访问。
  • There is no client-server support builtin to the library. An application that needs such support will have to wrap their own server around the library.  无网络模型。

[Synchronous Writes]

  By default, each write to leveldb is asynchronous: it returns after pushing the write from the process into the operating system.

默认所有到leveldb的写操作都是异步, 在把数据从进程交给操作系统后该写操作就返回.

  The transfer from operating system memory to the underlying persistent storage happens asynchronously.

  从操作系统到下层的持久存储是一个异步的过程.

  The sync flag can be turned on for a particular write to make the write operation not return until the data being written has been pushed all the way to persistent storage.

  sync标致可打开, 以使得写操作到直至把数据写入到持久存储才返回.

  

  The downside of asynchronous writes is that a crash of the machine may cause the last few updates to be lost.

  异步写操作不利的一面是, 机器的崩溃会导致最后几个操作丢失.

  Note that a crash of just the writing process will not cause any loss since even when sync is false, an update is pushed from the process memory into the operating system before it is considered done.

  当sync为false时,写进程的崩溃不会导致异步写操作丢失, 国为数据已经被写到了操作系统.

  Asynchronous writes can often be used safely. For example, when loading a large amount of data into the database you can handle lost updates by restarting the bulk load after a crash. A hybrid scheme is also possible where every Nth write is synchronous, and in the event of a crash, the bulk load is restarted just after the last synchronous write finished by the previous run.

[Concurrency]

  A database may only be opened by one process at a time. The leveldb implementation acquires a lock from the operating system to prevent misuse. Within a single process, the same leveldb::DB object may be safely shared by multiple concurrent threads. I.e., different threads may write into or fetch iterators or call Get on the same database without any external synchronization (the leveldb implementation will automatically do the required synchronization). However other objects (like Iterator and WriteBatch) may require external synchronization. If two threads share such an object, they must protect access to it using their own locking protocol.

[Iteration]

  The following example demonstrates how to print all key,value pairs in a database.

  

   The following variation shows how to process just the keys in the range [start,limit):

   

   You can also process entries in reverse order. (Caveat: reverse iteration may be somewhat slower than forward iteration.)
  
[Snapshots]
  Snapshots provide consistent read-only views over the entire state of the key-value store. ReadOptions::snapshot may be non-NULL to indicate that a read should operate on a particular version of the DB state. IReadOptions::snapshot is NULL, the read will operate on an implicit snapshot of the current state.
  如果ReadOptions的snapshot属性非空, 意味着操作会在该版本上发生, 如果为NULL, 操作会在一个隐含的版本上发生. 所以无论怎样, 使用iterator都会得到一个一致的版本, 不用担心在iteration过程中会插入或是删除数据.

  Snapshots are created by the DB::GetSnapshot() method:

  

  Note that when a snapshot is no longer needed, it should be released using the DB::ReleaseSnapshot interface. This allows the implementation to get rid of state that was being maintained just to support reading as of that snapshot.

leveldb的更多相关文章

  1. leveldb 性能、使用场景评估

    最近有个业务写远远大于读,读也集中在最近写入,这不很适合采用leveldb存储么,leveldb业界貌似ssdb用得挺广,花了两天时间就ssdb简单做下测试,以下总结. ssdb 是leveldb的r ...

  2. leveldb源码分析--SSTable之Compaction

    对于compaction是leveldb中体量最大的一部分,也应该是最为复杂的部分,为了便于理解我们首先从一些基本的概念开始.下面是一些从doc/impl.html中翻译和整理的内容: Level 0 ...

  3. leveldb 学习。

    1)大概浏览了leveldb文档的介绍.本想逐步看代码,想想还是自己先实现一个看看如何改进. 2)完成了一个非常丑陋的初版,但是还是比初初版有进步. 3)key value的数据库,不允许有key重复 ...

  4. 解决: org.iq80.leveldb.DBException: IO error: C:\data\trie\000945.sst: Could not create random access file.

    以太坊MPT树的持久化层是采用了leveldb数据库,然而在抽取MPT树代码运行过程中,进行get和write操作时却发生了错误: Caused by: org.fusesource.leveldbj ...

  5. 用Qt Creator 对 leveldb 进行简单的读写

    #include <iostream> #include <string> #include <leveldb/db.h> #include <boost/l ...

  6. leveldb 学习笔记之VarInt

    在leveldb在查找比较时的key里面保存key长度用的是VarInt,何为VarInt呢,就是变长的整数,每7bit代表一个数,第8bit代表是否还有下一个字节, 1. 比如小于128(一个字节以 ...

  7. leveldb源码学习系列

    楼主从2014年7月份开始学习<>,由于书籍比较抽象,为了加深思考,同时开始了Google leveldb的源码学习,主要是想学习leveldb的设计思想和Google的C++编程规范.目 ...

  8. LevelDB库简介

    LevelDB库简介 一.LevelDB入门 LevelDB是Google开源的持久化KV单机数据库,具有很高的随机写,顺序读/写性能,但是随机读的性能很一般,也就是说,LevelDB很适合应用在查询 ...

  9. zookeeper + LevelDB + ActiveMQ实现消息队列高可用

    通过集群实现消息队列高可用. 消息队列在项目中存储订单.邮件通知.数据分发等重要信息,故对消息队列稳定可用性有高要求. 现在通过zookeeper选取activemq leader的形式实现当某个ac ...

  10. leveldb.net对象读写封装

    leveldb是一个非常高效的可嵌入式K-V数据库,在.NET下有着基于win实现的包装leveldb.net;不过leveldb.net只提供了基于byte[]和string的处理,这显然会对使用的 ...

随机推荐

  1. 函数ut_malloc_low

    /**********************************************************************//** Allocates memory. @retur ...

  2. UVa 10106 Product

    高精度乘法问题,WA了两次是因为没有考虑结果为0的情况.  Product  The Problem The problem is to multiply two integers X, Y. (0& ...

  3. 51nod1294 修改数组

    看题解的...就是将必须要修改的数去掉后求最长的不递减子序列. upper_bound+lower_bound要理解.有时候-1有时候不用是有原因的. #include<cstdio> # ...

  4. ubuntu下实现openerp 7使用nginx反正代理及绑定域名

    这里要记录一个nginx upstream实现反向代理的配置过程. 连接vps的ssh. 先安装nginx sudo apt-get install nginx 修改/etc/nginx/nginx. ...

  5. 使用MySQL Proxy解决MySQL主从同步延迟

    MySQL的主从同步机制非常方便的解决了高并发读的应用需求,给Web方面开发带来了极大的便利.但这种方式有个比较大的缺陷在于MySQL的同步机制 是依赖Slave主动向Master发请求来获取数据的, ...

  6. BZOJ 1556 墓地秘密

    2333333333333333333333333333333333333333333333 啊啊啊啊啊啊啊啊啊啊啊啊啊啊啊啊啊啊啊啊啊啊啊啊啊啊啊啊啊啊 辣鸡出题人辣鸡出题人辣鸡出题人辣鸡出题人辣鸡 ...

  7. codevs 4927 线段树练习5

    赶在期末考试之前把这道傻逼题调了出来. #include<iostream> #include<cstdio> #include<cstring> #include ...

  8. Android解惑 - 为什么要用Fragment.setArguments(Bundle bundle)来传递参数(转)

    Fragment在Android3.0开始提供,并且在兼容包中也提供了Fragment特性的支持.Fragment的推出让我们编写和管理用户界面更快捷更方便了.   但当我们实例化自定义Fragmen ...

  9. mysql无法插入中文字符解决

    1. 基于可维护的角度,虽然latin1没什么问题,但是还是尽量换成utf8或者gb系列 2. 出现乱码时: SHOW VARIABLES LIKE 'character%'SHOW VARIABLE ...

  10. 最大熵模型 Maximum Entropy Model

    熵的概念在统计学习与机器学习中真是很重要,熵的介绍在这里:信息熵 Information Theory .今天的主题是最大熵模型(Maximum Entropy Model,以下简称MaxEnt),M ...