Bloom Filter是一种空间效率很高的随机数据结构，用来表示一个集合，主要的应用是判断一个元素是否属于这个集合，适用于能容忍一定错误率的场合下，比如网络爬虫里的url去重。
最近看到了一个写的非常好的关于Bloom Filter的文章系列，读完之后受益匪浅，写篇博文记录之。
Bloom Filter概念和原理
http://blog.csdn.net/jiaomeng/article/details/1495500
从哈希存储到Bloom Filter
http://blog.csdn.net/jiaomeng/article/details/1496329
应用Bloom Filter的几个技巧
http://blog.csdn.net/jiaomeng/article/details/1497361
Counting Bloom Filter
http://blog.csdn.net/jiaomeng/article/details/1498283
Partial Bloom Filter
http://blog.csdn.net/jiaomeng/article/details/1502910
Compressed Bloom Filter
http://blog.csdn.net/jiaomeng/article/details/1505299
Perfect Hashing VS. Bloom Filter
http://blog.csdn.net/jiaomeng/article/details/1519383
Bloom Filter应用之Web Cache Sharing
http://blog.csdn.net/jiaomeng/article/details/1531423
Bloom Filter, Counting Bloom Filter和Dynamic Count Filter源码下载
http://blog.csdn.net/jiaomeng/article/details/1619321
注：该文章系列的作者为焦萌
