The use of Julia's Bloomfilters

We all know that Bron filtering is a very effective way to determine whether an element is in a set. For example, in the WPS word processing software, you need to check whether a word is spelled correctly; need to determine whether a suspect's name is on the suspect list; in a web crawler, determine if a URL has been accessed. The simplest solution is to use the Hashtable method to store it, the benefits of which are fast and accurate, and the disadvantage is that it consumes a lot of memory space. Therefore, the Bron filter is proposed for the problem of large space-consuming. However, the Bron filter is the error recognition rate, that is, the elements in the collection must be recognized, but not in the set of elements may be recognized as in the collection, fortunately, the probability of such a false recognition rate is relatively small, usually acceptable.

The first step in the fabric filter is to construct a filter for the cloth-augmentation. So now Mayuyu take everyone to use Julia's three-party package Bloomfilters.

In Julia, there are a lot of better packages, specifically for reference:http://pkg.julialang.org/ and we need the Bühler filter pack here:https://github.com/ JOHNMYLESWHITE/BLOOMFILTERS.JL

Of course, the first step is to install the Bloomfilters package, in the Julia Interactive mode, execute the following command

Well, after executing the command, Mayuyu's bloomfilters is installed, and now it's time to learn how to use it. Such as

in Julia's Bühler filter package, there is also the mmap function, that is, when the file is used in memory, you can set up a good filter data such as the fabric to write to the file, so that the next direct use. for specific usage, refer to the following links:

Https://github.com/johnmyleswhite/BloomFilters.jl/blob/master/README.md

The use of Julia's Bloomfilters