数组和Ruby的哈希值的性能
我有将存储一个类的实例,让我们说高达10.000以上的程序。该类的实例有几个属性,我需要不时,但其最重要的一条是ID。
I have a program that will store many instances of one class, let's say up to 10.000 or more. The class instances have several properties that I need from time to time, but their most important one is the ID.
class Document
attr_accessor :id
def ==(document)
document.id == self.id
end
end
现在,什么是存储这些对象的数以千计的最快方法是什么?
Now, what is the fastest way of storing thousands of these objects?
我曾经把他们都到文档的数组:
I used to put them all into an array of Documents:
documents = Array.new
documents << Document.new
# etc
现在的替代办法是将它们存储在一个Hash:
Now an alternative would be to store them in a Hash:
documents = Hash.new
doc = Document.new
documents[doc.id] = doc
# etc
在我的申请,我主要是要找出一个文件是否都存在。是哈希的对象的has_key?
功能显著快于线性搜索阵列和文件
对象的比较?中都的 O(N)的或对象的has_key?
连的 O(1)的。我会看看有什么区别?
In my application, I mostly need to find out whether a document exists at all. Is the Hash's has_key?
function significantly faster than a linear search of the Array and the comparison of Document
objects? Are both within O(n) or is has_key?
even O(1). Will I see the difference?
此外,有时我需要添加文件时,它已经存在。当我使用数组,我会检查与包括哪些内容?
之前,当我使用一个Hash,我只是用对象的has_key?
一次。同样的问题之上。
Also, sometimes I need to add Documents when it is already existing. When I use an Array, I would have to check with include?
before, when I use a Hash, I'd just use has_key?
again. Same question as above.
你有什么想法?什么是存储大量数据时,90%的时间我只需要知道ID是否存在的最快速的方法(而不是对象本身!)
What are your thoughts? What is the fastest method of storing large amounts of data when 90% of the time I only need to know whether the ID exists (not the object itself!)
哈希是的多的更快查找:
require 'benchmark'
Document = Struct.new(:id,:a,:b,:c)
documents_a = []
documents_h = {}
1.upto(10_000) do |n|
d = Document.new(n)
documents_a << d
documents_h[d.id] = d
end
searchlist = Array.new(1000){ rand(10_000)+1 }
Benchmark.bm(10) do |x|
x.report('array'){searchlist.each{|el| documents_a.any?{|d| d.id == el}} }
x.report('hash'){searchlist.each{|el| documents_h.has_key?(el)} }
end
# user system total real
#array 2.240000 0.020000 2.260000 ( 2.370452)
#hash 0.000000 0.000000 0.000000 ( 0.000695)