Clojure中多方法与cond的性能 [英] Performance of multimethod vs cond in Clojure

问题描述

多方法比协议慢，即使使用多方法提供了一种更灵活的解决方案，也应在它们可以解决问题时尝试使用协议。
那么 cond 和multimethod怎么办？它们可以用来解决相同的问题，但我猜想，与 cond 相比，多方法具有巨大的性能开销。如果是这样，我为什么要使用多重方法而不是 cond ？

Multimethods are slower than protocols and one should try to use protocols when they can solve the problem, even though using multimethods gives a more flexible solution. So what is the case with cond and multimethod? They can be used to solve the same problem but my guess is that multimethod has a huge performance overhead vs cond. If so why would i ever want to use multimethod instead of cond?

推荐答案

<为了跟进@AlexMiller的评论，我尝试使用更多随机数据进行基准测试，并添加了协议实现（还为不同的方法添加了另一种类型-Integer）。

To follow up on @AlexMiller comment, I tried to benchmark with more randomised data and added up the protocol implementation (also added one more type - Integer - to the different methods).

(defprotocol StrConvert
  (to-str [this]))

(extend-protocol StrConvert
  nil
  (to-str [this] "null")
  java.lang.Integer
  (to-str [this] (str this))
  java.lang.String
  (to-str [this] (str "\"" this "\""))
  clojure.lang.Keyword
  (to-str [this] (to-str (name this)))
  java.lang.Object
  (to-str [this] (str this)))

data 包含10000个随机整数序列，这些整数随机转换为字符串， nil ，关键字或向量。

data contains a sequence of 10000 random integers, that are randomly converted to String, nil, keyword or vector.

(let [fns [identity            ; as is (integer)
           str                 ; stringify
           (fn [_] nil)        ; nilify
           #(-> % str keyword) ; keywordize
           vector]             ; vectorize
      data (doall (map #(let [f (rand-nth fns)] (f %))
                       (repeatedly 10000 (partial rand-int 1000000))))]
  ;; print a summary of what we have in data
  (println (map (fn [[k v]] [k (count v)]) (group-by class data)))
  ;; multimethods
  (c/quick-bench (dorun (map convert data)))
  ;; cond-itionnal
  (c/quick-bench (dorun (map convert-cond data)))
  ;; protocols
  (c/quick-bench (dorun (map to-str data))))

结果是针对包含以下内容的数据：

The result is for data containing :

([clojure.lang.PersistentVector 1999] [clojure.lang.Keyword 1949]
 [java.lang.Integer 2021] [java.lang.String 2069] [nil 1962])

• 多种方法：6.26 ms


• 条件：5.18 ms


• 协议：6.04毫秒



我当然会建议@DanielCompton：设计比纯粹的性能更重要至少在此示例中，每种方法似乎成对出现。

I would certainly suggest as @DanielCompton : the design matters more than the pure performances that seem on pair for each method, at least on this example.

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