Let’s start with a test for sorting. Sometimes, after writing a test, it turns out that everything works and there’s nothing to implement.

(ns poligon.algorithms.sorting-test
  (:require [poligon.algorithms.sorting :refer :all]
            [clojure.test :refer :all]))

;; random 10.000 numbers:
(def unsorted-data
  (vec (doall (repeatedly 10000 #(rand-int 10000)))))

;; expected result:
(def sorted-data (sort unsorted-data))

(deftest insertion-sort-test
  (is (= [] (insertion-sort [])))
  (is (= [1 2 3] (insertion-sort [1 2 3])))
  (is (= [1 2 3 4 5] (insertion-sort [5 2 3 4 1])))
  ;; transients version:
  (is (= sorted-data (time (insertion-sort unsorted-data))))
  ;; persistent vector version:
  (is (= sorted-data (time (insertion-sort-simple unsorted-data)))))

First let’s implement the algorithm in Clojure. The flow is simple: take next element and insert into correct position in already sorted vector. In this version we just reorder elements of persistent vector as we usually do in Clojure:

(defn- insert-simple
  [tv idx]
  (let [current-value (get tv idx)]
    (loop [i idx v tv]
      (let [left-value (get v (dec i))]
        (if (and (pos? i)
                 (> left-value current-value))
          (recur (dec i) (assoc v i left-value))
          (assoc v i current-value))))))

(defn insertion-sort-simple
  [v]
  (let [size (-> v count dec)]
    (loop [i 1 tv v]
      (if (<= i size)
        (recur (inc i) (insert-simple tv i))
        tv))))

This version works as expected, but here we have overhead of handling of persistent vector. If we would like to change only a few values it wouldn’t matter, but many algorithms reorder elements all the time. In such case we can simply resort to transients and mutate local data structure.

A nice thing about Clojure transients is that the code structure is almost the same as we normally write in Clojure. So we can develop an algorithm and then introduce transients. The only differences are:

1. Conversion of persistent data structure to transient using transient function.
2. Mutation using bang versions of the functions (assoc!, dissoc!, etc.)
3. Turning transient back into persistent structure using persistent!.

In case of Insertion Sort we only use transient, assoc!, and persistent!. The rest of the code stays the same:

(ns poligon.algorithms.sorting)

(defn- insert
  "Insert element from `idx` into correct position in transient vector `tv`."
  [tv idx]
  (let [current-value (get tv idx)]
    (loop [i idx v tv]
      (let [left-value (get v (dec i))]
        (if (and (pos? i)
                 (> left-value current-value))
          (recur (dec i) (assoc! v i left-value))
          (assoc! v i current-value))))))

(defn insertion-sort
  "Insertion sort using transients."
  [v]
  (let [size (-> v count dec)]
    (loop [i 1 tv (transient v)]
      (if (<= i size)
        (recur (inc i) (insert tv i))
        (persistent! tv)))))

I run the tests a couple of times and the run-times were pretty much the same as here, namely transients version is about 3 times faster:

lein test :only poligon.algorithms.sorting-test

lein test poligon.algorithms.sorting-test
"Elapsed time: 8855.431509 msecs"
"Elapsed time: 24010.397826 msecs"

Ran 2 tests containing 6 assertions.
0 failures, 0 errors.

Of course the numbers way be different for different data. But it’s pretty clear that Clojure transients increase performance without complicating code much.

• Insertion Sort explained
• Check out other cool things in Clojure Tutorial!
• The code is available at GitHub