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Java 7 vs Groovy 2.1 Performance Comparison

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Java 7 vs Groovy 2.1 Performance Comparison

Seeing how Groovy impacts our daily routines I decided to look closer at its performance, and compare it to Java 7.

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I haven't used Groovy for 2 years, since my last touch with Grails. I get stuck in (hard)core Enterprise Java, with some performance aspects in background. I've almost missed a chance to learn Spock, but fortunately Warsaw Java User Group helped me to snap out of some legacy systems and back to normal self-development. In fact I hope that frameworks such as Spock or Geb will change approach to writing tests, by making them easier and more effective. Both frameworks use Groovy, as well as the new king in build tools - Gradle. Seeing pace how Groovy impacts our daily routines I decided to look closer at its performance, and compare it to Java 7.

My test environment is based on Java 1.7.0_25 and Groovy 2.1.6. As always in such comparisons I used Caliper in version 1.0-beta-1 (almost stable) and prepared a number of (I hope) representative microbenchmarks.

First benchmark based on Fork/Join framework should be most similar in both languages, because it uses some native mechanisms. My test initialize array with some random int data, and then use framework to find biggest element in array. In Groovy my compute functions looks like below:

@Override
Integer compute() {
  def size = end - start
  if (size == 1) {
    Math.max(array[start], array[end])
  } else {
    int diff = size / 2
    MaxValueSeeker left = 
      new MaxValueSeeker(array, start, start + diff)
    left.fork()
    MaxValueSeeker right = 
      new MaxValueSeeker(array, start + diff, end)
    Math.max(right.compute(), left.join())
  }
}

Java version is of course very similar. After dozen minutes of measuring I get very promising result: Groovy is slower only... 8 times :)

Now it's time to check some more realistic in everyday development. I choosed simple POJO/POGO (yeah) with few simple operations just to be sure, that JIT won't eliminate my code (and belive me he loves doing such jokes). My pseudo "business logic" method in groovy:

def int proceed(int reps) {
  List<GroovyPojo> list = new ArrayList<>()
  int sum = 0;
  reps.times {
    // first param is int and second is String
    list.add(new GroovyPojo(value: it, stringValue: it))
  }
  list.each {
    if (Integer.parseInt(it.stringValue) == it.value) {
      sum += it.value
    }
  }
  sum
}

Java version differs mostly by getters and manual String boxing in POJO constructor. One more time dozen minutes spent on reading news and... this time Groovy is slower only 7 times

The last test should be stressful and check both languages in more complex computations. I made up my mind and chose quicksort algorithm. Few loops, few if statements should work. I'm not going to copy-paste it here, because it's well known solution.  What is worth to mention is of course timing result, outdistancing Groovy almost 5 times! But I've done some googling and noticed that Groovy 2.0 introduced @CompileStatic annotation, which should give us some additional performance boost. So lets check... Yes, with static compilation Java advantage fell to 220%.

In the table below you can find detailed results. To sum up - I'm not sure that using Groovy in mission critical functions is a good idea, but definitely it's great solution for implementing tests, prototyping, etc. Just let me highlight, that writing Caliper's results parser taken about 6 lines in Groovy (parse json, iterate over measurements and count average)

Method Java [ns] Groovy [ns] Factor
Fork/Join 22.132 181.018 8.18
Pojos 117.914 856.337 7.26
Quicksort 68.728 330.159 4.80
Quicksort with @CompileStatic 67.752 147.792 2.18
Performance comparison

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Topics:
java ,groovy ,high-perf ,performance ,caliper ,microbenchmark

Published at DZone with permission of Jakub Kubrynski, DZone MVB. See the original article here.

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