I assumed lambda functions
, delegates
and anonymous functions
with the same body would have the same "speed", however, running the following simple program:
static void Main(string[] args)
{
List<int> items = new List<int>();
Random random = new Random();
for (int i = 0; i < 10000000; i++)
{
items.Add(random.Next());
}
Stopwatch watch;
IEnumerable<int> result;
Func<int, bool> @delegate = delegate(int i)
{
return i < 500;
};
watch = Stopwatch.StartNew();
result = items.Where(@delegate);
watch.Stop();
Console.WriteLine("Delegate: {0}", watch.Elapsed.TotalMilliseconds);
Func<int, bool> lambda = i => i < 500;
watch = Stopwatch.StartNew();
result = items.Where(lambda);
watch.Stop();
Console.WriteLine("Lambda: {0}", watch.Elapsed.TotalMilliseconds);
watch = Stopwatch.StartNew();
result = items.Where(i => i < 500);
watch.Stop();
Console.WriteLine("Inline: {0}", watch.Elapsed.TotalMilliseconds);
Console.ReadLine();
}
I get:
Delegate: 4.2948 ms
Lambda: 0.0019 ms
Anonymous: 0.0034 ms
Although negligible, why are these three - apparently identical - methods running at different speeds? What's happening under the hood?
Update:
As suggested by the comments, the following "forces" the Where
by calling ToList()
on it. In addition, a loop is added to offer more run data:
while (true)
{
List<int> items = new List<int>();
Random random = new Random();
for (int i = 0; i < 10000000; i++)
{
items.Add(random.Next());
}
Stopwatch watch;
IEnumerable<int> result;
Func<int, bool> @delegate = delegate(int i)
{
return i < 500;
};
watch = Stopwatch.StartNew();
result = items.Where(@delegate).ToList();
watch.Stop();
Console.WriteLine("Delegate: {0}", watch.Elapsed.TotalMilliseconds);
Func<int, bool> lambda = i => i < 500;
watch = Stopwatch.StartNew();
result = items.Where(lambda).ToList();
watch.Stop();
Console.WriteLine("Lambda: {0}", watch.Elapsed.TotalMilliseconds);
watch = Stopwatch.StartNew();
result = items.Where(i => i < 500).ToList();
watch.Stop();
Console.WriteLine("Inline: {0}", watch.Elapsed.TotalMilliseconds);
Console.WriteLine(new string('-', 12));
}
The above code results in ~120 ms for each function.
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Anonymous objects are faster than named objects. But calling more functions is more expensive, and to a degree which eclipses any savings you might get from using anonymous functions. Each function called adds to the call stack, which introduces a small but non-trivial amount of overhead.
Anonymous Method is an inline code that can be used wherever a delegate type is expected. Microsoft introduced Anonymous Methods in C# 2.0 somewhere around 2003. Lambda expression is an anonymous method that you can use to create delegates or expression tree types.
In Python, an anonymous function is a function that is defined without a name. While normal functions are defined using the def keyword in Python, anonymous functions are defined using the lambda keyword. Hence, anonymous functions are also called lambda functions.
Other peoples results suggest that the performance is the same:
http://blogs.microsoft.co.il/blogs/alex_golesh/archive/2007/12/11/anonymous-delegates-vs-lambda-expressions-vs-function-calls-performance.aspx
As noted in the comments, micro-benchmarks are often misleading. There are too many factors over which you have no control, JIT optimisation, garbage collection cycles, etc ...
See this related question:
When not to use lambda expressions
Finally, I think your test is fundamentally flawed! You use a Linq Where
extension method to execute your code. However, Linq uses lazy-evaluation, your code will only be executed if you start iterating over the results!
A lambda expression is an anonymous function. "Anonymous function" refers to either a lambda expression or an anonymous method (which is what you've called a "delegate" in your code).
All three operations are using delegates. The second and third are both using lambda expressions. All three will execute in the same way, with the same performance characteristics.
Note that there can be a difference in performance between:
Func<int, int> func = x => ...;
for (int i = 0; i < 10000; i++) {
CallFunc(func);
}
and
for (int i = 0; i < 10000; i++) {
CallFunc(x => ...) // Same lambda as before
}
It depends on whether the compiler is able to cache the delegate created by the lambda expression. That will in turn depend on whether it captures variables etc.
For example, consider this code:
using System;
using System.Diagnostics;
class Test
{
const int Iterations = 1000000000;
static void Main()
{
AllocateOnce();
AllocateInLoop();
}
static void AllocateOnce()
{
int x = 10;
Stopwatch sw = Stopwatch.StartNew();
int sum = 0;
Func<int, int> allocateOnce = y => y + x;
for (int i = 0; i < Iterations; i++)
{
sum += Apply(i, allocateOnce);
}
sw.Stop();
Console.WriteLine("Allocated once: {0}ms", sw.ElapsedMilliseconds);
}
static void AllocateInLoop()
{
int x = 10;
Stopwatch sw = Stopwatch.StartNew();
int sum = 0;
for (int i = 0; i < Iterations; i++)
{
sum += Apply(i, y => y + x);
}
sw.Stop();
Console.WriteLine("Allocated in loop: {0}ms", sw.ElapsedMilliseconds);
}
static int Apply(int loopCounter, Func<int, int> func)
{
return func(loopCounter);
}
}
The compiler is smart, but there's still a difference. Using Reflector, we can see that AllocateInLoop
is effectively compiled to:
private static void AllocateInLoop()
{
Func<int, int> func = null;
int x = 10;
Stopwatch stopwatch = Stopwatch.StartNew();
int sum = 0;
for (int i = 0; i < Iterations; i++)
{
if (func == null)
{
func = y => y + x;
}
sum += Apply(i, func);
}
stopwatch.Stop();
Console.WriteLine("Allocated in loop: {0}ms", stopwatch.ElapsedMilliseconds);
}
So still only a single delegate instance is created, but there's extra logic within the loop - an extra nullity test on each iteration, basically.
On my machine that makes about a 15% difference in performance.
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