How to replace FirstOrDefault with something like RandomOrDefault to "balance" calls?
I have such code
senders.FirstOrDefault(sender => !sender.IsBusy);
This line is called pretty often.
The problem is that it always returns the first non-busy sender
; the same first sender is returned pretty often, but the last one is returned very rarely. How to easily balance this?
Ideally, on every call I should return the most rarely used sender. I.e. between all non-busy senders select the one that was selected t开发者_Python百科he least number of times during the last second.
Maybe something like:
public static T RandomOrDefault<T>(this IEnumerable<T> dataSet)
{
return dataSet.RandomOrDefault(y => true);
}
public static T RandomOrDefault<T>(this IEnumerable<T> dataSet, Func<T, bool> filter)
{
var elems = dataSet.Where(filter).ToList();
var count = elems.Count;
if (count == 0)
{
return default(T);
}
var random = new Random();
var index = random.Next(count - 1);
return elems[index];
}
then you can call it with:
senders.RandomOrDefault(sender => !sender.IsBusy);
If you want to get the least used one efficiently you will be probably good with the following non-Linq 'list rotation' solution, which is O(n)
effiency and O(1)
space unlike most of others:
// keep track of these
List<Sender> senders;
int nSelected = 0; // number of already selected senders
// ...
// solution
int total = senders.Count; // total number of senders
// looking for next non-busy sender
Sender s = null;
for (int i = 0; i < total; i++)
{
int ind = (i + nSelected) % total; // getting the one 'after' previous
if (!senders[ind].IsBusy)
{
s = senders[ind];
++nSelected;
break;
}
}
Of course this adds the must-be-indexable constraint on senders
container.
You could easily reorder by a new Guid, like this:
senders.Where(sender => !sender.IsBusy).OrderBy(x => Guid.NewGuid()).FirstOrDefault();
You don't mess with random numbers, you don't have to identify a "range" for these numbers. It just plain works and it's pretty elegant, I think.
You could use the "Shuffle" extension method from this post before your FirstOrDefault
You could use Skip with a random number less than the total number of non-busy senders.
senders.Where(sender => !sender.IsBusy).Skip(randomNumber).FirstOrDefault();
Identifying a sensible limit for the random number might be a bit tricky though.
Keep a look-up of senders that you have used and the time when they were used.
var recentlyUsed = new Dictionary<Sender, DateTime>();
var sender = senders.FirstOrDefault(sender => !sender.IsBusy && (!recentlyUsed.ContainsKey(sender) || recentlyUsed[sender] < DateTime.Now.AddSeconds(-1)));
if (sender != null)
recentlyUsed[sender] = DateTime.Now;
Based on algorithm from the "Real world functional programming" book here's the O(n) implementation of extension method for taking random or default value from IEnumearble.
public static class SampleExtensions
{
// The Random class is instantiated as singleton
// because it would give bad random values
// if instantiated on every call to RandomOrDefault method
private static readonly Random RandomGenerator = new Random(unchecked((int)DateTime.Now.Ticks));
public static T RandomOrDefault<T>(this IEnumerable<T> source, Func<T, bool> predicate)
{
IEnumerable<T> filtered = source.Where(predicate);
int count = 0;
T selected = default(T);
foreach (T current in filtered)
{
if (RandomGenerator.Next(0, ++count) == 0)
{
selected = current;
}
}
return selected;
}
public static T RandomOrDefault<T>(this IEnumerable<T> source)
{
return RandomOrDefault(source, element => true);
}
}
Here's the code to ensure that this algorithm really gives the Uniform distribution:
[Test]
public void TestRandom()
{
IEnumerable<int> source = Enumerable.Range(1, 10);
Dictionary<int, int> result = source.ToDictionary(element => element, element => 0);
result[0] = 0;
const int Limit = 1000000;
for (int i = 0; i < Limit; i++)
{
result[source.RandomOrDefault()]++;
}
foreach (var pair in result)
{
Console.WriteLine("{0}: {1:F2}%", pair.Key, pair.Value * 100f / Limit);
}
Console.WriteLine(Enumerable.Empty<int>().RandomOrDefault());
}
The output of TestRandom method is:
1: 9,92%
2: 10,03%
3: 10,04%
4: 9,99%
5: 10,00%
6: 10,01%
7: 9,98%
8: 10,03%
9: 9,97%
10: 10,02%
0: 0,00%
0
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