C# 4 and .NET 4

264 ❘ ChaPTer 10 cOllectiOns
}
ev.Set();
});
producer.Start(
Tuple.Create < BlockingCollection < int > , ManualResetEventSlim > (
sharedCollection, events[0]));
var consumer = new Thread(obj = >
{
var state =
(Tuple < BlockingCollection < int > , ManualResetEventSlim > )obj;
var coll = state.Item1;
var ev = state.Item2;
for (int i = 0; i < 300; i++)
{
int result = coll.Take();
}
ev.Set();
});
consumer.Start(
Tuple.Create < BlockingCollection < int > , ManualResetEventSlim > (
sharedCollection, events[1]));
if (!WaitHandle.WaitAll(waits))
Console.WriteLine("wait failed");
else
Console.WriteLine("reading/writing finished");
code snippet ConcurrentSample/Program.cs
Using the concurrent collections really gets interesting as soon as multiple threads come
into play. This as well as the use of the CancellationToken is shown in Chapter 20.
The next chapter also gives information about using the concurrent collections with
Parallel LINQ.
PerformanCe
Many collection classes offer the same functionality as others; for example, SortedList offers nearly the
same features as SortedDictionary . However, often there ’ s a big difference in performance. Whereas one
collection consumes less memory, the other collection class is faster with retrieval of elements. In the MSDN
documentation, you often fi nd performance hints with methods of the collection giving you information
about the time the operation represents in big - O notation:
O(1)
O(log n)
O(n)
O(1) means that the time this operation needs is constant no matter how many items are in the collection.
For example, the ArrayList has an Add() method with O(1) behavior. No matter how many elements are
in the list, it always takes the same time when adding a new element to the end of the list. The Count property
gives the number of items, so it is easy to fi nd the end of the list.
www.it-ebooks.info