private static IEnumerable <LabeledOperation> UnorderedRangeSources()
{
// The difference between this and the existing sources is more control is needed over the range creation.
// Specifically, start/count won't be known until the nesting level is resolved at runtime.
yield return(Label("ParallelEnumerable.Range", (start, count, ignore) => ParallelEnumerable.Range(start, count)));
yield return(Label("Enumerable.Range", (start, count, ignore) => Enumerable.Range(start, count).AsParallel()));
yield return(Label("Array", (start, count, ignore) => UnorderedSources.GetRangeArray(start, count).AsParallel()));
yield return(Label("Partitioner", (start, count, ignore) => Partitioner.Create(UnorderedSources.GetRangeArray(start, count)).AsParallel()));
yield return(Label("List", (start, count, ignore) => UnorderedSources.GetRangeArray(start, count).ToList().AsParallel()));
yield return(Label("ReadOnlyCollection", (start, count, ignore) => new ReadOnlyCollection <int>(UnorderedSources.GetRangeArray(start, count).ToList()).AsParallel()));
}
/// <summary>
/// Get a a combination of partitioned data sources, degree of parallelism, expected resulting dop,
/// query to execute on the data source, and mode of execution.
/// </summary>
/// <param name="dop">A set of the desired degrees of parallelism to be employed.</param>
/// <returns>Entries for test data.
/// The first element is the Labeled{ParallelQuery{int}} data source,
/// the second is the desired dop,
/// the third is the expected resulting dop,
/// the fourth is the query to execute on the data source,
/// and the fifth is the execution mode.</returns>
public static IEnumerable <object[]> WithExecutionModeQueryData(int[] dops)
{
foreach (int dop in dops)
{
// Use data sources that have a fixed set of elements in each partition (no load balancing between the partitions).
// PLINQ will assign a Task to each partition, and no other task will process that partition. As a result, we can
// verify that we get a known number of tasks doing the processing. (This doesn't guarantee that such tasks are
// running in parallel, but it's "good enough". If PLINQ's implementation is ever changed to proactively exit
// tasks and spawn replicas to continue the processing, ala Parallel.For*, this test will need to be updated.)
int count = 3 * dop; // 3 chosen arbitrarily as a small value; any positive value will do
var partitionedRanges = new Labeled <ParallelQuery <int> >[]
{
Labeled.Label("ParallelEnumerable.Range", ParallelEnumerable.Range(0, count)),
Labeled.Label("Partitioner.Create", Partitioner.Create(UnorderedSources.GetRangeArray(0, count), loadBalance: false).AsParallel())
};
// For each source and mode, get both unordered and ordered queries that should easily parallelize for all execution modes
foreach (ParallelExecutionMode mode in new[] { ParallelExecutionMode.Default, ParallelExecutionMode.ForceParallelism })
{
foreach (Labeled <ParallelQuery <int> > source in partitionedRanges)
{
foreach (var query in EasyUnorderedQueries(count))
{
yield return new object[] { source, dop, dop, query, mode }
}
;
foreach (var query in EasyOrderedQueries(count))
{
yield return new object[] { source.Order(), dop, dop, query, mode }
}
;
}
}
// For each source, get queries that are difficult to parallelize and thus only do so with ForceParallelism.
foreach (Labeled <ParallelQuery <int> > source in partitionedRanges)
{
foreach (var query in HardQueries(count))
{
yield return(new object[] { source, dop, dop, query, ParallelExecutionMode.ForceParallelism }); // should parallelize, thus expected DOP of > 1
yield return(new object[] { source, dop, 1, query, ParallelExecutionMode.Default }); // won't parallelize, thus expected DOP of 1
}
}
}
}
public static IEnumerable <object[]> NotLoadBalancedDegreeData(int[] counts, int[] degrees)
{
foreach (object[] results in DegreeData(counts, degrees))
{
Labeled <ParallelQuery <int> > query = (Labeled <ParallelQuery <int> >)results[0];
if (query.ToString().StartsWith("Partitioner"))
{
yield return(new object[] { Labeled.Label(query.ToString(), Partitioner.Create(UnorderedSources.GetRangeArray(0, (int)results[1]), false).AsParallel()), results[1], results[2] });
}
else if (query.ToString().StartsWith("Enumerable.Range"))
{
yield return(new object[] { Labeled.Label(query.ToString(), new StrictPartitioner <int>(Partitioner.Create(Enumerable.Range(0, (int)results[1]), EnumerablePartitionerOptions.NoBuffering), (int)results[1]).AsParallel()), results[1], results[2] });
}
else
{
yield return(results);
}
}
}
public static IEnumerable <object[]> AggregateExceptionData(int[] counts)
{
foreach (object[] results in UnorderedSources.Ranges(counts.Cast <int>()))
{
Labeled <ParallelQuery <int> > query = (Labeled <ParallelQuery <int> >)results[0];
if (query.ToString().StartsWith("Partitioner"))
{
yield return(new object[] { Labeled.Label(query.ToString(), Partitioner.Create(UnorderedSources.GetRangeArray(0, (int)results[1]), false).AsParallel()), results[1] });
}
else if (query.ToString().StartsWith("Enumerable.Range"))
{
yield return(new object[] { Labeled.Label(query.ToString(), new StrictPartitioner <int>(Partitioner.Create(Enumerable.Range(0, (int)results[1]), EnumerablePartitionerOptions.None), (int)results[1]).AsParallel()), results[1] });
}
else
{
yield return(results);
}
}
}