public void train(int topN)
{
_topN = topN;
_randomRecommends = ArrayView<string>.Create(primeNumber * topN);
var isbns = trainData.Select(e => e.ISBN).Distinct().ToArray();
Parallel.ForEach(Enumerable.Range(0, primeNumber), new ParallelOptions { MaxDegreeOfParallelism = 4 }, seed =>
{
var rand = new Random(seed);
var visited = new HashSet<int>();
var view = _randomRecommends.SubArray(seed* topN, _topN);
var viewIndex = 0;
while (viewIndex < topN)
{
var isbnIndex = rand.Next(isbns.Length);
if (!visited.Add(isbnIndex))
continue;
view[viewIndex++] = isbns[isbnIndex];
}
});
}
