C# – Should a c# dev switch to VB.net when the team language base is mixed

In my firm we are using the EF. It's a nice ORM, suitable for our small project. In reality people are using EF or NHibernate. Both frameworks are good. EF has a great MS support and you can find great tools bundled with Visual Studio. NHibernate is considered better than EF but there is a bigger "learning curve" so you will spend more time adopting it.

I think that, if you are on the Ado.Net "classic" try the EF. Create a simple project and replace some of the DAL methods. Check how it works and how you can manage/modify the code. Compare it with the simple "SqlDataReader" methods and decide which is better. Remember that every technology shift needs some time for adoption so you have to calculate if this change will be beneficial for your company in the long run.

I'd say the main weakness of this answer is less its use of Linq and more the specific operators chosen. GroupBy takes each element and projects it to a key and a value which go into a lookup. In other words, every word will add something to the lookup.

The naive implementation .GroupBy(e => e) will store a copy of every word in the source material, making the final lookup nearly as large as the original source material. Even if we project out the value with .GroupBy(e => e, e => null) we're creating a large lookup of small values.

What we would want is an operator that preserves only the needed information, which is one copy of each word and the count of that word so far. For that, we can use Aggregate:

words.Aggregate(new Dictionary<string, int>(), (counts, word) => 
{
    int currentCount;
    counts.TryGetValue(word, currentCount);
    counts[word] = currentCount + 1;
    return counts;
} 

From here, there are several ways we could attempt to make this faster:

1. Instead of creating many strings while splitting, we could pass around structs that reference the original string and the segment that contains the word, and only copy the segment out when it turns out to be a unique key
2. Use Parallel Linq to aggregate across several cores then combine the results. This is trivial compared to the leg work required for doing this by hand.