Parallel or async ASP.NET Core C#

Question

I've googled this plenty but I'm afraid I don't fully understand the consequences of concurrency and parallelism.

I have about 3000 rows of database objects that each have an average of 2-4 logical data attached to them that need to be validated as a part of a search query, meaning the validation service needs to execute approx. 3*3000 times. E.g. the user has filtered on color then each row needs to validate the color and return the result. The loop cannot break when a match has been found, meaning all logical objects will always need to be evaluated (this is due to calculations of relevance and just not a match).

This is done on-demand when the user selects various properties, meaning performance is key here.

I'm currently doing this by using Parallel.ForEach but wonder if it is smarter to use async behavior instead?

Current way

var validatorService = new LogicalGroupValidatorService();
ConcurrentBag<StandardSearchResult> results = new ConcurrentBag<StandardSearchResult>();
Parallel.ForEach(searchGroups, (group) =>
{
    var searchGroupResult = validatorService.ValidateLogicGroupRecursivly(
        propertySearchQuery, group.StandardPropertyLogicalGroup);
    result.Add(new StandardSearchResult(searchGroupResult));
});

Async example code

var validatorService = new LogicalGroupValidatorService();
List<StandardSearchResult> results = new List<StandardSearchResult>();
var tasks = new List<Task<StandardPropertyLogicalGroupSearchResult>>();

foreach (var group in searchGroups)
{
    tasks.Add(validatorService.ValidateLogicGroupRecursivlyAsync(
        propertySearchQuery, group.StandardPropertyLogicalGroup));
}

await Task.WhenAll(tasks);

results = tasks.Select(logicalGroupResultTask => 
    new StandardSearchResult(logicalGroupResultTask.Result)).ToList();

Since you seem to have both versions implemented, what does it look like if you measure execution times of both? — Risto M
– Risto M, Commented Feb 27, 2018 at 9:22
Did you measure the difference in performance? That is the only way to be sure. That said, my guess is that parallel should perform better in this case as async is mainly "do not block the main thread while waiting on other systems" — Hans Keﬆing
– Hans Keﬆing, Commented Feb 27, 2018 at 9:23
So does ValidateLogicGroupRecursivly work with database or everything is done in memory? — Evk
– Evk, Commented Feb 27, 2018 at 9:32
For 3000 or 9000 rows it doesn't matter, unless you are doing some roundtrips to the database or any CPU heavy work per row its not going to matter. 9000 iterations of a loop to calculate some simple formula or value is nothing for todays computers. Unless you have measured real world bottle neck issues on it, just do it on a single thread. starting/queuing too many threads in ASP.NET Core may actually lower your overall performance instead of increasing it (ASP.NET Core starts rejecting connections in a high-traffic situation when it runs out of (queued) threads) — Tseng
– Tseng, Commented Feb 27, 2018 at 9:33
And if you have to do any roundtrips to the DB there may be better ways to solve it (find out the values you need in code and fetch then all in a single query, then perform the calculation locally) (Heavy CPU means like 1-2 ms per row, so that the whole calculation would take 9 to 18 seconds. Typical calculations on todays CPUs are in the range of ns, so 9000 records making no big difference if it takes 1 or 2 ms) — Tseng
– Tseng, Commented Feb 27, 2018 at 9:36

Kenneth · Accepted Answer · 2018-02-27 09:29:53Z

3

The difference between parallel and async is this:

Parallel: Spin up multiple threads and divide the work over each thread
Async: Do the work in a non-blocking manner.

Whether this makes a difference depends on what it is that is blocking in the async-way. If you're doing work on the CPU, it's the CPU that is blocking you and therefore you will still end up with multiple threads. In case it's IO (or anything else besides the CPU, you will reuse the same thread)

For your particular example that means the following:

Parallel.ForEach => Spin up new threads for each item in the list (the nr of threads that are spun up is managed by the CLR) and execute each item on a different thread

async/await => Do this bit of work, but let me continue execution. Since you have many items, that means saying this multiple times. It depends now what the results:

If this bit of workis on the CPU, the effect is the same
Otherwise, you'll just use a single thread while the work is being done somewhere else

answered Feb 27, 2018 at 9:29

Kenneth

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5 Comments

Max Over a year ago

Based on the other comments (where starting 3000 tasks isn't the smartest to do), would it be better to wrap a standard foreach (replacing the Parallel.ForEach) in a Task.Run() and await that task? Meaning creating only one task per 9000 iteration request, if I understand it correctly.

Tseng Over a year ago

@Max: You gain no advantage of doing this. You just free the request thread and use another thread from the pool. So thread usage is same as if you do it on the request thread, except that you get the little bit of threadpool management overhead on switching the thread. It's perfectly fine to do CPU bound work on the ASP.NET Core request thread

Max Over a year ago

@Tseng, so in essence, it could be as easy as:

var results = searchGroups.Select(group => new StandardSearchResult(validatorService.ValidateLogicGroupRecursivly(propertySearchQuery, group.StandardPropertyLogicalGroup))).ToList();

and just be happy with it?

Kenneth Over a year ago

@Max The key here is measuring the performance. That means not only the performance when you run it for a single user, but also what happens if you need to do this for multiple users at the same time. With one user, most likely it'll be faster to do it in parallel, with multiple users, you might get a different result (depending on how CPU heavy it is).

vgru Over a year ago

This is a bit misleading, because 1) Parallel.ForEach does not spin up new threads, it uses tasks from the thread pool, and 2) calling async/await on Task.WhenAll cannot possibly use a single thread, on the contrary, Task.WhenAll(tasks) will always create tasks.Count tasks.

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