Mapster VS BenchmarkDotNet

🔴 [Mapster] A fast, fun and stimulating object to object Mapper! Mapster was designed to be efficient on both speed and memory. You could gain a 4x performance improvement whilst using only 1/3 of memory.

Mapster

Have you read this part in their documentation? https://github.com/MapsterMapper/Mapster/wiki/Data-types

Which is the main reason I don't use it anymore. I can still stand behind why it was created and what it was trying to solve. If you still want to use a mapper I would recommend Mapster as it supports source generation so you can see all code and it's references.

Gotta add a shoutout to Mapster which does pretty much the same thing also using source generation.

I highly recommend Mapster (https://github.com/MapsterMapper/Mapster)

We use Mapster coupled with FastExpressionCompiler and have been very happy with it.

Try Mapster

I hope I managed to convince you and proved the value of unit tests for mappings, so let's move on to the next example. We're going to use AutoMapper, but from a testing standpoint, the choice of mapper makes no difference. For instance, we can replace AutoMapper with Mapster and it won't affect our tests in any way. Moreover, the existing tests will indicate whether our mapping refactoring was successful or not, which is one of the points of having unit tests 🙂

Let’s look at the first example you see, when you open up BenchmarkDotnet’s website, or Github page.

Or use BenchmarkDotNet which, among other things to get an accurate benchmark, does JIT warmup outside of measurement.

( https://github.com/dotnet/BenchmarkDotNet ).

You can also do proper statistically correct benchmarking by using - https://github.com/dotnet/BenchmarkDotNet. This will run warmup the jit, gauge the overheads, and run your function many times to give you proper data.

take a look at: https://benchmarkdotnet.org/

Yes, weak references are slower than direct calls. How much slower? Heck if I know offhand. But it's usually pretty easy to set up something with Benchmark .NET and find out if it hurts your use case.

For this purpose we are going to use our beloved BenchmarkDotNet tool.

To quantify and compare the performance of the object mapping strategies discussed earlier, we can employ BenchmarkDotNet.

BenchmarkDotNet is a popular open-source library that, as stated in the repo's README.md, helps us to transform methods into benchmarks, track their performance, and share reproducible measurement experiments. Using BenchmarkDotNet feels similar to writing unit tests. It's very important to note that the library only works with console apps. Finally, we can visualize the results in the terminal where the benchmark ran or in user-friendly formats such as markdown, HTML and CSV. We will explore examples of there formats later in the article.

However, obviously this prevents parallelism within the lock, so this only makes sense if you do some other expensive operation in the parallel loop and the string builder is only a small part of it. Performance wise, it may be better to concatenate the results together after the parallel operation, instead of locking inside the loop. You'll have to benchmark it to know for sure.

We’re of course going to be using BenchmarkDotNet for our benchmarks, and you can find all of the code for these over at GitHub. To start, we need an entry point hook for our single Benchmark class that will be defining the permutations of scenarios that we’d like to run. This will be relatively basic as follows: