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Note: don’t forget to check out the Benchmarks page to see the latest round up of binary and JSON serializers.
When working with the BinaryFormatter class frequently, one of the things you notice is that it is really damn inefficient… both in terms of speed as well as the payload (the size of the serialized byte array).
Google’s Protocol Buffers format is designed to be super fast and minimizes the payload by requiring a serializable object to define ahead of time the order in which its properties/fields should be serialized/deserialized in, doing so removes the need for all sorts of metadata that traditionally need to be encoded along with the actual data.
Marc Gravell (of StackOverflow fame!) has a .Net implementation called ‘protobuf-net‘, and is said to totally kick ass! As with most performance related topics, it’s hugely intriguing to me so I decided to put it to test myself :-)
Assumptions/Conditions of tests
- code is compiled in release mode, with optimization option turned on
- 5 runs of the same test is performed, with the top and bottom results excluded, the remaining three results is then averaged
- 100,000 identical instances of type SimpleObject(see below) is serialized and deserialized
- serialization/deserializatoin of the objects happen sequentially in a loop (no concurrency)
Unsurprisingly, the protobuf-net serializer wins hands-down in all three categories, as you can see from the table below it is a staggering 12x faster than BinaryFormatter when it comes to serialization, with a payload size less than 15th of its counterpart’s.
One curious observation about the payload size is that, when I used a BinaryWriter to simply write every property into the output stream without any metadata, what I got back should be the minimum payload size without compression, and yet the protobuf-net serializer still manages to beat that!
BinaryFormatter with ISerializable
I also tested the BinaryFormatter with a class that implements the ISerializable interface (see below) because others had suggested in the past that you are likely to get a noticeable performance boost if you implement the ISerializable interface yourself. The belief is that it will perform much better as it removes the reliance on reflection which can be detrimental to the performance of your code when used excessively.
However, based on the tests I have done, this does not seem to be the case, the slightly better serialization speed is far from conclusive and is offset by a slightly slower deserialization speed..
If you’re interested in running the tests yourself, you can find the source code here, it uses my SimpleSpeedTester framework to orchestrate the test runs but you should be able to get the gist of it fairly easily.
As I mentioned in the post, protobuf-net managed to produce a smaller payload than what is required to hold all the property values of the test object without any meta.
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Here is a complete list of all my posts on serverless and AWS Lambda. In the meantime, here are a few of my most popular blog posts.
- Lambda optimization tip – enable HTTP keep-alive
- You are thinking about serverless costs all wrong
- Many faced threats to Serverless security
- We can do better than percentile latencies
- I’m afraid you’re thinking about AWS Lambda cold starts all wrong
- Yubl’s road to Serverless
- AWS Lambda – should you have few monolithic functions or many single-purposed functions?
- AWS Lambda – compare coldstart time with different languages, memory and code sizes
- Guys, we’re doing pagination wrong