[gengstrand]

Most data focused microservices for business applications devote most of their code to calling databases. The PoC microservices that I implemented in order to evaluate Clojure use Java libraries to communicate with Cassandra, MySql, Redis, and Elastic Search. Clojure is not currently at a point in adoption where it makes a lot of sense for these database vendors to support native Clojure libraries.

While it is true that not every method calls goes through Java reflection, it is also safe to say that every API call to this kind of service will end up making a lot of calls via Java reflection unless you use types hints all over the place in the DAOs.

[didibus]

The reflection lookup takes about 0.04 msecs extra on my laptop.

When you're doing things like I/O, an extra 0.04 milliseconds won't matter much, since the operation is already a lot slower then that. So hinting in those case generally isn't really needed, as it won't cause visible performance gains in your application.

Where hinting is worth it, is in tight loops where 0.04 ms will add up. Numeric code that uses arrays especially benefits, since the benefits of the array are lost to the reflection overhead otherwise.

[gengstrand]

Your claim, that the latency cost of reflection is small in comparison to the latency of performing I/O, seems reasonable assuming that the service is processing only one request at a time. That is not the case for typical microservice architectures and certainly not what is happening in the load test by which each of these service implementations are compared.

There is an upper limit of requests to which any service can handle concurrently. Usually, that limit is based on memory but there could be other factors too. After that upper limit is reached, additional requests wait in a queue or get rejected. From Little's Law, we know that the number of requests in any system is the product of the rate of ingress and the average time it takes to service a request. Since that number of requests is bounded, even small increases in the average process time can have a significant negative impact on the ingress rate that the service can sustainable handle. If you are not familiar with queuing theory, then perhaps you have heard of onlooker delay being the major cause of traffic jams.

Is running Clojure services with Java reflection the end of the world? Of course not. Just be aware that it does make performance for those kind of services look not quite as efficient when compared with services that do not use Java reflection.

[raspasov]

For sure. YourKit is an excellent piece of software to discover the hot spots in the code that are the bottleneck in such cases. It takes just a few minutes to discover and add the type hints in the proper places.