Play Framework: What happens when requests exceeds the available threads - multithreading

Question

I have one thread in the thread-pool servicing blocking request.
def sync = Action {
import Contexts.blockingPool
Future {
Thread.sleep(100)
}
Ok("Done")
}
In Contexts.blockingPool is configured as:
custom-pool {
fork-join-executor {
parallelism-min = 1
parallelism-max = 1
}
}
In theory, if above request receives 100 simultaneous requests, the expected behaviour should be: 1 request should sleep(100) and rest of 99 requests should be rejected (or queued until timeout?). However I observed that extra worker threads are created to service rest of requests. I also observed that latency increases as (gets slower to service request) as number of threads in the pool gets smaller than the requests received.
What is expected behavior if a request larger than configured thread-pool size is received?

Answer 1

Your test is not correctly structured to test your hypothesis.
If you go over this section in the docs you will see that Play has a few thread pools/execution contexts. The one that is important with regards to your question is the default thread pool and how that relates to the HTTP requests served by your action.
As the doc describes, the default thread pool is where all application code is run by default. I.e. all action code, including all Future's (not explicitly defining their own execution context), will run in this execution context/thread pool. So using your example:
def sync = Action {
// *** import Contexts.blockingPool
// *** Future {
// *** Thread.sleep(100)
// ***}
Ok("Done")
}
All the code in your action not commented by // *** will run in the default thread pool.
I.e. When a request gets routed to your action:
the Future with the Thread.sleep will be dispatched to your custom execution context
then without waiting for that Future to complete (because it's running in it's own thread pool [Context.blockingPool] and therefore not blocking any threads on the default thread pool)
your Ok("Done") statement is evaluated and the client receives the response
Approx. 100 milliseconds after the response has been received, your Future completes
So to explain you observation, when you send 100 simultaneous requests, Play will gladly accept those requests, route to your controller action (executing on the default thread pool), dispatch to your Future and then respond to the client.
The default size of the default pool is
play {
akka {
...
actor {
default-dispatcher = {
fork-join-executor {
parallelism-factor = 1.0
parallelism-max = 24
}
}
}
}
}
to use 1 thread per core up to a max of 24.
Given that your action does very little (excl. the Future), you will be able to handle into the 1000's of requests/sec without a sweat. Your Future will however take much longer to work through the backlog because you are blocking the only thread in your custom pool (blockingPool).
If you use my slightly adjusted version of your action, you will see what confirms the above explanation in the log output:
object Threading {
def sync = Action {
val defaultThreadPool = Thread.currentThread().getName;
import Contexts.blockingPool
Future {
val blockingPool = Thread.currentThread().getName;
Logger.debug(s"""\t>>> Done on thread: $blockingPool""")
Thread.sleep(100)
}
Logger.debug(s"""Done on thread: $defaultThreadPool""")
Results.Ok
}
}
object Contexts {
implicit val blockingPool: ExecutionContext = Akka.system.dispatchers.lookup("blocking-pool-context")
}
All your requests are swiftly dealt with first and then your Future's complete one by one afterwards.
So in conclusion, if you really want to test how Play will handle many simultaneous requests with only one thread handling requests, then you can use the following config:
play {
akka {
akka.loggers = ["akka.event.Logging$DefaultLogger", "akka.event.slf4j.Slf4jLogger"]
loglevel = WARNING
actor {
default-dispatcher = {
fork-join-executor {
parallelism-min = 1
parallelism-max = 1
}
}
}
}
}
you might also want to add a Thread.sleep to your action like this (to slow the default thread pools lonesome thread down a bit)
...
Thread.sleep(100)
Logger.debug(s"""<<< Done on thread: $defaultThreadPool""")
Results.Ok
}
Now you will have 1 thread for requests and 1 thread for your Future's.
If you run this with high concurrent connections you will notice that the client blocks while Play handles the requests one by one. Which is what you expected to see...

Answer 2

Play uses AkkaForkJoinPool which extends scala.concurrent.forkjoin.ForkJoinPool.
It has internal queue of tasks.
You may also find this description interesting in respect to handling blocking code by fork-join-pool: Scala: the global ExecutionContext makes your life easier