I'm trying to benchmark akka http client before adding it to one of my
projects.
It's making a series of outbound HTTP requests through a MergeHub to a
SuperPool. And, I'd like to be able to max out my laptops CPU usage but for
some reason it never passes 1700 requests per second or 14% cpu usage. I've
tried both the PinnedDispatcher and the blocking dispatcher from the
blocking I/O docks without making much of a difference.
The average latency per request is around 150ms
1700 cant be the maximum. Is there something I'm missing?
```
# The maximum number of parallel connections that a connection pool to a
# single host endpoint is allowed to establish. Must be greater than zero.
max-connections = 1024
# The minimum number of parallel connections that a pool should keep alive
("hot").
# If the number of connections is falling below the given threshold, new ones
are being spawned.
# You can use this setting to build a hot pool of "always on" connections.
# Default is 0, meaning there might be no active connection at given moment.
# Keep in mind that `min-connections` should be smaller than `max-connections`
or equal
min-connections = 128
# The maximum number of times failed requests are attempted again,
# (if the request can be safely retried) before giving up and returning an
error.
# Set to zero to completely disable request retries.
max-retries = 1
# The maximum number of open requests accepted into the pool across all
# materializations of any of its client flows.
# Protects against (accidentally) overloading a single pool with too many
client flow materializations.
# Note that with N concurrent materializations the max number of open request
in the pool
# will never exceed N * max-connections * pipelining-limit.
# Must be a power of 2 and > 0!
max-open-requests = 1024
```
```
pinned-dispatcher {
executor = "thread-pool-executor"
type = PinnedDispatcher
}
```
```
blocking-request-dispatcher = {
# Dispatcher is the name of the event-based dispatcher
type = Dispatcher
# What kind of ExecutionService to use
executor = "thread-pool-executor"
# Configuration for the thread pool
thread-pool-executor {
fixed-pool-size = 1024
# minimum number of threads to cap factor-based core number to
core-pool-size-min = 1024
# No of core threads ... ceil(available processors * factor)
core-pool-size-factor = 2.0
# maximum number of threads to cap factor-based number to
core-pool-size-max = 1024
}
# Throughput defines the maximum number of messages to be
# processed per actor before the thread jumps to the next actor.
# Set to 1 for as fair as possible.
throughput = 100
}
```
```
val throttleRate: Int = 500
val totalRequest: Int = 10000
Future {
Source(1 to totalRequest)
.map(MockRequestFactory.buildRawRequest)
.throttle(throttleRate, 1 second, throttleRate, ThrottleMode.Shaping)
.runWith(requestQueue.sink)
}
Future {
Source(1 to totalRequest)
.map(MockRequestFactory.buildRawRequest)
.throttle(throttleRate, 1 second, throttleRate, ThrottleMode.Shaping)
.runWith(requestQueue.sink)
}
```
```
val sink: MediationReqSink =
MergeHub.source[MediationRequestQueue](perProducerBufferSize =* 1024*)
.map[MediationRequestQueue] { requestAndResponse =>
val timer = ddMonitor.getTimer(s"$metricName.responseTime")
requestAndResponse._2.future.onComplete(x => timer.stop)
requestAndResponse
}
.via(Http().superPool[Promise[MediationResponse]]())
.withAttributes(
ActorAttributes.supervisionStrategy(decider)
).toMat(Sink.foreach({
case (Success(res: HttpResponse), p: Promise[MediationResponse]) =>
ddMonitor.increment(s"$metricName.responseCount[status: success]")
p.complete(LogTry(deserialize(res))).future
case (Failure(err: Throwable), _) =>
ddMonitor.increment(s"$metricName.responseCount[status: failure]")
Future.failed(err)
}))(Keep.left).run
```
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