At API there is:
val http = Http.configure(_
.setConnectionTimeoutInMs(1)
)
What for is this config? I use it with:
.setMaxRequestRetry(0)
I fought I will get failed future after timeout. Future I create like that:
val f = http(u OK as.String)
f.map {
NotificationClientConnectionParams.parseFromString
}
But instead of failure I get success long after my timeout.
How it should work?
My test looks like this:
val startTime = java.time.LocalTime.now()
val f = TcpUtil2.registerClientViaDispatch(ClientHeaders("12345", "123456789"))
f onSuccess {
case c =>
println(s"Success: $c")
println(java.time.Duration.between(startTime, java.time.LocalTime.now()).toMillis)
}
f onFailure {
case e =>
println(s"failure:${e.getMessage}")
}
Thread.sleep(2000)
Response time is in hundreds of milliseconds and I got success. Is it a bug of dispatch?
An HTTP roundtrip goes through several phases (overly simplified):
establishing connection
connection established
sending request payload
request payload sent
waiting for response payload
receiving response payload
response payload received
From what I understand you measure the time between states 1 and 7.
setConnectionTimeoutInMs comes from async-http-client which is used by Dispatch internally. Here's an excerpt from its documentation:
Set the maximum time in millisecond an AsyncHttpClient can wait when connecting to a remote host
Thus, this method sets the maximum time the client will wait between states 1 and 2.
There's also setRequestTimeoutInMs:
Set the maximum time in millisecond an AsyncHttpClient wait for a response
This method seems to set the time between states 5 and 6 (or 7, I'm not sure which one).
So here's what's probably happening in your case. You connect to remote host, the server accepts the connection very quickly (the time between 1 and 2 is small), so your Future doesn't get failed. Then there are several options: either server takes a lot of time to prepare the response before it starts sending it back to you (the time between 5 and 6), or the response is very big so it takes a lot of time to deliver it to you (the time between 6 and 7), or both. But since you don't set the request timeout, your Future is not getting failed because of this.
Related
I'm writing a C# Web API server application, and will send JSON to it via a Mirth HTTP Sender destination. This post is about how to handle error conditions. Specifically, there are three scenarios I want to handle:
Sometimes we take the C# application server offline for a short period for system upgrade or maintenance, and Mirth is unable to connect at all. I want Mirth to queue all messages in order, and when the server is available, process them in the order they were received.
The server receives the request, but rejects it due to a problem with the content of the request, e.g., missing a required field. In accordance with REST conventions, the server will return a 400-level HTTP response. This message would be rejected every time it's submitted, so it should not be re-sent; just log the failure and move on to the next message.
The server receives the request, but something goes wrong on the server, and the server returns an HTTP 500 Server Error response. This would be the appropriate response, for example, when something in the server environment has gone wrong. One real-world example was the time the Web API server was running, but somebody rebooted the database server. REST conventions would suggest we continue to resend the message until the transient problem has been resolved.
For #1, initially I had it queue on failure/always, but it appears the response transformer never runs for messages that were queued (at least, the debug statements never showed in the log). I have turned queueing off, and set it to retry every ten seconds for an hour, and that seems to give the desired behavior. Am I on the right track here, or missing something?
For #2 and #3, returning any HTTP 400 or 500 error invokes the 1-hour retries. What I want is to apply the 1-hour retries for the 500 errors, but not the 400 errors. I’ve tried responseStatus = SENT in the response transformer, but the response transformer only runs once, after the hour has expired, and not for each retry.
This seems like a common problem, yet I’m not finding a solution. How are the rest of you handling this?
You're close!
So by default, the response transformer will only run if there's a response payload to transform. For connection problems, or possibly for 4xx/5xx responses that contain no payload, the response transformer won't execute.
However, if you set your response data types (From the Summary -> Set Data Types dialog, or from the Destinations -> Edit Response, Message Templates tab) to Raw, then the response transformer will execute all the time. The reason being that the Raw data type considers even an empty payload to be "transformable".
So turn queuing back on, and set your response data types to Raw. Then in the response transformer, if you look at the Reference tab there's a category for HTTP Sender:
You'll want the "response status line", that's the "HTTP/1.1 200 OK" line of the response that contains the response code. Here's a response transformer script that forces 4xx responses to error:
if (responseStatus == QUEUED) {
var statusLine = $('responseStatusLine');
if (statusLine) {
var parts = statusLine.split(' ');
if (parts.length >= 2) {
var responseCode = parseInt(parts[1], 10);
// Force 4xx responses to error
if (responseCode >= 400 && responseCode < 500) {
responseStatus = ERROR;
responseStatusMessage = statusLine;
}
}
}
}
I am using Play 2.6 and The twitter streaming API.
Below is how I connect to twitter using the ws library's stream() method.
The problem is that, the steam always stops after exactly 2 minutes. I tried different topics and the behavior is pretty consistent.
It seems there is a setting but I could not find where.
I am not sure it's on the play side or twitter side.
Any help is greatly appreciated.
ws.url("https://stream.twitter.com/1.1/statuses/filter.json")
.sign(OAuthCalculator(ConsumerKey(credentials._1, credentials._2), RequestToken(credentials._3, credentials._4)))
.withQueryStringParameters("track" -> topic)
.withMethod("POST")
.stream()
.map {
response => response.bodyAsSource.map(t=> {t.utf8String})
}
Play WS has default request timeout which is exactly 2 minutes by default.
Here is link to the docs:
https://www.playframework.com/documentation/2.6.x/ScalaWS#Configuring-Timeouts
So you can put in your application.conf line like
play.ws.timeout.request = 10 minutes
to specify default timeout for your all requests.
Also you can specify timeout for single request using withRequestTimeout method of WSRequest builder
/**
* Sets the maximum time you expect the request to take.
* Use Duration.Inf to set an infinite request timeout.
* Warning: a stream consumption will be interrupted when this time is reached unless Duration.Inf is set.
*/
def withRequestTimeout(timeout: Duration): WSRequest
So to disable request timeout for a sigle request you can use following code
ws.url(someurl)
.withMethod("GET")
.withRequestTimeout(Duration.Inf)
I'm using the akka http client (version 10.0.0) to make requests to an endpoint served by a PHP Yii framework based application. The following code is executed every time a request is to be made:
val importConfimMsg = new ImportConfirmMessage(msg.orderId, msg.shipmentDate)
val uri = Uri(config.getString("endpoint.url"))
.withQuery(Query("call_id" -> config.getString("endpoint.call_id"),
"cmd" -> config.getString("endpoint.cmd")
))
val request = HttpRequest(method = POST, uri = uri, entity = importConfimMsg)
val result = http.singleRequest(request)
.map(r => r.entity.dataBytes.runWith(Sink.ignore))
The first few requests receive responses in a matter of milliseconds but as the application continues to run and send more requests I'm seeing response times rising steadily to several seconds, then to tens of seconds and eventually timing out at the one minute mark.
Is my implementation incorrect?
So I have a client server based program, where the client will send a request to the server, the server will do a computation and response. This is done via ask.
Specifically the client will receive a message from the client app and send call ask
val response = ask(actorRef, SessionMessage(token, message)).mapTo[ResponseMessage]
The server will receive it like so
val response = sessionMessage.message match {
case message: message1 =>
ask(actorSet.actor1,message)
case message: message2 =>
ask(actorSet.actor2,message)
Where the actorset is literally a set of the different actors.
I then collect the result and send back to the sender
val responseResult = response.mapTo[ResponseMessage]
responseResult pipeTo sender
The problem I'm running into is that for some of the requests, the database query can take a while (5-10 minutes) and when the query completes it sends to dead letters and I get a dissociation and it is unable to associate again and sends to dead letters.
I thought that because it took so long, that the sender would time out (or specifically the sender reference) so I stored the sender reference as a val, and confirmed that by doing this I the sender reference was lost. However, as soon as as the query finishes and I pipe it to the correct sender, it dissociates. Even other queries that take a minute or so don't seem to suffer this problem, only ones that last for a few minutes dissociate and I need to restart the server or the server will keep sending to dead letters.
Even if I do a onComplete then send on success or do an Await.result, the same issue occurs, as soon as it tries to send the message (after completion) the server dissociates and sends to dead letters.
I'm very much at lost as to why this is happening.
The problem you are into is that ask itself has a timeout, which is separate from a timeout you might specify in Await.result. The full signature to ask is:
def ask (actorRef: ActorRef, message: Any)(implicit timeout: Timeout): Future[Any]
This means that if you did not manually provide a value for timeout and did not define an implicit yourself, you must be inheriting one via one of your imports.
To extend the timeout for your particular ask, simply call it with one:
ask(actorRef, SessionMessage(token, message))(15.minutes).mapTo[ResponseMessage]
or if this applies to all asks in scope, declare your own implicit:
implicit val timeout = Timeout(15.minutes)
streaming data out of play, is quite easy.
here's a quick example of how I intend to do it (please let me know if i'm doing it wrong):
def getRandomStream = Action { implicit req =>
import scala.util.Random
import scala.concurrent.{blocking, ExecutionContext}
import ExecutionContext.Implicits.global
def getSomeRandomFutures: List[Future[String]] = {
for {
i <- (1 to 10).toList
r = Random.nextInt(30000)
} yield Future {
blocking {
Thread.sleep(r)
}
s"after $r ms. index: $i.\n"
}
}
val enumerator = Concurrent.unicast[Array[Byte]] {
(channel: Concurrent.Channel[Array[Byte]]) => {
getSomeRandomFutures.foreach {
_.onComplete {
case Success(x: String) => channel.push(x.getBytes("utf-8"))
case Failure(t) => channel.push(t.getMessage)
}
}
//following future will close the connection
Future {
blocking {
Thread.sleep(30000)
}
}.onComplete {
case Success(_) => channel.eofAndEnd()
case Failure(t) => channel.end(t)
}
}
}
new Status(200).chunked(enumerator).as("text/plain;charset=UTF-8")
}
now, if you get served by this action, you'll get something like:
after 1757 ms. index: 10.
after 3772 ms. index: 3.
after 4282 ms. index: 6.
after 4788 ms. index: 8.
after 10842 ms. index: 7.
after 12225 ms. index: 4.
after 14085 ms. index: 9.
after 17110 ms. index: 1.
after 21213 ms. index: 2.
after 21516 ms. index: 5.
where every line is received after the random time has passed.
now, imagine I want to preserve this simple example when streaming data from the server to the client, but I also want to support full streaming of data from the client to the server.
So, lets say i'm implementing a new BodyParser that parses the input into a List[Future[String]]. this means, that now, my Action could look like something like this:
def getParsedStream = Action(myBodyParser) { implicit req =>
val xs: List[Future[String]] = req.body
val enumerator = Concurrent.unicast[Array[Byte]] {
(channel: Concurrent.Channel[Array[Byte]]) => {
xs.foreach {
_.onComplete {
case Success(x: String) => channel.push(x.getBytes("utf-8"))
case Failure(t) => channel.push(t.getMessage)
}
}
//again, following future will close the connection
Future.sequence(xs).onComplete {
case Success(_) => channel.eofAndEnd()
case Failure(t) => channel.end(t)
}
}
}
new Status(200).chunked(enumerator).as("text/plain;charset=UTF-8")
}
but this is still not what I wanted to achieve. in this case, I’ll get the body from the request only after the request was finished, and all the data was uploaded to the server. but I want to start serving request as I go. a simple demonstration, would be to echo any received line back to the user, while keeping the connection alive.
so here's my current thoughts:
what if my BodyParser would return an Enumerator[String] instead of List[Future[String]]?
in this case, I could simply do the following:
def getParsedStream = Action(myBodyParser) { implicit req =>
new Status(200).chunked(req.body).as("text/plain;charset=UTF-8")
}
so now, i'm facing the problem of how to implement such a BodyParser.
being more precise as to what exactly I need, well:
I need to receive chunks of data to parse as a string, where every string ends in a newline \n (may contain multiple lines though...). every "chunk of lines" would be processed by some (irrelevant to this question) computation, which would yield a String, or better, a Future[String], since this computation may take some time. the resulted strings of this computation, should be sent to the user as they are ready, much like the random example above. and this should happen simultaneously while more data is being sent.
I have looked into several resources trying to achieve it, but was unsuccessful so far.
e.g. scalaQuery play iteratees -> it seems like this guy is doing something similar to what I want to do, but I couldn't translate it into a usable example. (and the differences from play2.0 to play2.2 API doesn't help...)
So, to sum it up: Is this the right approach (considering I don't want to use WebSockets)? and if so, how do I implement such a BodyParser?
EDIT:
I have just stumble upon a note on the play documentation regarding this issue, saying:
Note: It is also possible to achieve the same kind of live
communication the other way around by using an infinite HTTP request
handled by a custom BodyParser that receives chunks of input data, but
that is far more complicated.
so, i'm not giving up, now that I know for sure this is achievable.
What you want to do isn't quite possible in Play.
The problem is that Play can't start sending a response until it has completely received the request. So you can either receive the request in its entirety and then send a response, as you have been doing, or you can process requests as you receive them (in a custom BodyParser), but you still can't reply until you've received the request in its entirety (which is what the note in the documentation was alluding to - although you can send a response in a different connection).
To see why, note that an Action is fundamentally a (RequestHeader) => Iteratee[Array[Byte], SimpleResult]. At any time, an Iteratee is in one of three states - Done, Cont, or Error. It can only accept more data if it's in the Cont state, but it can only return a value when it's in the Done state. Since that return value is a SimpleResult (i.e, our response), this means there's a hard cut off from receiving data to sending data.
According to this answer, the HTTP standard does allow a response before the request is complete, but most browsers don't honor the spec, and in any case Play doesn't support it, as explained above.
The simplest way to implement full-duplex communication in Play is with WebSockets, but we've ruled that out. If server resource usage is the main reason for the change, you could try parsing your data with play.api.mvc.BodyParsers.parse.temporaryFile, which will save the data to a temporary file, or play.api.mvc.BodyParsers.parse.rawBuffer, which will overflow to a temporary file if the request is too large.
Otherwise, I can't see a sane way to do this using Play, so you may want to look at using another web server.
"Streaming data in and out simultaneously on a single HTTP connection in play"
I haven't finished reading all of your question, nor the code, but what you're asking to do isn't available in HTTP. That has nothing to do with Play.
When you make a web request, you open a socket to a web server and send "GET /file.html HTTP/1.1\n[optional headers]\n[more headers]\n\n"
You get a response after (and only after) you have completed your request (optionally including a request body as part of the request). When and only when the request and response are finished, in HTTP 1.1 (but not 1.0) you can make a new request on the same socket (in http 1.0 you open a new socket).
It's possible for the response to "hang" ... this is how web chats work. The server just sits there, hanging onto the open socket, not sending a response until someone sends you a message. The persistent connection to the web server eventually provides a response when/if you receive a chat message.
Similarly, the request can "hang." You can start to send your request data to the server, wait a bit, and then complete the request when you receive additional user input. This mechanism provides better performance than continually creating new http requests on each user input. A server can interpret this stream of data as a stream of distinct inputs, even though that wasn't necessarily the initial intention of the HTTP spec.
HTTP does not support a mechanism to receive part of a request, then send part of a response, then receive more of a request. It's just not in the spec. Once you've begun to receive a response, the only way to send additional information to the server is to use another HTTP request. You can use one that's already open in parallel, or you can open a new one, or you can complete the first request/response and issue an additional request on the same socket (in 1.1).
If you must have asynchronous io on a single socket connection, you might want to consider a different protocol other than HTTP.