scala

问题 I would expect the following code to compile just fine: trait Widen[M[_]] { def widen[A, B >: A](ma: M[A]): M[B] } object Widen { implicit class Ops[M[_], A](ma: M[A]) { def widen[B >: A](implicit ev: Widen[M]): M[B] = ev.widen[A, B](ma) } // implicit class OpsNothing[M[_]](ma: M[Nothing]) { // def widen[B](implicit ev: Widen[M]): M[B] = ev.widen(ma) // } implicit val WidenList = new Widen[List] { def widen[A, B >: A](l: List[A]): List[B] = l } } import Widen._ List.empty[Some[Int]].widen

问题 I have a scala application that uses Akka Streams and running as a cronjob in Google Kubernetes Engine. But the pod is still in the “Running” state (not completed). And the Java process is still running inside the container. Here's what I do exactly: I build the docker image with sbt-native-packager and sbt docker:publish . When the job is done, I terminate it with regular system.terminate call. implicit val system: ActorSystem = ActorSystem("actor-system") /* doing actual stuff */ stream

问题 I have a scala application that uses Akka Streams and running as a cronjob in Google Kubernetes Engine. But the pod is still in the “Running” state (not completed). And the Java process is still running inside the container. Here's what I do exactly: I build the docker image with sbt-native-packager and sbt docker:publish . When the job is done, I terminate it with regular system.terminate call. implicit val system: ActorSystem = ActorSystem("actor-system") /* doing actual stuff */ stream

问题 To get a sequence with one value updated, one can use seq.updated(index, value) I want to set a new value for a range of elements. Is there a library function for that? I currently use the following function: def updatedSlice[A](seq: List[A], ind: Iterable[Int], value: A): List[A] = if (ind.isEmpty) seq else updatedSlice(seq.updated(ind.head, value), ind.tail, value) Besides the need of writing function, this seems to be inefficient, and also works only for lists, rather than arbitrary

问题 I am new to scala..I want to know when processing large datasets with scala in spark is it possible to read as int RDD instead of String RDD I tried the below: val intArr = sc .textFile("Downloads/data/train.csv") .map(line=>line.split(",")) .map(_.toInt) But I am getting the error: error: value toInt is not a member of Array[String] I need to convert to int rdd because down the line i need to do the below val vectors = intArr.map(p => Vectors.dense(p)) which requires the type to be integer

问题 I am using play Reads validation helpers i want to show some custom message in case of json exception eg:length is minimum then specified or the given email is not valid , i knnow play displays the error message like this error.minLength but i want to display a reasonable message like please enter the character greater then 1 (or something ) here is my code case class DirectUserSignUpValidation(firstName: String, lastName: String, email: String, password: String) extends Serializable object

问题 If I have a DataFrame called df that looks like: +----+----+ | a1+ a2| +----+----+ | foo| bar| | N/A| baz| |null| etc| +----+----+ I can selectively replace values like so: val df2 = df.withColumn("a1", when($"a1" === "N/A", $"a2")) so that df2 looks like: +----+----+ | a1+ a2| +----+----+ | foo| bar| | baz| baz| |null| etc| +----+----+ but why can't I check if it's null, like: val df3 = df2.withColumn("a1", when($"a1" === null, $"a2")) so that I get: +----+----+ | a1+ a2| +----+----+ | foo|

问题 I'm writing a simple scala-based script which supposed to insert some data into Mongo collection. The problem is, that script exits before mongo finishes it's task. What is the idiomatic/best approach to deal with the problem, considering following script: #!/usr/bin/env scalas /*** scalaVersion := "2.12.2" libraryDependencies ++= { Seq( "org.mongodb.scala" %% "mongo-scala-driver" % "2.1.0" ) } */ import org.mongodb.scala._ val mongoClient: MongoClient = MongoClient("mongodb://localhost") val

问题 If we have such two functions... def findUserById(id: Long): Future[Option[User]] = ??? def findAddressByUser(user: User): Future[Option[Address]] = ??? ...then we are able to use cats OptionT monad transformer to write for-comprehension with them easily: for { user <- OptionT(findUserById(id)) address <- OptionT(findAddressByUser(user)) } ... I'd like to compose future of sequences this way, like this: def findUsersBySomeField(value: FieldValue): Future[Seq[User]] = ??? def

问题 If we have such two functions... def findUserById(id: Long): Future[Option[User]] = ??? def findAddressByUser(user: User): Future[Option[Address]] = ??? ...then we are able to use cats OptionT monad transformer to write for-comprehension with them easily: for { user <- OptionT(findUserById(id)) address <- OptionT(findAddressByUser(user)) } ... I'd like to compose future of sequences this way, like this: def findUsersBySomeField(value: FieldValue): Future[Seq[User]] = ??? def