You can use Window function if the calculation is fixed as calculating difference between previous months, or calculating between previous two months … etc. For that you can use lag and lead function with Window. But for that you need to change the date column as below so that it can be ordered. +——-+——+————–+——+ |Column1|Date … Read more
add an index column to both dataframe using the below code df1.withColumn(“id1”,monotonicallyIncreasingId) df2.withColumn(“id2”,monotonicallyIncreasingId) then join both the dataframes using the below code and drop the index column df1.join(df2,col(“id1”)===col(“id2″),”inner”) .drop(“id1″,”id2”)
Your code is almost correct – with two issues: The return type of your function is DataFrame, but the last line is aggregated.show(), which returns Unit. Remove the call to show to return aggregated itself, or just return the result of agg immediately DataFrame.groupBy expects arguments as follows: col1: String, cols: String* – so you … Read more
nohup play start works for me.
You can simply foldLeft over the Array of columns: val transformed: DataFrame = df.columns.foldLeft(df)((df, arg) => str(arg, df)) Still, I will argue that it is not a good approach. Since src discards StringIndexerModel it cannot be used when you get new data. Because of that I would recommend using Pipeline: import org.apache.spark.ml.Pipeline val transformers: Array[org.apache.spark.ml.PipelineStage] … Read more
The use case is the first successful completion: scala> :pa // Entering paste mode (ctrl-D to finish) def firstSuccessOf[T](fs: Future[T]*)(implicit x: ExecutionContext): Future[T] = { val p = Promise[T]() val count = new java.util.concurrent.atomic.AtomicInteger(fs.size) def bad() = if (count.decrementAndGet == 0) { p tryComplete new Failure(new RuntimeException(“All bad”)) } val completeFirst: Try[T] => Unit = … Read more
Thank you for your interest in Chisel! We generally encourage people to use our chisel-template repo as a starting point for Chisel3 projects: https://github.com/ucb-bar/chisel-template If you want to do the most barebones possible thing. Create this build.sbt and put it in the root directory for your project. scalaVersion := “2.13.8” addCompilerPlugin(“edu.berkeley.cs” % “chisel3-plugin” % “3.5.3” … Read more
The issue is that you’re executing that as a standalone program, whose main thread is terminating before one of the worker threads can execute the “Hello future!” println. (The threads that the new futures library spawns are daemon threads). You can also use the Await object (also in scala.concurrent) to wait until the future f … Read more
See this scala-debate thread for a discussion of what’s going on here. The problem is that Scala’s type inference happens per parameter list, not per parameter. As Josh Suereth notes in that thread, there’s a good reason for the current approach. If Scala had per-parameter type inference, the compiler couldn’t infer an upper bound across … Read more
You have to use zero-argument functions instead. If you want, you can implicit def byname_to_noarg[A](a: => A) = () => a and then def foo(s: (() => Any)*) = s.foreach(a => println(a())) scala> foo(“fish”, Some(7), {println(“This still happens first”); true }) This still happens first fish Some(7) true