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package spark.deploy.yarn
import spark.util.IntParam
import collection.mutable.ArrayBuffer
class ApplicationMasterArguments(val args: Array[String]) {
var userJar: String = null
var userClass: String = null
var userArgs: Seq[String] = Seq[String]()
var workerMemory = 1024
var workerCores = 1
var numWorkers = 2
parseArgs(args.toList)
private def parseArgs(inputArgs: List[String]): Unit = {
val userArgsBuffer = new ArrayBuffer[String]()
var args = inputArgs
while (! args.isEmpty) {
args match {
case ("--jar") :: value :: tail =>
userJar = value
args = tail
case ("--class") :: value :: tail =>
userClass = value
args = tail
case ("--args") :: value :: tail =>
userArgsBuffer += value
args = tail
case ("--num-workers") :: IntParam(value) :: tail =>
numWorkers = value
args = tail
case ("--worker-memory") :: IntParam(value) :: tail =>
workerMemory = value
args = tail
case ("--worker-cores") :: IntParam(value) :: tail =>
workerCores = value
args = tail
case Nil =>
if (userJar == null || userClass == null) {
printUsageAndExit(1)
}
case _ =>
printUsageAndExit(1, args)
}
}
userArgs = userArgsBuffer.readOnly
}
def printUsageAndExit(exitCode: Int, unknownParam: Any = null) {
if (unknownParam != null) {
System.err.println("Unknown/unsupported param " + unknownParam)
}
System.err.println(
"Usage: spark.deploy.yarn.ApplicationMaster [options] \n" +
"Options:\n" +
" --jar JAR_PATH Path to your application's JAR file (required)\n" +
" --class CLASS_NAME Name of your application's main class (required)\n" +
" --args ARGS Arguments to be passed to your application's main class.\n" +
" Mutliple invocations are possible, each will be passed in order.\n" +
" Note that first argument will ALWAYS be yarn-standalone : will be added if missing.\n" +
" --num-workers NUM Number of workers to start (Default: 2)\n" +
" --worker-cores NUM Number of cores for the workers (Default: 1)\n" +
" --worker-memory MEM Memory per Worker (e.g. 1000M, 2G) (Default: 1G)\n")
System.exit(exitCode)
}
}
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