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package spark.deploy
import org.apache.hadoop.conf.Configuration
import org.apache.hadoop.mapred.JobConf
/**
* Contains util methods to interact with Hadoop from spark.
*/
object SparkHadoopUtil {
def getUserNameFromEnvironment(): String = {
// defaulting to -D ...
System.getProperty("user.name")
}
def runAsUser(func: (Product) => Unit, args: Product) {
// Add support, if exists - for now, simply run func !
func(args)
}
// Return an appropriate (subclass) of Configuration. Creating config can initializes some hadoop subsystems
def newConfiguration(): Configuration = new Configuration()
// add any user credentials to the job conf which are necessary for running on a secure Hadoop cluster
def addCredentials(conf: JobConf) {}
}
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