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/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
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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