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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 org.apache.spark.rdd
import java.text.SimpleDateFormat
import java.util.Date
import org.apache.hadoop.conf.{Configurable, Configuration}
import org.apache.hadoop.io.Writable
import org.apache.hadoop.mapreduce._
import org.apache.spark.{InterruptibleIterator, Logging, Partition, SerializableWritable, SparkContext, TaskContext}
private[spark]
class NewHadoopPartition(rddId: Int, val index: Int, @transient rawSplit: InputSplit with Writable)
extends Partition {
val serializableHadoopSplit = new SerializableWritable(rawSplit)
override def hashCode(): Int = (41 * (41 + rddId) + index)
}
class NewHadoopRDD[K, V](
sc : SparkContext,
inputFormatClass: Class[_ <: InputFormat[K, V]],
keyClass: Class[K],
valueClass: Class[V],
@transient conf: Configuration)
extends RDD[(K, V)](sc, Nil)
with SparkHadoopMapReduceUtil
with Logging {
// A Hadoop Configuration can be about 10 KB, which is pretty big, so broadcast it
private val confBroadcast = sc.broadcast(new SerializableWritable(conf))
// private val serializableConf = new SerializableWritable(conf)
private val jobtrackerId: String = {
val formatter = new SimpleDateFormat("yyyyMMddHHmm")
formatter.format(new Date())
}
@transient private val jobId = new JobID(jobtrackerId, id)
override def getPartitions: Array[Partition] = {
val inputFormat = inputFormatClass.newInstance
if (inputFormat.isInstanceOf[Configurable]) {
inputFormat.asInstanceOf[Configurable].setConf(conf)
}
val jobContext = newJobContext(conf, jobId)
val rawSplits = inputFormat.getSplits(jobContext).toArray
val result = new Array[Partition](rawSplits.size)
for (i <- 0 until rawSplits.size) {
result(i) = new NewHadoopPartition(id, i, rawSplits(i).asInstanceOf[InputSplit with Writable])
}
result
}
override def compute(theSplit: Partition, context: TaskContext) = {
val iter = new Iterator[(K, V)] {
val split = theSplit.asInstanceOf[NewHadoopPartition]
logInfo("Input split: " + split.serializableHadoopSplit)
val conf = confBroadcast.value.value
val attemptId = newTaskAttemptID(jobtrackerId, id, isMap = true, split.index, 0)
val hadoopAttemptContext = newTaskAttemptContext(conf, attemptId)
val format = inputFormatClass.newInstance
if (format.isInstanceOf[Configurable]) {
format.asInstanceOf[Configurable].setConf(conf)
}
val reader = format.createRecordReader(
split.serializableHadoopSplit.value, hadoopAttemptContext)
reader.initialize(split.serializableHadoopSplit.value, hadoopAttemptContext)
// Register an on-task-completion callback to close the input stream.
context.addOnCompleteCallback(() => close())
var havePair = false
var finished = false
override def hasNext: Boolean = {
if (!finished && !havePair) {
finished = !reader.nextKeyValue
havePair = !finished
}
!finished
}
override def next(): (K, V) = {
if (!hasNext) {
throw new java.util.NoSuchElementException("End of stream")
}
havePair = false
(reader.getCurrentKey, reader.getCurrentValue)
}
private def close() {
try {
reader.close()
} catch {
case e: Exception => logWarning("Exception in RecordReader.close()", e)
}
}
}
new InterruptibleIterator(context, iter)
}
override def getPreferredLocations(split: Partition): Seq[String] = {
val theSplit = split.asInstanceOf[NewHadoopPartition]
theSplit.serializableHadoopSplit.value.getLocations.filter(_ != "localhost")
}
def getConf: Configuration = confBroadcast.value.value
}
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