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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 examples;
//
import scala.Tuple2;
import org.apache.commons.lang.math.LongRange;
import org.apache.spark.SparkConf;
import org.apache.spark.api.java.JavaRDD;
import org.apache.spark.api.java.JavaPairRDD;
import org.apache.spark.api.java.JavaSparkContext;
import org.apache.spark.api.java.function.FlatMapFunction;
import org.apache.spark.api.java.function.Function2;
import org.apache.spark.api.java.function.Function;
import org.apache.spark.api.java.function.PairFunction;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;
import java.util.List;
import ngs.ErrorMsg;
import ngs.ReadCollection;
import ngs.ReadIterator;
import ngs.Read;
/**
* Computes an approximation to pi
* Usage: SparkKMer [slices] [kmer-size]
*/
public final class SparkKMer {
public static void main(String[] args) throws Exception {
//Setup
SparkConf sparkConf = new SparkConf().setAppName("SparkKMer");
JavaSparkContext jsc = new JavaSparkContext(sparkConf);
//Agrument parsing
if(args.length < 2) {
System.err.println("Usage: SparkKMer <accession> <kmer-length>");
System.exit(1);
}
final String acc = args[0];
final int KMER_LENGTH = Integer.parseInt(args[1]);
//Check accession and split
ReadCollection run = gov.nih.nlm.ncbi.ngs.NGS.openReadCollection ( acc );
long numreads = run.getReadCount ();
//Slice the job
int chunk = 20000; /** amount of reads per 1 map operation **/
int slices = (int)(numreads / chunk / 1);
if(slices==0) slices=1;
List<LongRange> sub = new ArrayList<LongRange>();
for(long first=1;first <= numreads;){
long last= first+chunk-1;
if(last > numreads) last=numreads;
sub.add(new LongRange(first,last));
first=last+1;
}
System.err.println("Prepared ranges: \n"+sub);
JavaRDD<LongRange> jobs= jsc.parallelize(sub, slices);
//Map
//
JavaRDD<String> kmers = jobs.flatMap(new FlatMapFunction<LongRange, String>() {
ReadCollection run=null;
@Override
public Iterable<String> call(LongRange s) {
//Executes on task nodes
List<String> ret = new ArrayList<String>();
try {
long first = s.getMinimumLong();
long last = s.getMaximumLong();
if(run==null) {
run = gov.nih.nlm.ncbi.ngs.NGS.openReadCollection ( acc );
}
ReadIterator it = run.getReadRange ( first, last-first+1, Read.all );
while(it.nextRead ()){
//iterate through fragments
while ( it.nextFragment () ){
String bases=it.getFragmentBases ();
//iterate through kmers
for(int i=0;i<bases.length()-KMER_LENGTH;i++){
ret.add(bases.substring(i,i+KMER_LENGTH));
}
}
}
} catch ( ErrorMsg x ) {
System.err.println ( x.toString () );
x.printStackTrace ();
}
return ret;
}
});
//Initiate kmer counting;
JavaPairRDD<String, Integer> kmer_ones = kmers.mapToPair(new PairFunction<String, String, Integer>() {
@Override
public Tuple2<String, Integer> call(String s) {
return new Tuple2<String, Integer>(s, 1);
}
});
//Reduce counts
JavaPairRDD<String, Integer> counts = kmer_ones.reduceByKey(new Function2<Integer, Integer, Integer>() {
@Override
public Integer call(Integer i1, Integer i2) {
return i1 + i2;
}
});
//Collect the output
List<Tuple2<String, Integer>> output = counts.collect();
for (Tuple2<String,Integer> tuple : output) {
System.out.println(tuple._1() + ": " + tuple._2());
}
jsc.stop();
}
}
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