public static void main(String[] args) throws IOException {
Parameters param = new Parameters();
long initTime = System.currentTimeMillis();
SparkConf conf = new SparkConf().setAppName("StarJoin");
JavaSparkContext sc = new JavaSparkContext(conf);
if (param.useKryo) {
conf.set("spark.serializer", "org.apache.spark.serializer.KryoSerializer");
conf.set("spark.kryo.registrator", MyBloomFilter.BloomFilterRegistrator.class.getName());
conf.set("spark.kryoserializer.buffer.mb", param.buffer);
}
MyBloomFilter.BloomFilter<String> BFS =
new MyBloomFilter.BloomFilter(1.0, param.bitsS, param.hashes);
MyBloomFilter.BloomFilter<String> BFD =
new MyBloomFilter.BloomFilter(1.0, param.bitsD, param.hashes);
MyBloomFilter.BloomFilter<String> BFC =
new MyBloomFilter.BloomFilter(1.0, param.bitsC, param.hashes);
JavaPairRDD<String, String> supps =
sc.textFile(param.suppPath)
.map(
new Function<String, String[]>() {
public String[] call(String line) {
return line.split("\\|");
}
})
.filter(
new Function<String[], Boolean>() {
public Boolean call(String[] s) {
return s[3].equals("UNITED KI1") | s[3].equals("UNITED KI5");
}
})
.mapToPair(
new PairFunction<String[], String, String>() {
public Tuple2<String, String> call(String[] s) {
return new Tuple2<String, String>(s[0], s[3]);
}
});
List<Tuple2<String, String>> s = supps.collect();
for (int i = 0; i < s.size(); i++) {
BFS.add(s.get(i)._1);
}
final Broadcast<MyBloomFilter.BloomFilter<String>> varS = sc.broadcast(BFS);
JavaPairRDD<String, String> custs =
sc.textFile(param.custPath)
.map(
new Function<String, String[]>() {
public String[] call(String line) {
return line.split("\\|");
}
})
.filter(
new Function<String[], Boolean>() {
public Boolean call(String[] s) {
return s[3].equals("UNITED KI1") | s[3].equals("UNITED KI5");
}
})
.mapToPair(
new PairFunction<String[], String, String>() {
public Tuple2<String, String> call(String[] s) {
return new Tuple2<String, String>(s[0], s[3]);
}
});
List<Tuple2<String, String>> c = custs.collect();
for (int i = 0; i < c.size(); i++) {
BFC.add(c.get(i)._1);
}
final Broadcast<MyBloomFilter.BloomFilter<String>> varC = sc.broadcast(BFC);
JavaPairRDD<String, String> dates =
sc.textFile(param.datePath)
.map(
new Function<String, String[]>() {
public String[] call(String line) {
return line.split("\\|");
}
})
.filter(
new Function<String[], Boolean>() {
public Boolean call(String[] s) {
return s[6].equals("Dec1997");
}
})
.mapToPair(
new PairFunction<String[], String, String>() {
public Tuple2<String, String> call(String[] s) {
return new Tuple2<String, String>(s[0], s[4]);
}
});
List<Tuple2<String, String>> d = dates.collect();
for (int i = 0; i < d.size(); i++) {
BFD.add(d.get(i)._1);
}
final Broadcast<MyBloomFilter.BloomFilter<String>> varD = sc.broadcast(BFD);
JavaPairRDD<String, String[]> lines =
sc.textFile(param.linePath)
.map(
new Function<String, String[]>() {
public String[] call(String line) {
return line.split("\\|");
}
})
.filter(
new Function<String[], Boolean>() {
public Boolean call(String[] s) {
return varC.value().contains(s[2].getBytes())
& varS.value().contains(s[4].getBytes())
& varD.value().contains(s[5].getBytes());
}
})
.mapToPair(
new PairFunction<String[], String, String[]>() {
public Tuple2<String, String[]> call(String[] s) {
String[] v = {s[2], s[5], s[12]};
return new Tuple2<String, String[]>(s[4], v);
}
});
JavaPairRDD<String, String[]> result =
lines
.join(supps)
.mapToPair(
new PairFunction<Tuple2<String, Tuple2<String[], String>>, String, String[]>() {
public Tuple2<String, String[]> call(Tuple2<String, Tuple2<String[], String>> s) {
String[] v = {s._2._1[1], s._2._1[2], s._2._2};
return new Tuple2<String, String[]>(s._2._1[0], v);
}
});
result =
result
.join(custs)
.mapToPair(
new PairFunction<Tuple2<String, Tuple2<String[], String>>, String, String[]>() {
public Tuple2<String, String[]> call(Tuple2<String, Tuple2<String[], String>> s) {
String[] v = {s._2._1[1], s._2._1[2], s._2._2};
return new Tuple2<String, String[]>(s._2._1[0], v);
}
});
JavaPairRDD<String, Long> final_result =
result
.join(dates)
.mapToPair(
new PairFunction<Tuple2<String, Tuple2<String[], String>>, String, Long>() {
public Tuple2<String, Long> call(Tuple2<String, Tuple2<String[], String>> s) {
return new Tuple2<String, Long>(
s._2._1[2] + "," + s._2._1[1] + "," + s._2._2, Long.parseLong(s._2._1[0]));
}
})
.reduceByKey(
new Function2<Long, Long, Long>() {
public Long call(Long i1, Long i2) {
return i1 + i2;
}
});
JavaPairRDD<String, String> sub_result =
final_result.mapToPair(
new PairFunction<Tuple2<String, Long>, String, String>() {
public Tuple2<String, String> call(Tuple2<String, Long> line) {
return new Tuple2(line._1 + "," + line._2.toString(), null);
}
});
final_result =
sub_result
.sortByKey(new Q3Comparator())
.mapToPair(
new PairFunction<Tuple2<String, String>, String, Long>() {
public Tuple2<String, Long> call(Tuple2<String, String> line) {
String[] s = line._1.split(",");
return new Tuple2<String, Long>(
s[0] + "," + s[1] + "," + s[2], Long.parseLong(s[3]));
}
});
Configuration HDFSconf = new Configuration();
FileSystem fs = FileSystem.get(HDFSconf);
fs.delete(new Path(param.output), true);
final_result.saveAsTextFile(param.output);
long finalTime = System.currentTimeMillis();
System.out.print("Tempo total(ms): ");
System.out.println(finalTime - initTime);
sc.close();
}
public static void main(String[] args) throws FileNotFoundException {
if (args.length <= 0) {
System.out.println(
"We require input file path, output file path and number of partitions argument to proceed further.");
System.out.println(
"Usage: java FarthestPair <input file path> <output file path> <noOfPartitions>");
System.exit(0);
}
String inputFile = args[0];
SparkConf conf = new SparkConf().setAppName("Group6-FarthestPair");
JavaSparkContext sc = new JavaSparkContext(conf);
// Read file as RDD
JavaRDD<String> inputData = sc.textFile(inputFile);
// JavaRDD<Coordinate> coordinates = inputData.mapPartitions(parseData);
// Map each String in the file as a coordinate object
JavaRDD<Coordinate> coordinates = inputData.map(parseData); // .repartition(noOfPartitions);
// Map to a tuple to sort the Points
JavaPairRDD<Coordinate, Boolean> pointTupleRDD =
coordinates.mapToPair(new CoordinatePairFunction());
// Sort the points
JavaPairRDD<Coordinate, Boolean> sortedPointTupleRDD =
pointTupleRDD.sortByKey(new CoordinateComparator());
// Map to points RDD
JavaRDD<Coordinate> finalSortedPointRDD =
sortedPointTupleRDD.map(new TupleToCoordinateMapFunction());
// Convert sorted collection to RDD
// Perform Convex hull operation on individual partition
JavaRDD<Coordinate> localHull = finalSortedPointRDD.mapPartitions(new hull());
// Repartition to 1 partition in order to apply 'convex hull' on all the Coordinate objects
// obtained from individual partitions
JavaRDD<Coordinate> calculatedHull = localHull.coalesce(1).cache();
// Perform Convex hull operation
JavaRDD<Coordinate> globalHull = calculatedHull.mapPartitions(new hull()).distinct();
JavaPairRDD<Coordinate, Coordinate> allCoordinateTuples = globalHull.cartesian(globalHull);
System.out.println("Total cart: " + allCoordinateTuples.collect().size());
JavaRDD<Pair> pairsRDD =
allCoordinateTuples.map(
new Function<Tuple2<Coordinate, Coordinate>, Pair>() {
public Pair call(Tuple2<Coordinate, Coordinate> tuple) throws Exception {
// TODO Auto-generated method stub
Coordinate pointA = tuple._1();
Coordinate pointB = tuple._2();
Pair a = new Pair(pointA, pointB);
return a;
}
});
JavaRDD<Pair> pairs =
allCoordinateTuples.mapPartitions(
new FlatMapFunction<Iterator<Tuple2<Coordinate, Coordinate>>, Pair>() {
/** */
private static final long serialVersionUID = 1L;
public Iterable<Pair> call(Iterator<Tuple2<Coordinate, Coordinate>> tuples)
throws Exception {
// TODO Auto-generated method stub
List<Pair> pairsFromTuples = new ArrayList<Pair>();
// Pair singlePair = new Pair();
Tuple2<Coordinate, Coordinate> tuple;
while (tuples.hasNext()) {
tuple = tuples.next();
// singlePair.A = tuples.next()._1;
// singlePair.B = tuples.next()._2;
Pair singlePair = new Pair(tuple._1(), tuple._2());
pairsFromTuples.add(singlePair);
}
return pairsFromTuples;
}
});
JavaRDD<Integer> x =
pairsRDD.mapPartitions(
new FlatMapFunction<Iterator<Pair>, Integer>() {
public Iterable<Integer> call(Iterator<Pair> arg0) throws Exception {
// TODO Auto-generated method stub
ArrayList<Integer> x = new ArrayList<Integer>();
x.add(1);
return x;
}
});
System.out.println("Num of partitions: " + x.collect());
JavaRDD<Integer> y =
pairs.mapPartitions(
new FlatMapFunction<Iterator<Pair>, Integer>() {
public Iterable<Integer> call(Iterator<Pair> arg0) throws Exception {
// TODO Auto-generated method stub
ArrayList<Integer> x = new ArrayList<Integer>();
x.add(1);
return x;
}
});
System.out.println("Num of partitions charan: " + y.collect());
Pair minDistPair =
pairs.reduce(
new Function2<Pair, Pair, Pair>() {
/** */
private static final long serialVersionUID = 1L;
public Pair call(Pair a, Pair b) throws Exception {
// TODO Auto-generated method stub
return (a.distanceLength > b.distanceLength ? a : b);
}
});
// System.out.println(minDistPair);
Coordinate closestpointA = minDistPair.A;
Coordinate closestpointB = minDistPair.B;
List<Coordinate> closestPoints = new ArrayList<Coordinate>();
closestPoints.add(closestpointA);
closestPoints.add(closestpointB);
JavaRDD<Coordinate> closestRDD = sc.parallelize(closestPoints);
// Map to a tuple to sort the Points
JavaPairRDD<Coordinate, Boolean> coordinateTupleRDD =
closestRDD.mapToPair(new CoordinatePairFunction());
// Sort the points
JavaPairRDD<Coordinate, Boolean> sortedCoordinateTupleRDD =
coordinateTupleRDD.sortByKey(new CoordinateComparator());
// Map to points RDD
JavaRDD<Coordinate> finalSortedCoordinateRDD =
sortedCoordinateTupleRDD.map(new TupleToCoordinateMapFunction());
JavaRDD<String> outputData = finalSortedCoordinateRDD.map(parseOutputData);
// closestRDD.saveAsTextFile(outputfilepath);
outputData.saveAsTextFile(args[1]);
// Output your result, you need to sort your result!!!
// And,Don't add a additional clean up step delete the new generated
// file...
sc.close();
}
public static void main(String[] args) {
// STEP 1: create a SparkConf object
if (args.length < 1) {
log.fatal("Syntax Error: there must be one argument (a file name or a directory)");
throw new RuntimeException();
}
// STEP 2: create a SparkConf object
SparkConf sparkConf = new SparkConf().setAppName("Trending Topic");
// STEP 3: create a Java Spark context
JavaSparkContext sparkContext = new JavaSparkContext(sparkConf);
// STEP 4: read lines of files
JavaRDD<String> lines = sparkContext.textFile(args[0]);
JavaRDD<String> words;
words =
lines.flatMap(
new FlatMapFunction<String, String>() {
@Override
public Iterable call(String s) throws Exception {
return Arrays.asList(s.split("\t")[2].split(" "));
}
});
JavaPairRDD<String, Integer> ones;
ones =
words.mapToPair(
new PairFunction<String, String, Integer>() {
@Override
public Tuple2<String, Integer> call(String string) {
return new Tuple2<>(string, 1);
}
});
JavaPairRDD<String, Integer> counts;
counts =
ones.reduceByKey(
new Function2<Integer, Integer, Integer>() {
@Override
public Integer call(Integer integer, Integer integer2) throws Exception {
return integer + integer2;
}
});
// Es necesario invertir las tuplas ya que no podemos ordenar por valor, sino por clave
JavaPairRDD<Integer, String> swapped;
swapped =
counts.mapToPair(
new PairFunction<Tuple2<String, Integer>, Integer, String>() {
@Override
public Tuple2<Integer, String> call(Tuple2<String, Integer> tupla) throws Exception {
return tupla.swap();
}
});
// STEP 7: sort the results by key
List<Tuple2<Integer, String>> output = swapped.sortByKey().collect();
// El ejercicio dice que quitemos las palabras que no aportan nada. Para ello podríamos ponerlas
// en un fichero y leerlas y luego obviar esas. Vamos a obviar esa parte ya que se entiende y no
// es el caso del ejercicio
List<String> excluyentes = new LinkedList<>();
excluyentes.add("rt");
excluyentes.add("http");
excluyentes.add("https");
excluyentes.add("www");
for (Tuple2<Integer, String> t : output) {
if (excluyentes.contains(t._2)) {
output.remove(t);
}
}
// STEP 8: print the results
for (int i = 0; i < 10; i++) {
Tuple2<Integer, String> tuple;
tuple = output.get(i);
System.out.println(tuple._2() + ": " + tuple._1());
}
// STEP 9: stop the spark context
sparkContext.stop();
}
