spark Transformations算子

时间:2023-03-08 23:30:00
spark Transformations算子

在java中,RDD分为javaRDDs和javaPairRDDs。下面分两大类来进行。

都必须要进行的一步。

SparkConf conf = new SparkConf().setMaster("local").setAppName("test");
JavaSparkContext sc = new JavaSparkContext(conf);

  

一。javaRDDs

         String[] ayys = {"a","b","c"};
List<String> strings = Arrays.asList(ayys); JavaRDD<String> rdd1 = sc.parallelize(strings);
strings.add("d");
JavaRDD<String> rdd2 = sc.parallelize(strings); JavaRDD<Tuple2<String, Integer>> parallelize = sc.parallelize(Arrays.asList(
new Tuple2<String, Integer>("asd", 11),
new Tuple2<String, Integer>("asd", 11),
new Tuple2<String, Integer>("asd", 11)
)); rdd1.map(new Function<String, String>() {
public String call(String s) throws Exception {
return s.replace("a","qqq");
}
}).foreach(new VoidFunction<String>() {
public void call(String s) throws Exception {
System.out.println(s);
}
}); List<String> a = rdd1.filter(new Function<String, Boolean>() {
public Boolean call(String s) throws Exception {
return s.contains("a");
}
}).collect(); System.out.println(a); JavaRDD<String> rdd22 = rdd1.flatMap(new FlatMapFunction<String, String>() {
public Iterable<String> call(String s) throws Exception {
return Arrays.asList(s.split(" "));
}
}); JavaPairRDD<String, Integer> rdd4 = rdd2.mapToPair(new PairFunction<String, String, Integer>() {
public Tuple2<String, Integer> call(String s) throws Exception {
return new Tuple2<String, Integer>(s, 1);
}
}); JavaRDD<String> rdd11 = rdd2.mapPartitions(new FlatMapFunction<Iterator<String>, String>() {
public Iterable<String> call(Iterator<String> stringIterator) throws Exception {
ArrayList<String> strings = new ArrayList<String>();
while (stringIterator.hasNext()){
strings.add(stringIterator.next());
}
return strings;
}
}); JavaRDD<String> stringJavaRDD = rdd1.mapPartitionsWithIndex(new Function2<Integer, Iterator<String>, Iterator<String>>() {
public Iterator<String> call(Integer integer, Iterator<String> stringIterator) throws Exception {
ArrayList<String> strings = new ArrayList<String>();
while (stringIterator.hasNext()){
strings.add(stringIterator.next());
}
return strings.iterator();
}
},false); JavaRDD<String> sample = rdd1.sample(false, 0.3); JavaRDD<String> union = rdd1.union(rdd2); JavaRDD<String> intersection = rdd1.intersection(rdd2); JavaRDD<String> distinct = rdd1.distinct();

二。JavaPairRDDs.

  

        JavaPairRDD<String, Integer> rdd1 = sc.parallelizePairs(Arrays.asList(
new Tuple2<String, Integer>("asd", 111),
new Tuple2<String, Integer>("asd", 111),
new Tuple2<String, Integer>("asd", 111)
)); JavaPairRDD<String, Integer> rdd2 = sc.parallelizePairs(Arrays.asList(
new Tuple2<String, Integer>("sdfsd", 222),
new Tuple2<String, Integer>("sdfsd", 222),
new Tuple2<String, Integer>("sdfsd", 222)
)); JavaPairRDD<String, Iterable<Integer>> stringIterableJavaPairRDD = rdd1.groupByKey(); JavaPairRDD<String, Integer> rdd = rdd1.reduceByKey(new Function2<Integer, Integer, Integer>() {
public Integer call(Integer integer, Integer integer2) throws Exception {
return integer + integer2;
}
}); JavaPairRDD<String, Integer> rdd3 = rdd1.aggregateByKey(0, new Function2<Integer, Integer, Integer>() {
public Integer call(Integer integer, Integer integer2) throws Exception {
return max(integer,integer2);
}
}, new Function2<Integer, Integer, Integer>() {
public Integer call(Integer integer, Integer integer2) throws Exception {
return integer + integer2;
}
}); JavaPairRDD<String, Integer> rdd111 = rdd1.sortByKey(); JavaPairRDD<String, Tuple2<Integer, Integer>> join = rdd1.join(rdd2);
JavaPairRDD<String, Tuple2<Integer, Optional<Integer>>> stringTuple2JavaPairRDD = rdd1.leftOuterJoin(rdd2);
JavaPairRDD<String, Tuple2<Optional<Integer>, Integer>> stringTuple2JavaPairRDD1 = rdd1.rightOuterJoin(rdd2);
JavaPairRDD<String, Tuple2<Optional<Integer>, Optional<Integer>>> stringTuple2JavaPairRDD2 = rdd1.fullOuterJoin(rdd2); JavaPairRDD<String, Tuple2<Iterable<Integer>, Iterable<Integer>>> cogroup = rdd1.cogroup(rdd2); JavaPairRDD<String, Integer> coalesce = rdd1.coalesce(3, false); JavaPairRDD<String, Integer> repartition = rdd1.repartition(3); JavaPairRDD<String, Integer> rdd5 = rdd1.repartitionAndSortWithinPartitions(new HashPartitioner(2)); JavaPairRDD<Tuple2<String, Integer>, Tuple2<String, Integer>> cartesian = rdd1.cartesian(rdd2); JavaRDD<String> pipe = rdd1.pipe("");

  

zip:

  

        JavaPairRDD<Tuple2<String, Integer>, Tuple2<String, Integer>> zip = rdd1.zip(rdd2);

        JavaPairRDD<Tuple2<String, Integer>, Long> tuple2LongJavaPairRDD =     rdd1.zipWithIndex();

  

最后都要加上

  

        sc.stop();

 

aggregateByKey算子详解

repartitionAndSortWithinPartitions算子详解