【Spark Java API】Action(3)—foreach、foreachPartition、lookup

foreach

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官方文档描述：

Applies a function f to all elements of this RDD.

函数原型：

def foreach(f: VoidFunction[T])

foreach用于遍历RDD,将函数f应用于每一个元素。

源码分析：

def foreach(f: T => Unit): Unit = withScope {    val cleanF = sc.clean(f)    sc.runJob(this, (iter: Iterator[T]) => iter.foreach(cleanF))}

实例：

List<Integer> data = Arrays.asList(5, 1, 1, 4, 4, 2, 2);JavaRDD<Integer> javaRDD = javaSparkContext.parallelize(data,3);javaRDD.foreach(new VoidFunction<Integer>() {      @Override      public void call(Integer integer) throws Exception {            System.out.println(integer);      }});

foreachPartition

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官方文档描述：

Applies a function f to each partition of this RDD.

函数原型：

def foreachPartition(f: VoidFunction[java.util.Iterator[T]])

foreachPartition和foreach类似，只不过是对每一个分区使用f。

源码分析：

def foreachPartition(f: Iterator[T] => Unit): Unit = withScope {    val cleanF = sc.clean(f)    sc.runJob(this, (iter: Iterator[T]) => cleanF(iter))}

实例：

List<Integer> data = Arrays.asList(5, 1, 1, 4, 4, 2, 2);JavaRDD<Integer> javaRDD = javaSparkContext.parallelize(data,3);//获得分区IDJavaRDD<String> partitionRDD = javaRDD.mapPartitionsWithIndex(new Function2<Integer, Iterator<Integer>, Iterator<String>>() {      @Override      public Iterator<String> call(Integer v1, Iterator<Integer> v2) throws Exception {              LinkedList<String> linkedList = new LinkedList<String>();              while(v2.hasNext()){                    linkedList.add(v1 + "=" + v2.next());              }     return linkedList.iterator();      }},false);System.out.println(partitionRDD.collect());javaRDD.foreachPartition(new VoidFunction<Iterator<Integer>>() {      @Override       public void call(Iterator<Integer> integerIterator) throws Exception {            System.out.println("___________begin_______________");            while(integerIterator.hasNext())                  System.out.print(integerIterator.next() + "      ");            System.out.println("\n___________end_________________");       }});

lookup

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官方文档描述：

Return the list of values in the RDD for key `key`. This operation is done efficiently if the RDD has a known partitioner by only searching the partition that the key maps to.

函数原型：

def lookup(key: K): JList[V]

lookup用于(K,V)类型的RDD,指定K值，返回RDD中该K对应的所有V值。

源码分析：

def lookup(key: K): Seq[V] = self.withScope {    self.partitioner match {        case Some(p) =>            val index = p.getPartition(key)            val process = (it: Iterator[(K, V)]) => {                val buf = new ArrayBuffer[V]                for (pair <- it if pair._1 == key) {                    buf += pair._2                }                buf            } : Seq[V]            val res = self.context.runJob(self, process, Array(index), false)            res(0)        case None =>            self.filter(_._1 == key).map(_._2).collect()    }}

从源码中可以看出，如果partitioner不为空，计算key得到对应的partition，在从该partition中获得key对应的所有value；如果partitioner为空，则通过filter过滤掉其他不等于key的值，然后将其value输出。

实例：

List<Integer> data = Arrays.asList(5, 1, 1, 4, 4, 2, 2);JavaRDD<Integer> javaRDD = javaSparkContext.parallelize(data, 3);JavaPairRDD<Integer,Integer> javaPairRDD = javaRDD.mapToPair(new PairFunction<Integer, Integer, Integer>() {      int i = 0;      @Override      public Tuple2<Integer, Integer> call(Integer integer) throws Exception {            i++;            return new Tuple2<Integer, Integer>(integer,i + integer);      }});System.out.println(javaPairRDD.collect());System.out.println("lookup------------" + javaPairRDD.lookup(4));