本文整理了Java中org.apache.spark.api.java.JavaPairRDD.flatMapToPair()方法的一些代码示例，展示了JavaPairRDD.flatMapToPair()的具体用法。这些代码示例主要来源于Github/Stackoverflow/Maven等平台，是从一些精选项目中提取出来的代码，具有较强的参考意义，能在一定程度帮忙到你。JavaPairRDD.flatMapToPair()方法的具体详情如下：
包路径：org.apache.spark.api.java.JavaPairRDD
类名称：JavaPairRDD
方法名：flatMapToPair

JavaPairRDD.flatMapToPair介绍

暂无

代码示例

代码示例来源：origin: org.apache.spark/spark-core_2.10

@Test
public void mapsFromPairsToPairs() {
 List<Tuple2<Integer, String>> pairs = Arrays.asList(
  new Tuple2<>(1, "a"),
  new Tuple2<>(2, "aa"),
  new Tuple2<>(3, "aaa")
 );
 JavaPairRDD<Integer, String> pairRDD = sc.parallelizePairs(pairs);
 // Regression test for SPARK-668:
 JavaPairRDD<String, Integer> swapped =
  pairRDD.flatMapToPair(x -> Collections.singletonList(x.swap()).iterator());
 swapped.collect();
 // There was never a bug here, but it's worth testing:
 pairRDD.map(Tuple2::swap).collect();
}

代码示例来源：origin: org.apache.spark/spark-core_2.11

@Test
public void mapsFromPairsToPairs() {
 List<Tuple2<Integer, String>> pairs = Arrays.asList(
  new Tuple2<>(1, "a"),
  new Tuple2<>(2, "aa"),
  new Tuple2<>(3, "aaa")
 );
 JavaPairRDD<Integer, String> pairRDD = sc.parallelizePairs(pairs);
 // Regression test for SPARK-668:
 JavaPairRDD<String, Integer> swapped =
  pairRDD.flatMapToPair(x -> Collections.singletonList(x.swap()).iterator());
 swapped.collect();
 // There was never a bug here, but it's worth testing:
 pairRDD.map(Tuple2::swap).collect();
}

代码示例来源：origin: org.apache.spark/spark-core

@Test
public void mapsFromPairsToPairs() {
 List<Tuple2<Integer, String>> pairs = Arrays.asList(
  new Tuple2<>(1, "a"),
  new Tuple2<>(2, "aa"),
  new Tuple2<>(3, "aaa")
 );
 JavaPairRDD<Integer, String> pairRDD = sc.parallelizePairs(pairs);
 // Regression test for SPARK-668:
 JavaPairRDD<String, Integer> swapped =
  pairRDD.flatMapToPair(x -> Collections.singletonList(x.swap()).iterator());
 swapped.collect();
 // There was never a bug here, but it's worth testing:
 pairRDD.map(Tuple2::swap).collect();
}

代码示例来源：origin: org.apache.spark/spark-core_2.10

@SuppressWarnings("unchecked")
@Test
public void mapsFromPairsToPairs() {
 List<Tuple2<Integer, String>> pairs = Arrays.asList(
  new Tuple2<>(1, "a"),
  new Tuple2<>(2, "aa"),
  new Tuple2<>(3, "aaa")
 );
 JavaPairRDD<Integer, String> pairRDD = sc.parallelizePairs(pairs);
 // Regression test for SPARK-668:
 JavaPairRDD<String, Integer> swapped = pairRDD.flatMapToPair(
  item -> Collections.singletonList(item.swap()).iterator());
 swapped.collect();
 // There was never a bug here, but it's worth testing:
 pairRDD.mapToPair(Tuple2::swap).collect();
}

代码示例来源：origin: org.apache.spark/spark-core

@SuppressWarnings("unchecked")
@Test
public void mapsFromPairsToPairs() {
 List<Tuple2<Integer, String>> pairs = Arrays.asList(
  new Tuple2<>(1, "a"),
  new Tuple2<>(2, "aa"),
  new Tuple2<>(3, "aaa")
 );
 JavaPairRDD<Integer, String> pairRDD = sc.parallelizePairs(pairs);
 // Regression test for SPARK-668:
 JavaPairRDD<String, Integer> swapped = pairRDD.flatMapToPair(
  item -> Collections.singletonList(item.swap()).iterator());
 swapped.collect();
 // There was never a bug here, but it's worth testing:
 pairRDD.mapToPair(Tuple2::swap).collect();
}

代码示例来源：origin: org.apache.spark/spark-core_2.11

@SuppressWarnings("unchecked")
@Test
public void mapsFromPairsToPairs() {
 List<Tuple2<Integer, String>> pairs = Arrays.asList(
  new Tuple2<>(1, "a"),
  new Tuple2<>(2, "aa"),
  new Tuple2<>(3, "aaa")
 );
 JavaPairRDD<Integer, String> pairRDD = sc.parallelizePairs(pairs);
 // Regression test for SPARK-668:
 JavaPairRDD<String, Integer> swapped = pairRDD.flatMapToPair(
  item -> Collections.singletonList(item.swap()).iterator());
 swapped.collect();
 // There was never a bug here, but it's worth testing:
 pairRDD.mapToPair(Tuple2::swap).collect();
}

代码示例来源：origin: apache/kylin

hfilerdd = inputRDDs.flatMapToPair(new PairFlatMapFunction<Tuple2<Text, Text>, RowKeyWritable, KeyValue>() {
  @Override
  public Iterator<Tuple2<RowKeyWritable, KeyValue>> call(Tuple2<Text, Text> textTextTuple2)

代码示例来源：origin: apache/kylin

partition = SparkUtil.estimateLayerPartitionNum(level, cubeStatsReader, envConfig);
allRDDs[level] = allRDDs[level - 1].flatMapToPair(flatMapFunction).reduceByKey(reducerFunction2, partition)
    .persist(storageLevel);
allRDDs[level - 1].unpersist();

代码示例来源：origin: OryxProject/oryx

positiveUserProducts.groupByKey().flatMapToPair(
 new PairFlatMapFunction<Tuple2<Integer,Iterable<Integer>>,Integer,Integer>() {
  private final RandomGenerator random = RandomManager.getRandom();

代码示例来源：origin: mahmoudparsian/data-algorithms-book

groupedRDD.flatMapToPair((Tuple2<String, Iterable<Tuple2<String,String>>> s) -> {

代码示例来源：origin: mahmoudparsian/data-algorithms-book

triads.flatMapToPair((Tuple2<Long, Iterable<Long>> s) -> {

代码示例来源：origin: mahmoudparsian/data-algorithms-book

combined.flatMapToPair((Tuple2<List<String>, Integer> pattern) -> {
  List<Tuple2<List<String>,Tuple2<List<String>,Integer>>> result =
      new ArrayList<Tuple2<List<String>,Tuple2<List<String>,Integer>>>();

代码示例来源：origin: mahmoudparsian/data-algorithms-book

moviesGrouped.flatMapToPair(new PairFlatMapFunction<Tuple2<String, Iterable<Tuple2<String,Integer>>>, String, Tuple3<String,Integer,Integer>>() {
@Override
public Iterator<Tuple2<String,Tuple3<String,Integer,Integer>>> call(Tuple2<String, Iterable<Tuple2<String,Integer>>> s) {
  moviePairs = groupedbyUser.flatMapToPair(new PairFlatMapFunction

代码示例来源：origin: mahmoudparsian/data-algorithms-book

groupedRDD.flatMapToPair(new PairFlatMapFunction<Tuple2<String, Iterable<Tuple2<String,String>>>, String, String>() {
@Override
public Iterator<Tuple2<String,String>> call(Tuple2<String, Iterable<Tuple2<String,String>>> s) {

代码示例来源：origin: mahmoudparsian/data-algorithms-book

stateSequence.flatMapToPair((Tuple2<String, List<String>> s) -> {
List<String> states = s._2;
if ( (states == null) || (states.size() < 2) ) {

代码示例来源：origin: mahmoudparsian/data-algorithms-book

triads.flatMapToPair(new PairFlatMapFunction<

代码示例来源：origin: mahmoudparsian/data-algorithms-book

JavaPairRDD<Long,Tuple2<Long,Long>> possibleRecommendations = filtered.flatMapToPair(
  new PairFlatMapFunction<Tuple2<Tuple2<Long,Long>,Long>, Long, Tuple2<Long,Long>>() {
  @Override

代码示例来源：origin: mahmoudparsian/data-algorithms-book

combined.flatMapToPair(new PairFlatMapFunction<

代码示例来源：origin: mahmoudparsian/data-algorithms-book

JavaPairRDD<Tuple2<String,String>, Integer> model = stateSequence.flatMapToPair(
  new PairFlatMapFunction<

代码示例来源：origin: apache/tinkerpop

viewOutgoingRDD.flatMapToPair(messageFunction).reduceByKey(graphRDD.partitioner().get(), reducerFunction) :
viewOutgoingRDD.flatMapToPair(messageFunction).reduceByKey(reducerFunction))