org.apache.spark.api.java.function.Function2 Java Examples

The following examples show how to use org.apache.spark.api.java.function.Function2. You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may check out the related API usage on the sidebar.
Example #1
Source Project: sparkResearch   Author: Mydreamandreality   File: KafkaStreaming.java    License: Apache License 2.0 8 votes vote down vote up
public static void main(String[] args) {
    SparkConf sparkConf = new SparkConf().setAppName("KafkaWordCount").setMaster("local[2]");
    JavaStreamingContext streamingContext = new JavaStreamingContext(sparkConf, Durations.seconds(10000));
    //设置检查点
    streamingContext.checkpoint("HDFS URL");
    Map<String, Integer> topicThread = new HashMap<>(1);
    topicThread.put(TOPIC, THREAD);
    JavaPairInputDStream<String, String> dStream = KafkaUtils.createStream(streamingContext, HOST, GROP, topicThread);

    JavaDStream<String> words = dStream.flatMap((FlatMapFunction<Tuple2<String, String>, String>) stringStringTuple2 -> Arrays.asList(SPACE.split(stringStringTuple2._2)).iterator());

    //统计
    JavaPairDStream<String, Integer> result = words.mapToPair((PairFunction<String, String, Integer>) s -> new Tuple2<>(s, 1)).reduceByKey((Function2<Integer, Integer, Integer>) (v1, v2) -> v1 + v2);

    try {
        result.print();
        streamingContext.start();
        streamingContext.awaitTermination();
    } catch (InterruptedException e) {
        e.printStackTrace();
    }
}
 
Example #2
Source Project: kylin-on-parquet-v2   Author: Kyligence   File: SparkCubingByLayer.java    License: Apache License 2.0 6 votes vote down vote up
private Long getRDDCountSum(JavaPairRDD<ByteArray, Object[]> rdd, final int countMeasureIndex) {
    final ByteArray ONE = new ByteArray();
    Long count = rdd.mapValues(new Function<Object[], Long>() {
        @Override
        public Long call(Object[] objects) throws Exception {
            return (Long) objects[countMeasureIndex];
        }
    }).reduce(new Function2<Tuple2<ByteArray, Long>, Tuple2<ByteArray, Long>, Tuple2<ByteArray, Long>>() {
        @Override
        public Tuple2<ByteArray, Long> call(Tuple2<ByteArray, Long> longTuple2, Tuple2<ByteArray, Long> longTuple22)
                throws Exception {
            return new Tuple2<>(ONE, longTuple2._2() + longTuple22._2());
        }
    })._2();
    return count;
}
 
Example #3
Source Project: kylin-on-parquet-v2   Author: Kyligence   File: NGlobalDictionaryV2Test.java    License: Apache License 2.0 6 votes vote down vote up
private void runWithSparkBuildGlobalDict(NGlobalDictionaryV2 dict, List<String> stringSet) throws IOException {
    KylinConfig config = KylinConfig.getInstanceFromEnv();
    dict.prepareWrite();
    List<Row> rowList = Lists.newLinkedList();
    for (String str : stringSet) {
        rowList.add(RowFactory.create(str));
    }
    Dataset<Row> ds = ss.createDataFrame(rowList,
            new StructType(new StructField[] { DataTypes.createStructField("col1", DataTypes.StringType, true) }));
    ds.toJavaRDD().mapToPair((PairFunction<Row, String, String>) row -> {
        if (row.get(0) == null)
            return new Tuple2<>(null, null);
        return new Tuple2<>(row.get(0).toString(), null);
    }).sortByKey().partitionBy(new HashPartitioner(BUCKET_SIZE)).mapPartitionsWithIndex(
            (Function2<Integer, Iterator<Tuple2<String, String>>, Iterator<Object>>) (bucketId, tuple2Iterator) -> {
                NBucketDictionary bucketDict = dict.loadBucketDictionary(bucketId);
                while (tuple2Iterator.hasNext()) {
                    Tuple2<String, String> tuple2 = tuple2Iterator.next();
                    bucketDict.addRelativeValue(tuple2._1);
                }
                bucketDict.saveBucketDict(bucketId);
                return Lists.newArrayList().iterator();
            }, true).count();

    dict.writeMetaDict(BUCKET_SIZE, config.getGlobalDictV2MaxVersions(), config.getGlobalDictV2VersionTTL());
}
 
Example #4
Source Project: incubator-nemo   Author: apache   File: ReduceTransform.java    License: Apache License 2.0 6 votes vote down vote up
/**
 * Reduce the iterator elements into a single object.
 *
 * @param elements the iterator of elements.
 * @param func     function to apply for reduction.
 * @param <T>      type of the elements.
 * @return the reduced element.
 */
@Nullable
public static <T> T reduceIterator(final Iterator<T> elements, final Function2<T, T, T> func) {
  if (!elements.hasNext()) { // nothing to be done
    return null;
  }

  T res = elements.next();
  while (elements.hasNext()) {
    try {
      res = func.call(res, elements.next());
    } catch (Exception e) {
      throw new RuntimeException(e);
    }
  }
  return res;
}
 
Example #5
Source Project: SparkDemo   Author: huangyueranbbc   File: Reduce.java    License: MIT License 6 votes vote down vote up
private static void reduce(JavaSparkContext sc) {
	
	List<Integer> numberList=Arrays.asList(1,2,3,4,5,6,7,8,9,10);
	JavaRDD<Integer> javaRDD = sc.parallelize(numberList);
	
	/**
	 *   =====================================================
	 *   |                                                                 累加求和                                                               | 
	 *   =====================================================
	 */
	Integer num = javaRDD.reduce(new Function2<Integer, Integer, Integer>() {
		/**
		 * @param num1上一次计算结果 return的值
		 * @param num2 当前值
		 */
		@Override
		public Integer call(Integer num1, Integer num2) throws Exception {
			// System.out.println(num1+"======"+num2);
			return num1 + num2;
		}
	});
	
	System.out.println(num);
	
	sc.close();
}
 
Example #6
Source Project: vn.vitk   Author: phuonglh   File: Tokenizer.java    License: GNU General Public License v3.0 6 votes vote down vote up
/**
 * Counts the number of non-space characters in this data set. This utility method 
 * is used to check the tokenization result.
 * @param lines
 * @return number of characters
 */
int numCharacters(JavaRDD<String> lines) {
	JavaRDD<Integer> lengths = lines.map(new Function<String, Integer>() {
		private static final long serialVersionUID = -2189399343462982586L;
		@Override
		public Integer call(String line) throws Exception {
			line = line.replaceAll("[\\s_]+", "");
			return line.length();
		}
	});
	return lengths.reduce(new Function2<Integer, Integer, Integer>() {
		private static final long serialVersionUID = -8438072946884289401L;

		@Override
		public Integer call(Integer e0, Integer e1) throws Exception {
			return e0 + e1;
		}
	});
}
 
Example #7
Source Project: nemo   Author: snuspl   File: ReduceTransform.java    License: Apache License 2.0 6 votes vote down vote up
/**
 * Reduce the iterator elements into a single object.
 * @param elements the iterator of elements.
 * @param func function to apply for reduction.
 * @param <T> type of the elements.
 * @return the reduced element.
 */
@Nullable
public static <T> T reduceIterator(final Iterator<T> elements, final Function2<T, T, T> func) {
  if (!elements.hasNext()) { // nothing to be done
    return null;
  }

  T res = elements.next();
  while (elements.hasNext()) {
    try {
      res = func.call(res, elements.next());
    } catch (Exception e) {
      throw new RuntimeException(e);
    }
  }
  return res;
}
 
Example #8
Source Project: kylin   Author: apache   File: SparkCubingByLayer.java    License: Apache License 2.0 6 votes vote down vote up
private Long getRDDCountSum(JavaPairRDD<ByteArray, Object[]> rdd, final int countMeasureIndex) {
    final ByteArray ONE = new ByteArray();
    Long count = rdd.mapValues(new Function<Object[], Long>() {
        @Override
        public Long call(Object[] objects) throws Exception {
            return (Long) objects[countMeasureIndex];
        }
    }).reduce(new Function2<Tuple2<ByteArray, Long>, Tuple2<ByteArray, Long>, Tuple2<ByteArray, Long>>() {
        @Override
        public Tuple2<ByteArray, Long> call(Tuple2<ByteArray, Long> longTuple2, Tuple2<ByteArray, Long> longTuple22)
                throws Exception {
            return new Tuple2<>(ONE, longTuple2._2() + longTuple22._2());
        }
    })._2();
    return count;
}
 
Example #9
Source Project: incubator-retired-blur   Author: apache   File: BlurBulkLoadSparkProcessor.java    License: Apache License 2.0 6 votes vote down vote up
@Override
protected Function2<JavaPairRDD<String, RowMutation>, Time, Void> getFunction() {
  return new Function2<JavaPairRDD<String, RowMutation>, Time, Void>() {
    // Blur Thrift Client
    @Override
    public Void call(JavaPairRDD<String, RowMutation> rdd, Time time) throws Exception {
      Iface client = getBlurClient();
      for (Tuple2<String, RowMutation> tuple : rdd.collect()) {
        if (tuple != null) {
          try {
            RowMutation rm = tuple._2;
            // Index using enqueue mutate call
            client.enqueueMutate(rm);
          } catch (Exception ex) {
            LOG.error("Unknown error while trying to call enqueueMutate.", ex);
            throw ex;
          }
        }
      }
      return null;
    }
  };
}
 
Example #10
Source Project: incubator-nemo   Author: apache   File: SparkJavaPairRDD.java    License: Apache License 2.0 5 votes vote down vote up
@Override
public SparkJavaPairRDD<K, V> reduceByKey(final Function2<V, V, V> func) {
  // Explicit conversion
  final PairRDDFunctions<K, V> pairRdd = RDD.rddToPairRDDFunctions(
    rdd, ClassTag$.MODULE$.apply(Object.class), ClassTag$.MODULE$.apply(Object.class), null);
  final RDD<Tuple2<K, V>> reducedRdd = pairRdd.reduceByKey(func);
  return SparkJavaPairRDD.fromRDD(reducedRdd);
}
 
Example #11
Source Project: incubator-nemo   Author: apache   File: SparkJavaPairRDD.java    License: Apache License 2.0 5 votes vote down vote up
@Override
public <C> SparkJavaPairRDD<K, C> combineByKey(final Function<V, C> createCombiner,
                                               final Function2<C, V, C> mergeValue,
                                               final Function2<C, C, C> mergeCombiners,
                                               final Partitioner partitioner,
                                               final boolean mapSideCombine,
                                               final Serializer serializer) {
  throw new UnsupportedOperationException(NOT_YET_SUPPORTED);
}
 
Example #12
Source Project: incubator-nemo   Author: apache   File: SparkJavaPairRDD.java    License: Apache License 2.0 5 votes vote down vote up
@Override
public <C> SparkJavaPairRDD<K, C> combineByKey(final Function<V, C> createCombiner,
                                               final Function2<C, V, C> mergeValue,
                                               final Function2<C, C, C> mergeCombiners,
                                               final Partitioner partitioner) {
  throw new UnsupportedOperationException(NOT_YET_SUPPORTED);
}
 
Example #13
Source Project: incubator-nemo   Author: apache   File: SparkJavaPairRDD.java    License: Apache License 2.0 5 votes vote down vote up
@Override
public <C> SparkJavaPairRDD<K, C> combineByKey(final Function<V, C> createCombiner,
                                               final Function2<C, V, C> mergeValue,
                                               final Function2<C, C, C> mergeCombiners,
                                               final int numPartitions) {
  throw new UnsupportedOperationException(NOT_YET_SUPPORTED);
}
 
Example #14
Source Project: incubator-nemo   Author: apache   File: SparkJavaPairRDD.java    License: Apache License 2.0 5 votes vote down vote up
@Override
public <U> SparkJavaPairRDD<K, U> aggregateByKey(final U zeroValue,
                                                 final Partitioner partitioner,
                                                 final Function2<U, V, U> seqFunc,
                                                 final Function2<U, U, U> combFunc) {
  throw new UnsupportedOperationException(NOT_YET_SUPPORTED);
}
 
Example #15
Source Project: incubator-nemo   Author: apache   File: SparkJavaPairRDD.java    License: Apache License 2.0 5 votes vote down vote up
@Override
public <U> SparkJavaPairRDD<K, U> aggregateByKey(final U zeroValue,
                                                 final int numPartitions,
                                                 final Function2<U, V, U> seqFunc,
                                                 final Function2<U, U, U> combFunc) {
  throw new UnsupportedOperationException(NOT_YET_SUPPORTED);
}
 
Example #16
Source Project: SparkDemo   Author: huangyueranbbc   File: JavaLogQuery.java    License: MIT License 5 votes vote down vote up
public static void main(String[] args) {
  SparkSession spark = SparkSession
    .builder()
    .appName("JavaLogQuery")
    .getOrCreate();

  JavaSparkContext jsc = new JavaSparkContext(spark.sparkContext());

  JavaRDD<String> dataSet = (args.length == 1) ? jsc.textFile(args[0]) : jsc.parallelize(exampleApacheLogs);

  JavaPairRDD<Tuple3<String, String, String>, Stats> extracted = dataSet.mapToPair(new PairFunction<String, Tuple3<String, String, String>, Stats>() {
    @Override
    public Tuple2<Tuple3<String, String, String>, Stats> call(String s) {
      return new Tuple2<>(extractKey(s), extractStats(s));
    }
  });

  JavaPairRDD<Tuple3<String, String, String>, Stats> counts = extracted.reduceByKey(new Function2<Stats, Stats, Stats>() {
    @Override
    public Stats call(Stats stats, Stats stats2) {
      return stats.merge(stats2);
    }
  });

  List<Tuple2<Tuple3<String, String, String>, Stats>> output = counts.collect();
  for (Tuple2<?,?> t : output) {
    System.out.println(t._1() + "\t" + t._2());
  }
  spark.stop();
}
 
Example #17
Source Project: SparkDemo   Author: huangyueranbbc   File: JavaCustomReceiver.java    License: MIT License 5 votes vote down vote up
public static void main(String[] args) throws Exception {
  if (args.length < 2) {
    System.err.println("Usage: JavaCustomReceiver <hostname> <port>");
    System.exit(1);
  }

  StreamingExamples.setStreamingLogLevels();

  // Create the context with a 1 second batch size
  SparkConf sparkConf = new SparkConf().setAppName("JavaCustomReceiver");
  JavaStreamingContext ssc = new JavaStreamingContext(sparkConf, new Duration(1000));

  // Create an input stream with the custom receiver on target ip:port and count the
  // words in input stream of \n delimited text (eg. generated by 'nc')
  JavaReceiverInputDStream<String> lines = ssc.receiverStream(
    new JavaCustomReceiver(args[0], Integer.parseInt(args[1])));
  JavaDStream<String> words = lines.flatMap(new FlatMapFunction<String, String>() {
    @Override
    public Iterator<String> call(String x) {
      return Arrays.asList(SPACE.split(x)).iterator();
    }
  });
  JavaPairDStream<String, Integer> wordCounts = words.mapToPair(
    new PairFunction<String, String, Integer>() {
      @Override public Tuple2<String, Integer> call(String s) {
        return new Tuple2<>(s, 1);
      }
    }).reduceByKey(new Function2<Integer, Integer, Integer>() {
      @Override
      public Integer call(Integer i1, Integer i2) {
        return i1 + i2;
      }
    });

  wordCounts.print();
  ssc.start();
  ssc.awaitTermination();
}
 
Example #18
Source Project: SparkDemo   Author: huangyueranbbc   File: MapPartitionsWithIndex.java    License: MIT License 5 votes vote down vote up
private static void mapPartitionsWithIndex(JavaSparkContext sc) {

		List<String> names = Arrays.asList("张三1", "李四1", "王五1", "张三2", "李四2", "王五2", "张三3", "李四3", "王五3", "张三4");

		// 初始化,分为3个分区
		JavaRDD<String> namesRDD = sc.parallelize(names, 3);
		JavaRDD<String> mapPartitionsWithIndexRDD = namesRDD
				.mapPartitionsWithIndex(new Function2<Integer, Iterator<String>, Iterator<String>>() {

					private static final long serialVersionUID = 1L;

					public Iterator<String> call(Integer v1, Iterator<String> v2) throws Exception {
						List<String> list = new ArrayList<String>();
						while (v2.hasNext()) {
							list.add("分区索引:" + v1 + "\t" + v2.next());
						}
						return list.iterator();
					}
				}, true);

		// 从集群获取数据到本地内存中
		List<String> result = mapPartitionsWithIndexRDD.collect();
		for (String s : result) {
			System.out.println(s);
		}

		sc.close();
	}
 
Example #19
Source Project: rheem   Author: rheem-ecosystem   File: FunctionCompiler.java    License: Apache License 2.0 5 votes vote down vote up
/**
 * Create an appropriate {@link Function} for deploying the given {@link ReduceDescriptor}
 * on Apache Spark.
 */
public <T> Function2<T, T, T> compile(ReduceDescriptor<T> descriptor,
                                      SparkExecutionOperator operator,
                                      OptimizationContext.OperatorContext operatorContext,
                                      ChannelInstance[] inputs) {
    final BinaryOperator<T> javaImplementation = descriptor.getJavaImplementation();
    if (javaImplementation instanceof FunctionDescriptor.ExtendedSerializableBinaryOperator) {
        return new ExtendedBinaryOperatorAdapter<>(
                (FunctionDescriptor.ExtendedSerializableBinaryOperator<T>) javaImplementation,
                new SparkExecutionContext(operator, inputs, operatorContext.getOptimizationContext().getIterationNumber())
        );
    } else {
        return new BinaryOperatorAdapter<>(javaImplementation);
    }
}
 
Example #20
Source Project: spark-streaming-direct-kafka   Author: ameyamk   File: Functions.java    License: Apache License 2.0 5 votes vote down vote up
/**
 * @return a function that returns the second of two values
 * @param <T> element type
 */
public static <T> Function2<T,T,T> last() {
    return new Function2<T,T,T>() {
        @Override
        public T call(T current, T next) {
            return next;
        }
    };
}
 
Example #21
Source Project: nemo   Author: snuspl   File: JavaPairRDD.java    License: Apache License 2.0 5 votes vote down vote up
@Override
public JavaPairRDD<K, V> reduceByKey(final Function2<V, V, V> func) {
  final DAGBuilder<IRVertex, IREdge> builder = new DAGBuilder<>(dag);

  final IRVertex reduceByKeyVertex = new OperatorVertex(new ReduceByKeyTransform<K, V>(func));
  builder.addVertex(reduceByKeyVertex, loopVertexStack);

  final IREdge newEdge = new IREdge(getEdgeCommunicationPattern(lastVertex, reduceByKeyVertex),
      lastVertex, reduceByKeyVertex, new SparkCoder(serializer));
  newEdge.setProperty(KeyExtractorProperty.of(new SparkKeyExtractor()));
  builder.connectVertices(newEdge);

  return new JavaPairRDD<>(this.sparkContext, builder.buildWithoutSourceSinkCheck(), reduceByKeyVertex);
}
 
Example #22
Source Project: DDF   Author: ddf-project   File: MLSupporter.java    License: Apache License 2.0 5 votes vote down vote up
@Override
public long[][] getConfusionMatrix(IModel model, double threshold) throws DDFException {
  SparkDDF ddf = (SparkDDF) this.getDDF();
  SparkDDF predictions = (SparkDDF) ddf.ML.applyModel(model, true, false);

  // Now get the underlying RDD to compute
  JavaRDD<double[]> yTrueYPred = (JavaRDD<double[]>) predictions.getJavaRDD(double[].class);
  final double threshold1 = threshold;
  long[] cm = yTrueYPred.map(new Function<double[], long[]>() {
    @Override
    public long[] call(double[] params) {
      byte isPos = toByte(params[0] > threshold1);
      byte predPos = toByte(params[1] > threshold1);

      long[] result = new long[] { 0L, 0L, 0L, 0L };
      result[isPos << 1 | predPos] = 1L;
      return result;
    }
  }).reduce(new Function2<long[], long[], long[]>() {
    @Override
    public long[] call(long[] a, long[] b) {
      return new long[] { a[0] + b[0], a[1] + b[1], a[2] + b[2], a[3] + b[3] };
    }
  });

  return new long[][] { new long[] { cm[3], cm[2] }, new long[] { cm[1], cm[0] } };
}
 
Example #23
Source Project: examples   Author: ArchitectingHBase   File: CountLines.java    License: Apache License 2.0 5 votes vote down vote up
@SuppressWarnings("serial")
public static void main(String[] args) {
  SparkConf sparkConf = new SparkConf().setAppName("JavaHBaseBulkGetExample ").setMaster("local[2]");
  JavaSparkContext jsc = new JavaSparkContext(sparkConf);
  JavaRDD<String> textFile = jsc.textFile("hdfs://localhost/user/cloudera/data.txt");
  JavaPairRDD<String, Integer> pairs = textFile.mapToPair(new PairFunction<String, String, Integer>() {
    public Tuple2<String, Integer> call(String s) { return new Tuple2<String, Integer>(s.substring(0, s.indexOf("|")), 1); }
  });
  JavaPairRDD<String, Integer> counts = pairs.reduceByKey(new Function2<Integer, Integer, Integer>() {
    public Integer call(Integer a, Integer b) { return a + b; }
  });
  System.out.println ("We have generaged " + counts.count() + " users");
  jsc.close();
}
 
Example #24
Source Project: BigDataArchitect   Author: bjmashibing   File: WordCountJava.java    License: Apache License 2.0 4 votes vote down vote up
public static void main(String[] args) throws FileNotFoundException {

        SparkConf conf = new SparkConf();
        conf.setAppName("java-wordcount");
        conf.setMaster("local");

        JavaSparkContext jsc = new JavaSparkContext(conf);

        JavaRDD<String> fileRDD = jsc.textFile("bigdata-spark/data/testdata.txt");

        JavaRDD<String> words = fileRDD.flatMap(new FlatMapFunction<String, String>() {
            public Iterator<String> call(String line) throws Exception {
                return Arrays.asList(line.split(" ")).iterator();
            }
        });

        JavaPairRDD<String, Integer> pairWord = words.mapToPair(new PairFunction<String, String, Integer>() {
            public Tuple2<String, Integer> call(String word) throws Exception {
                return new Tuple2<String, Integer>(word, 1);
            }
        });

        JavaPairRDD<String, Integer> res = pairWord.reduceByKey(new Function2<Integer, Integer, Integer>() {
            public Integer call(Integer oldV, Integer v) throws Exception {
                return oldV + v;
            }
        });

        res.foreach(new VoidFunction<Tuple2<String, Integer>>() {
            public void call(Tuple2<String, Integer> value) throws Exception {
                System.out.println(value._1+"\t"+value._2);
            }
        });

//
//        RandomAccessFile rfile = new RandomAccessFile("ooxx","rw");
//
////        rfile.seek(222);
//        FileChannel channel = rfile.getChannel();
//        //  linux  fd   write(fd)  read(fd)
//
//
//        ByteBuffer b1 = ByteBuffer.allocate(1024);
//        ByteBuffer b2 = ByteBuffer.allocateDirect(1024);
//        MappedByteBuffer buffer = channel.map(FileChannel.MapMode.READ_WRITE, 80, 120);
//


    }
 
Example #25
Source Project: incubator-nemo   Author: apache   File: SparkJavaPairRDD.java    License: Apache License 2.0 4 votes vote down vote up
@Override
public SparkJavaPairRDD<K, V> reduceByKey(final Partitioner partitioner,
                                          final Function2<V, V, V> func) {
  throw new UnsupportedOperationException(NOT_YET_SUPPORTED);
}
 
Example #26
Source Project: incubator-nemo   Author: apache   File: SparkJavaPairRDD.java    License: Apache License 2.0 4 votes vote down vote up
@Override
public Map<K, V> reduceByKeyLocally(final Function2<V, V, V> func) {
  throw new UnsupportedOperationException(NOT_YET_SUPPORTED);
}
 
Example #27
Source Project: incubator-nemo   Author: apache   File: SparkJavaPairRDD.java    License: Apache License 2.0 4 votes vote down vote up
@Override
public <U> SparkJavaPairRDD<K, U> aggregateByKey(final U zeroValue,
                                                 final Function2<U, V, U> seqFunc,
                                                 final Function2<U, U, U> combFunc) {
  throw new UnsupportedOperationException(NOT_YET_SUPPORTED);
}
 
Example #28
Source Project: incubator-nemo   Author: apache   File: SparkJavaPairRDD.java    License: Apache License 2.0 4 votes vote down vote up
@Override
public SparkJavaPairRDD<K, V> foldByKey(final V zeroValue,
                                        final Partitioner partitioner,
                                        final Function2<V, V, V> func) {
  throw new UnsupportedOperationException(NOT_YET_SUPPORTED);
}
 
Example #29
Source Project: incubator-nemo   Author: apache   File: SparkJavaPairRDD.java    License: Apache License 2.0 4 votes vote down vote up
@Override
public SparkJavaPairRDD<K, V> foldByKey(final V zeroValue,
                                        final int numPartitions,
                                        final Function2<V, V, V> func) {
  throw new UnsupportedOperationException(NOT_YET_SUPPORTED);
}
 
Example #30
Source Project: incubator-nemo   Author: apache   File: SparkJavaPairRDD.java    License: Apache License 2.0 4 votes vote down vote up
@Override
public SparkJavaPairRDD<K, V> foldByKey(final V zeroValue,
                                        final Function2<V, V, V> func) {
  throw new UnsupportedOperationException(NOT_YET_SUPPORTED);
}