Java 类org.apache.spark.api.java.JavaRDDLike 实例源码

项目:beam    文件:BoundedDataset.java   
Iterable<WindowedValue<T>> getValues(PCollection<T> pcollection) {
  if (windowedValues == null) {
    WindowFn<?, ?> windowFn =
        pcollection.getWindowingStrategy().getWindowFn();
    Coder<? extends BoundedWindow> windowCoder = windowFn.windowCoder();
    final WindowedValue.WindowedValueCoder<T> windowedValueCoder;
    if (windowFn instanceof GlobalWindows) {
      windowedValueCoder =
          WindowedValue.ValueOnlyWindowedValueCoder.of(pcollection.getCoder());
    } else {
      windowedValueCoder =
          WindowedValue.FullWindowedValueCoder.of(pcollection.getCoder(), windowCoder);
    }
    JavaRDDLike<byte[], ?> bytesRDD =
        rdd.map(CoderHelpers.toByteFunction(windowedValueCoder));
    List<byte[]> clientBytes = bytesRDD.collect();
    windowedValues = Iterables.transform(clientBytes,
        new Function<byte[], WindowedValue<T>>() {
          @Override
          public WindowedValue<T> apply(byte[] bytes) {
            return CoderHelpers.fromByteArray(bytes, windowedValueCoder);
          }
        });
  }
  return windowedValues;
}
项目:Camel    文件:AnnotatedRddCallbackProxy.java   
@Override
public Object onRdd(JavaRDDLike rdd, Object... payloads) {
    try {
        List<Object> arguments = new ArrayList<>(payloads.length + 1);
        arguments.add(rdd);
        arguments.addAll(asList(payloads));
        if (arguments.get(1) == null) {
            arguments.remove(1);
        }

        Method callbackMethod = rddCallbacks.get(0);
        callbackMethod.setAccessible(true);

        if (camelContext != null) {
            for (int i = 1; i < arguments.size(); i++) {
                arguments.set(i, camelContext.getTypeConverter().convertTo(callbackMethod.getParameterTypes()[i], arguments.get(i)));
            }
        }

        return callbackMethod.invoke(objectWithCallback, arguments.toArray(new Object[arguments.size()]));
    } catch (IllegalAccessException | InvocationTargetException e) {
        throw new RuntimeException(e);
    }
}
项目:Camel    文件:SparkProducerTest.java   
@Override
protected JndiRegistry createRegistry() throws Exception {
    JndiRegistry registry = super.createRegistry();

    registry.bind("testFileRdd", sparkContext.textFile("src/test/resources/testrdd.txt"));

    if (shouldRunHive) {
        registry.bind("hiveContext", hiveContext);
        DataFrame jsonCars = hiveContext.read().json("src/test/resources/cars.json");
        jsonCars.registerTempTable("cars");
        registry.bind("jsonCars", jsonCars);
    }

    registry.bind("countLinesTransformation", new org.apache.camel.component.spark.RddCallback() {
        @Override
        public Object onRdd(JavaRDDLike rdd, Object... payloads) {
            return rdd.count();
        }
    });
    return registry;
}
项目:Camel    文件:SparkProducerTest.java   
@Test
public void shouldExecuteVoidCallback() throws IOException {
    // Given
    final File output = File.createTempFile("camel", "spark");
    output.delete();

    // When
    template.sendBodyAndHeader(sparkUri, null, SPARK_RDD_CALLBACK_HEADER, new VoidRddCallback() {
        @Override
        public void doOnRdd(JavaRDDLike rdd, Object... payloads) {
            rdd.saveAsTextFile(output.getAbsolutePath());
        }
    });

    // Then
    Truth.assertThat(output.length()).isGreaterThan(0L);
}
项目:spark-dataflow    文件:TransformTranslator.java   
private static <K, V> TransformEvaluator<GroupByKey.GroupByKeyOnly<K, V>> gbk() {
  return new TransformEvaluator<GroupByKey.GroupByKeyOnly<K, V>>() {
    @Override
    public void evaluate(GroupByKey.GroupByKeyOnly<K, V> transform, EvaluationContext context) {
      @SuppressWarnings("unchecked")
      JavaRDDLike<WindowedValue<KV<K, V>>, ?> inRDD =
          (JavaRDDLike<WindowedValue<KV<K, V>>, ?>) context.getInputRDD(transform);
      @SuppressWarnings("unchecked")
      KvCoder<K, V> coder = (KvCoder<K, V>) context.getInput(transform).getCoder();
      Coder<K> keyCoder = coder.getKeyCoder();
      Coder<V> valueCoder = coder.getValueCoder();

      // Use coders to convert objects in the PCollection to byte arrays, so they
      // can be transferred over the network for the shuffle.
      JavaRDDLike<WindowedValue<KV<K, Iterable<V>>>, ?> outRDD = fromPair(
            toPair(inRDD.map(WindowingHelpers.<KV<K, V>>unwindowFunction()))
          .mapToPair(CoderHelpers.toByteFunction(keyCoder, valueCoder))
          .groupByKey()
          .mapToPair(CoderHelpers.fromByteFunctionIterable(keyCoder, valueCoder)))
          // empty windows are OK here, see GroupByKey#evaluateHelper in the SDK
          .map(WindowingHelpers.<KV<K, Iterable<V>>>windowFunction());
      context.setOutputRDD(transform, outRDD);
    }
  };
}
项目:spark-dataflow    文件:TransformTranslator.java   
private static <T> TransformEvaluator<TextIO.Write.Bound<T>> writeText() {
  return new TransformEvaluator<TextIO.Write.Bound<T>>() {
    @Override
    public void evaluate(TextIO.Write.Bound<T> transform, EvaluationContext context) {
      @SuppressWarnings("unchecked")
      JavaPairRDD<T, Void> last =
          ((JavaRDDLike<WindowedValue<T>, ?>) context.getInputRDD(transform))
          .map(WindowingHelpers.<T>unwindowFunction())
          .mapToPair(new PairFunction<T, T,
                  Void>() {
            @Override
            public Tuple2<T, Void> call(T t) throws Exception {
              return new Tuple2<>(t, null);
            }
          });
      ShardTemplateInformation shardTemplateInfo =
          new ShardTemplateInformation(transform.getNumShards(),
              transform.getShardTemplate(), transform.getFilenamePrefix(),
              transform.getFilenameSuffix());
      writeHadoopFile(last, new Configuration(), shardTemplateInfo, Text.class,
          NullWritable.class, TemplatedTextOutputFormat.class);
    }
  };
}
项目:spark-dataflow    文件:TransformTranslator.java   
private static <T, W extends BoundedWindow> TransformEvaluator<Window.Bound<T>> window() {
  return new TransformEvaluator<Window.Bound<T>>() {
    @Override
    public void evaluate(Window.Bound<T> transform, EvaluationContext context) {
      @SuppressWarnings("unchecked")
      JavaRDDLike<WindowedValue<T>, ?> inRDD =
          (JavaRDDLike<WindowedValue<T>, ?>) context.getInputRDD(transform);
      WindowFn<? super T, W> windowFn = WINDOW_FG.get("windowFn", transform);
      if (windowFn instanceof GlobalWindows) {
        context.setOutputRDD(transform, inRDD);
      } else {
        @SuppressWarnings("unchecked")
        DoFn<T, T> addWindowsDoFn = new AssignWindowsDoFn<>(windowFn);
        DoFnFunction<T, T> dofn =
                new DoFnFunction<>(addWindowsDoFn, context.getRuntimeContext(), null);
        context.setOutputRDD(transform, inRDD.mapPartitions(dofn));
      }
    }
  };
}
项目:spark-dataflow    文件:EvaluationContext.java   
JavaRDDLike<WindowedValue<T>, ?> getRDD() {
  if (rdd == null) {
    Iterable<WindowedValue<T>> windowedValues = Iterables.transform(values,
        new Function<T, WindowedValue<T>>() {
        @Override
        public WindowedValue<T> apply(T t) {
         // TODO: this is wrong if T is a TimestampedValue
          return WindowedValue.valueInEmptyWindows(t);
        }
    });
    WindowedValue.ValueOnlyWindowedValueCoder<T> windowCoder =
        WindowedValue.getValueOnlyCoder(coder);
    rdd = jsc.parallelize(CoderHelpers.toByteArrays(windowedValues, windowCoder))
        .map(CoderHelpers.fromByteFunction(windowCoder));
  }
  return rdd;
}
项目:spark-dataflow    文件:EvaluationContext.java   
@Override
public <T> T get(PValue value) {
  if (pobjects.containsKey(value)) {
    @SuppressWarnings("unchecked")
    T result = (T) pobjects.get(value);
    return result;
  }
  if (pcollections.containsKey(value)) {
    JavaRDDLike<?, ?> rdd = pcollections.get(value).getRDD();
    @SuppressWarnings("unchecked")
    T res = (T) Iterables.getOnlyElement(rdd.collect());
    pobjects.put(value, res);
    return res;
  }
  throw new IllegalStateException("Cannot resolve un-known PObject: " + value);
}
项目:gcp    文件:IdleStop.java   
public static <A extends JavaRDDLike<?, ?>> VoidFunction<A> create(JavaStreamingContext jsc, long amount, String printf) {
  final LongAccumulator stopAcc = jsc.ssc().sc().longAccumulator();
  return rdd -> {
    if (printf != null)
      System.out.printf(printf, rdd.count());
    if (rdd.count() == 0L) {
      stopAcc.add(1L);
      if (stopAcc.value() >= amount)
        jsc.stop();
    } else
      stopAcc.reset();
  };
}
项目:Camel    文件:ConvertingRddCallback.java   
@Override
public T onRdd(JavaRDDLike rdd, Object... payloads) {
    if (payloads.length != payloadsTypes.length) {
        String message = format("Received %d payloads, but expected %d.", payloads.length, payloadsTypes.length);
        throw new IllegalArgumentException(message);
    }
    for (int i = 0; i < payloads.length; i++) {
        payloads[i] = camelContext.getTypeConverter().convertTo(payloadsTypes[i], payloads[i]);
    }
    return doOnRdd(rdd, payloads);
}
项目:Camel    文件:RddSparkProducer.java   
@Override
public void process(Exchange exchange) throws Exception {
    JavaRDDLike rdd = resolveRdd(exchange);
    RddCallback rddCallback = resolveRddCallback(exchange);
    Object body = exchange.getIn().getBody();
    Object result = body instanceof List ? rddCallback.onRdd(rdd, ((List) body).toArray(new Object[0])) : rddCallback.onRdd(rdd, body);
    collectResults(exchange, result);
}
项目:Camel    文件:RddSparkProducer.java   
protected JavaRDDLike resolveRdd(Exchange exchange) {
    if (exchange.getIn().getHeader(SPARK_RDD_HEADER) != null) {
        return (JavaRDD) exchange.getIn().getHeader(SPARK_RDD_HEADER);
    } else if (getEndpoint().getRdd() != null) {
        return getEndpoint().getRdd();
    } else {
        throw new IllegalStateException("No RDD defined.");
    }
}
项目:Camel    文件:SparkProducerTest.java   
@Test
public void shouldExecuteRddCallback() {
    long linesCount = template.requestBodyAndHeader(sparkUri, null, SPARK_RDD_CALLBACK_HEADER, new org.apache.camel.component.spark.RddCallback() {
        @Override
        public Long onRdd(JavaRDDLike rdd, Object... payloads) {
            return rdd.count();
        }
    }, Long.class);
    Truth.assertThat(linesCount).isEqualTo(numberOfLinesInTestFile);
}
项目:Camel    文件:SparkProducerTest.java   
@Test
public void shouldExecuteRddCallbackWithSinglePayload() {
    long linesCount = template.requestBodyAndHeader(sparkUri, 10, SPARK_RDD_CALLBACK_HEADER, new org.apache.camel.component.spark.RddCallback() {
        @Override
        public Long onRdd(JavaRDDLike rdd, Object... payloads) {
            return rdd.count() * (int) payloads[0];
        }
    }, Long.class);
    Truth.assertThat(linesCount).isEqualTo(numberOfLinesInTestFile * 10);
}
项目:Camel    文件:SparkProducerTest.java   
@Test
public void shouldExecuteRddCallbackWithPayloads() {
    long linesCount = template.requestBodyAndHeader(sparkUri, asList(10, 10), SPARK_RDD_CALLBACK_HEADER, new org.apache.camel.component.spark.RddCallback() {
        @Override
        public Long onRdd(JavaRDDLike rdd, Object... payloads) {
            return rdd.count() * (int) payloads[0] * (int) payloads[1];
        }
    }, Long.class);
    Truth.assertThat(linesCount).isEqualTo(numberOfLinesInTestFile * 10 * 10);
}
项目:Camel    文件:SparkProducerTest.java   
@Test
public void shouldExecuteRddCallbackWithTypedPayloads() {
    ConvertingRddCallback rddCallback = new ConvertingRddCallback<Long>(context, int.class, int.class) {
        @Override
        public Long doOnRdd(JavaRDDLike rdd, Object... payloads) {
            return rdd.count() * (int) payloads[0] * (int) payloads[1];
        }
    };
    long linesCount = template.requestBodyAndHeader(sparkUri, asList("10", "10"), SPARK_RDD_CALLBACK_HEADER, rddCallback, Long.class);
    Truth.assertThat(linesCount).isEqualTo(1900);
}
项目:spark4knime    文件:TableCellUtils.java   
/**
 * Read an RDD from BufferedDataTable table
 * 
 * @param table
 *            <code>BufferedDataTable</code>
 * @throws ClassCastException
 *             If <code>table</code> doesn't contain JavaRDDLike object
 * @return <code>JavaRDDLike</code> saved in <code>table</code>
 */
@SuppressWarnings("rawtypes")
public static JavaRDDLike getRDD(BufferedDataTable table) {
    DataCell dc = table.iterator().next().getCell(0);
    if (dc.getType() == RddCell.TYPE) {
        return ((RddCell) dc).getRDDValue();
    } else if (dc.getType() == PairRddCell.TYPE) {
        return ((PairRddCell) dc).getPairRDDValue();
    } else {
        throw new ClassCastException(
                "table contains non JavaRDDLike object");
    }
}
项目:spark4knime    文件:UnionNodeModel.java   
/**
 * {@inheritDoc}
 */
@SuppressWarnings({ "rawtypes", "unchecked" })
@Override
protected BufferedDataTable[] execute(final BufferedDataTable[] inData,
        final ExecutionContext exec) throws Exception {

    JavaRDDLike rdd;
    BufferedDataTable[] out;

    // create and save an
    if (TableCellUtils.isPairRDD(inData[0])) {
        if (TableCellUtils.isPairRDD(inData[1])) {
            rdd = ((JavaPairRDD) TableCellUtils.getRDD(inData[0]))
                    .union((JavaPairRDD) TableCellUtils.getRDD(inData[1]));
            out = new BufferedDataTable[] { TableCellUtils.setRDD(exec,
                    rdd, true) };
        } else {
            throw new IllegalArgumentException("RDD's must be of same type");
        }

    } else {
        if (TableCellUtils.isPairRDD(inData[1])) {
            throw new IllegalArgumentException("RDD's must be of same type");
        } else {
            rdd = ((JavaRDD) TableCellUtils.getRDD(inData[0]))
                    .union((JavaRDD) TableCellUtils.getRDD(inData[1]));
            out = new BufferedDataTable[] { TableCellUtils.setRDD(exec,
                    rdd, false) };
        }
    }

    // update viewer
    rddViewer = new RddViewer(out[0], exec);

    return out;
}
项目:spark4knime    文件:IntersectionNodeModel.java   
/**
 * {@inheritDoc}
 */
@SuppressWarnings({ "rawtypes", "unchecked" })
@Override
protected BufferedDataTable[] execute(final BufferedDataTable[] inData,
        final ExecutionContext exec) throws Exception {

    JavaRDDLike rdd;
    BufferedDataTable[] out;

    // create and save an intersection
    if (TableCellUtils.isPairRDD(inData[0])) {
        if (TableCellUtils.isPairRDD(inData[1])) {
            rdd = ((JavaPairRDD) TableCellUtils.getRDD(inData[0]))
                    .intersection((JavaPairRDD) TableCellUtils
                            .getRDD(inData[1]));
            out = new BufferedDataTable[] { TableCellUtils.setRDD(exec,
                    rdd, true) };
        } else {
            throw new IllegalArgumentException("RDD's must be of same type");
        }

    } else {
        if (TableCellUtils.isPairRDD(inData[1])) {
            throw new IllegalArgumentException("RDD's must be of same type");
        } else {
            rdd = ((JavaRDD) TableCellUtils.getRDD(inData[0]))
                    .intersection((JavaRDD) TableCellUtils
                            .getRDD(inData[1]));
            out = new BufferedDataTable[] { TableCellUtils.setRDD(exec,
                    rdd, false) };
        }
    }

    // update viewer
    rddViewer = new RddViewer(out[0], exec);

    return out;
}
项目:spark4knime    文件:SampleNodeModel.java   
/**
 * {@inheritDoc}
 */
@SuppressWarnings("rawtypes")
@Override
protected BufferedDataTable[] execute(final BufferedDataTable[] inData,
        final ExecutionContext exec) throws Exception {

    JavaRDDLike rdd;
    BufferedDataTable[] out;

    // create and save sample
    if (TableCellUtils.isPairRDD(inData[0])) {
        rdd = ((JavaPairRDD) TableCellUtils.getRDD(inData[0])).sample(
                m_replacement.getBooleanValue(),
                m_fraction.getIntValue() / 100.0, m_seed.getIntValue());
        out = new BufferedDataTable[] { TableCellUtils.setRDD(exec, rdd,
                true) };

    } else {
        rdd = ((JavaRDD) TableCellUtils.getRDD(inData[0])).sample(
                m_replacement.getBooleanValue(),
                m_fraction.getIntValue() / 100.0, m_seed.getIntValue());
        out = new BufferedDataTable[] { TableCellUtils.setRDD(exec, rdd,
                false) };
    }

    // update viewer
    rddViewer = new RddViewer(out[0], exec);

    return out;
}
项目:spark-dataflow    文件:TransformTranslator.java   
private static <K, VI, VO> TransformEvaluator<Combine.GroupedValues<K, VI, VO>> grouped() {
  return new TransformEvaluator<Combine.GroupedValues<K, VI, VO>>() {
    @Override
    public void evaluate(Combine.GroupedValues<K, VI, VO> transform, EvaluationContext context) {
      Combine.KeyedCombineFn<K, VI, ?, VO> keyed = GROUPED_FG.get("fn", transform);
      @SuppressWarnings("unchecked")
      JavaRDDLike<WindowedValue<KV<K, Iterable<VI>>>, ?> inRDD =
          (JavaRDDLike<WindowedValue<KV<K, Iterable<VI>>>, ?>) context.getInputRDD(transform);
      context.setOutputRDD(transform,
          inRDD.map(new KVFunction<>(keyed)));
    }
  };
}
项目:spark-dataflow    文件:TransformTranslator.java   
private static <K, V> JavaPairRDD<K, V> toPair(JavaRDDLike<KV<K, V>, ?> rdd) {
  return rdd.mapToPair(new PairFunction<KV<K, V>, K, V>() {
    @Override
    public Tuple2<K, V> call(KV<K, V> kv) {
      return new Tuple2<>(kv.getKey(), kv.getValue());
    }
  });
}
项目:spark-dataflow    文件:TransformTranslator.java   
private static <K, V> JavaRDDLike<KV<K, V>, ?> fromPair(JavaPairRDD<K, V> rdd) {
  return rdd.map(new Function<Tuple2<K, V>, KV<K, V>>() {
    @Override
    public KV<K, V> call(Tuple2<K, V> t2) {
      return KV.of(t2._1(), t2._2());
    }
  });
}
项目:spark-dataflow    文件:TransformTranslator.java   
private static <I, O> TransformEvaluator<ParDo.Bound<I, O>> parDo() {
  return new TransformEvaluator<ParDo.Bound<I, O>>() {
    @Override
    public void evaluate(ParDo.Bound<I, O> transform, EvaluationContext context) {
      DoFnFunction<I, O> dofn =
          new DoFnFunction<>(transform.getFn(),
              context.getRuntimeContext(),
              getSideInputs(transform.getSideInputs(), context));
      @SuppressWarnings("unchecked")
      JavaRDDLike<WindowedValue<I>, ?> inRDD =
          (JavaRDDLike<WindowedValue<I>, ?>) context.getInputRDD(transform);
      context.setOutputRDD(transform, inRDD.mapPartitions(dofn));
    }
  };
}
项目:spark-dataflow    文件:TransformTranslator.java   
private static <I, O> TransformEvaluator<ParDo.BoundMulti<I, O>> multiDo() {
  return new TransformEvaluator<ParDo.BoundMulti<I, O>>() {
    @Override
    public void evaluate(ParDo.BoundMulti<I, O> transform, EvaluationContext context) {
      TupleTag<O> mainOutputTag = MULTIDO_FG.get("mainOutputTag", transform);
      MultiDoFnFunction<I, O> multifn = new MultiDoFnFunction<>(
          transform.getFn(),
          context.getRuntimeContext(),
          mainOutputTag,
          getSideInputs(transform.getSideInputs(), context));

      @SuppressWarnings("unchecked")
      JavaRDDLike<WindowedValue<I>, ?> inRDD =
          (JavaRDDLike<WindowedValue<I>, ?>) context.getInputRDD(transform);
      JavaPairRDD<TupleTag<?>, WindowedValue<?>> all = inRDD
          .mapPartitionsToPair(multifn)
          .cache();

      PCollectionTuple pct = context.getOutput(transform);
      for (Map.Entry<TupleTag<?>, PCollection<?>> e : pct.getAll().entrySet()) {
        @SuppressWarnings("unchecked")
        JavaPairRDD<TupleTag<?>, WindowedValue<?>> filtered =
            all.filter(new TupleTagFilter(e.getKey()));
        @SuppressWarnings("unchecked")
        // Object is the best we can do since different outputs can have different tags
        JavaRDD<WindowedValue<Object>> values =
            (JavaRDD<WindowedValue<Object>>) (JavaRDD<?>) filtered.values();
        context.setRDD(e.getValue(), values);
      }
    }
  };
}
项目:spark-dataflow    文件:TransformTranslator.java   
private static <T> TransformEvaluator<AvroIO.Write.Bound<T>> writeAvro() {
  return new TransformEvaluator<AvroIO.Write.Bound<T>>() {
    @Override
    public void evaluate(AvroIO.Write.Bound<T> transform, EvaluationContext context) {
      Job job;
      try {
        job = Job.getInstance();
      } catch (IOException e) {
        throw new IllegalStateException(e);
      }
      AvroJob.setOutputKeySchema(job, transform.getSchema());
      @SuppressWarnings("unchecked")
      JavaPairRDD<AvroKey<T>, NullWritable> last =
          ((JavaRDDLike<WindowedValue<T>, ?>) context.getInputRDD(transform))
          .map(WindowingHelpers.<T>unwindowFunction())
          .mapToPair(new PairFunction<T, AvroKey<T>, NullWritable>() {
            @Override
            public Tuple2<AvroKey<T>, NullWritable> call(T t) throws Exception {
              return new Tuple2<>(new AvroKey<>(t), NullWritable.get());
            }
          });
      ShardTemplateInformation shardTemplateInfo =
          new ShardTemplateInformation(transform.getNumShards(),
          transform.getShardTemplate(), transform.getFilenamePrefix(),
          transform.getFilenameSuffix());
      writeHadoopFile(last, job.getConfiguration(), shardTemplateInfo,
          AvroKey.class, NullWritable.class, TemplatedAvroKeyOutputFormat.class);
    }
  };
}
项目:spark-dataflow    文件:TransformTranslator.java   
private static <K, V> TransformEvaluator<HadoopIO.Write.Bound<K, V>> writeHadoop() {
  return new TransformEvaluator<HadoopIO.Write.Bound<K, V>>() {
    @Override
    public void evaluate(HadoopIO.Write.Bound<K, V> transform, EvaluationContext context) {
      @SuppressWarnings("unchecked")
      JavaPairRDD<K, V> last = ((JavaRDDLike<WindowedValue<KV<K, V>>, ?>) context
          .getInputRDD(transform))
          .map(WindowingHelpers.<KV<K, V>>unwindowFunction())
          .mapToPair(new PairFunction<KV<K, V>, K, V>() {
            @Override
            public Tuple2<K, V> call(KV<K, V> t) throws Exception {
              return new Tuple2<>(t.getKey(), t.getValue());
            }
          });
      ShardTemplateInformation shardTemplateInfo =
          new ShardTemplateInformation(transform.getNumShards(),
              transform.getShardTemplate(), transform.getFilenamePrefix(),
              transform.getFilenameSuffix());
      Configuration conf = new Configuration();
      for (Map.Entry<String, String> e : transform.getConfigurationProperties().entrySet()) {
        conf.set(e.getKey(), e.getValue());
      }
      writeHadoopFile(last, conf, shardTemplateInfo,
          transform.getKeyClass(), transform.getValueClass(), transform.getFormatClass());
    }
  };
}
项目:spark-dataflow    文件:EvaluationContext.java   
Iterable<T> getValues(PCollection<T> pcollection) {
  if (values == null) {
    coder = pcollection.getCoder();
    JavaRDDLike<byte[], ?> bytesRDD = rdd.map(WindowingHelpers.<T>unwindowFunction())
        .map(CoderHelpers.toByteFunction(coder));
    List<byte[]> clientBytes = bytesRDD.collect();
    values = Iterables.transform(clientBytes, new Function<byte[], T>() {
      @Override
      public T apply(byte[] bytes) {
        return CoderHelpers.fromByteArray(bytes, coder);
      }
    });
  }
  return values;
}
项目:spark-dataflow    文件:EvaluationContext.java   
protected JavaRDDLike<?, ?> getRDD(PValue pvalue) {
  RDDHolder<?> rddHolder = pcollections.get(pvalue);
  JavaRDDLike<?, ?> rdd = rddHolder.getRDD();
  leafRdds.remove(rddHolder);
  if (multireads.contains(pvalue)) {
    // Ensure the RDD is marked as cached
    rdd.rdd().cache();
  } else {
    multireads.add(pvalue);
  }
  return rdd;
}
项目:spark-dataflow    文件:EvaluationContext.java   
protected <T> void setRDD(PValue pvalue, JavaRDDLike<WindowedValue<T>, ?> rdd) {
  try {
    rdd.rdd().setName(pvalue.getName());
  } catch (IllegalStateException e) {
    // name not set, ignore
  }
  RDDHolder<T> rddHolder = new RDDHolder<>(rdd);
  pcollections.put(pvalue, rddHolder);
  leafRdds.add(rddHolder);
}
项目:spark-dataflow    文件:EvaluationContext.java   
/**
 * Computes the outputs for all RDDs that are leaves in the DAG and do not have any
 * actions (like saving to a file) registered on them (i.e. they are performed for side
 * effects).
 */
protected void computeOutputs() {
  for (RDDHolder<?> rddHolder : leafRdds) {
    JavaRDDLike<?, ?> rdd = rddHolder.getRDD();
    rdd.rdd().cache(); // cache so that any subsequent get() is cheap
    rdd.count(); // force the RDD to be computed
  }
}
项目:deeplearning4j    文件:SharedTrainingMaster.java   
protected <T, Repr extends JavaRDDLike<T, Repr>> long getTotalDataSetObjectCount(
                JavaRDDLike<T, Repr> trainingData) {
    if (collectTrainingStats)
        stats.logCountStart();

    long totalDataSetObjectCount = trainingData.count();

    if (collectTrainingStats)
        stats.logCountEnd();

    return totalDataSetObjectCount;
}
项目:deeplearning4j    文件:ParameterAveragingTrainingMaster.java   
protected <T, Repr extends JavaRDDLike<T, Repr>> long getTotalDataSetObjectCount(
                JavaRDDLike<T, Repr> trainingData) {
    if (collectTrainingStats)
        stats.logCountStart();
    long totalDataSetObjectCount = trainingData.count();
    if (collectTrainingStats)
        stats.logCountEnd();
    return totalDataSetObjectCount;
}
项目:Camel    文件:VoidRddCallback.java   
@Override
public Void onRdd(JavaRDDLike rdd, Object... payloads) {
    doOnRdd(rdd, payloads);
    return null;
}
项目:Camel    文件:SparkEndpoint.java   
public JavaRDDLike getRdd() {
    return rdd;
}
项目:Camel    文件:SparkEndpoint.java   
/**
 * RDD to compute against.
 */
public void setRdd(JavaRDDLike rdd) {
    this.rdd = rdd;
}
项目:Camel    文件:SparkComponent.java   
public JavaRDDLike getRdd() {
    return rdd;
}
项目:Camel    文件:SparkComponent.java   
/**
 * RDD to compute against.
 */
public void setRdd(JavaRDDLike rdd) {
    this.rdd = rdd;
}
项目:Camel    文件:SparkComponentConfiguration.java   
public JavaRDDLike getRdd() {
    return rdd;
}