org.apache.flink.api.java.operators.DataSink类的使用及代码示例

x33g5p2x  于2022-01-18 转载在 其他  
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本文整理了Java中org.apache.flink.api.java.operators.DataSink类的一些代码示例，展示了DataSink类的具体用法。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。DataSink类的具体详情如下：
包路径：org.apache.flink.api.java.operators.DataSink
类名称：DataSink

DataSink介绍

[英]An operation that allows storing data results.
[中]一种允许存储数据结果的操作。

代码示例

代码示例来源：origin: apache/flink

@Override
public void emitDataSet(DataSet<Row> dataSet) {
  dataSet
    .output(new Utils.CollectHelper<>(accumulatorName, serializer))
    .name("SQL Client Batch Collect Sink");
}

代码示例来源：origin: apache/flink

private void createTextSink(PythonOperationInfo info) {
  DataSet<byte[]> parent = sets.getDataSet(info.parentID);
  parent.map(new StringDeserializerMap()).setParallelism(info.parallelism)
    .writeAsText(info.path, info.writeMode).setParallelism(info.parallelism).name("TextSink");
}

代码示例来源：origin: apache/flink

/**
 * Emits a DataSet using an {@link OutputFormat}. This method adds a data sink to the program.
 * Programs may have multiple data sinks. A DataSet may also have multiple consumers (data sinks
 * or transformations) at the same time.
 *
 * @param outputFormat The OutputFormat to process the DataSet.
 * @return The DataSink that processes the DataSet.
 *
 * @see OutputFormat
 * @see DataSink
 */
public DataSink<T> output(OutputFormat<T> outputFormat) {
  Preconditions.checkNotNull(outputFormat);
  // configure the type if needed
  if (outputFormat instanceof InputTypeConfigurable) {
    ((InputTypeConfigurable) outputFormat).setInputType(getType(), context.getConfig());
  }
  DataSink<T> sink = new DataSink<>(this, outputFormat, getType());
  this.context.registerDataSink(sink);
  return sink;
}

代码示例来源：origin: apache/flink

private <T> GenericDataSinkBase<T> translate(DataSink<T> sink) {
  // translate the input recursively
  Operator<T> input = translate(sink.getDataSet());
  // translate the sink itself and connect it to the input
  GenericDataSinkBase<T> translatedSink = sink.translateToDataFlow(input);
  translatedSink.setResources(sink.getMinResources(), sink.getPreferredResources());
  return translatedSink;
}

代码示例来源：origin: apache/flink

@Test
public void testPojoSortingNestedParallelism1() throws Exception {
  final ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
  DataSet<CollectionDataSets.POJO> ds = CollectionDataSets.getMixedPojoDataSet(env);
  ds.writeAsText(resultPath)
    .sortLocalOutput("nestedTupleWithCustom.f0", Order.ASCENDING)
    .sortLocalOutput("nestedTupleWithCustom.f1.myInt", Order.DESCENDING)
    .sortLocalOutput("nestedPojo.longNumber", Order.ASCENDING)
    .setParallelism(1);
  env.execute();
  String expected =
      "2 First_ (10,105,1000,One) 10200\n" +
      "1 First (10,100,1000,One) 10100\n" +
      "4 First_ (11,106,1000,One) 10300\n" +
      "5 First (11,102,2000,One) 10100\n" +
      "3 First (11,102,3000,One) 10200\n" +
      "6 Second_ (20,200,2000,Two) 10100\n" +
      "8 Third_ (30,300,1000,Three) 10100\n" +
      "7 Third (31,301,2000,Three) 10200\n";
  compareResultsByLinesInMemoryWithStrictOrder(expected, resultPath);
}

代码示例来源：origin: apache/flink

private void createPrintSink(PythonOperationInfo info) {
  DataSet<byte[]> parent = sets.getDataSet(info.parentID);
  parent.map(new StringDeserializerMap()).setParallelism(info.parallelism).name("PrintSinkPreStep")
    .output(new PrintingOutputFormat<String>(info.toError)).setParallelism(info.parallelism);
}

代码示例来源：origin: dataArtisans/cascading-flink

.name(tap.getIdentifier())
.setParallelism(dop)
.withParameters(FlinkConfigConverter.toFlinkConfig(sinkConfig));

代码示例来源：origin: apache/flink

@Test
public void testTupleSortingNestedParallelism1_2() throws Exception {
  final ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
  DataSet<Tuple3<Tuple2<Integer, Integer>, String, Integer>> ds =
      CollectionDataSets.getGroupSortedNestedTupleDataSet2(env);
  ds.writeAsText(resultPath)
    .sortLocalOutput(1, Order.ASCENDING)
    .sortLocalOutput(2, Order.DESCENDING)
    .setParallelism(1);
  env.execute();
  String expected =
      "((2,1),a,3)\n" +
      "((1,3),a,2)\n" +
      "((1,2),a,1)\n" +
      "((2,2),b,4)\n" +
      "((4,9),c,7)\n" +
      "((3,6),c,6)\n" +
      "((3,3),c,5)\n";
  compareResultsByLinesInMemoryWithStrictOrder(expected, resultPath);
}

代码示例来源：origin: apache/flink

public static void main(String[] args) throws Exception {
  if (args.length < 2) {
    System.err.println("Usage: WordCount <input path> <result path>");
    return;
  }
  final String inputPath = args[0];
  final String outputPath = args[1];
  final ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
  // Set up the Hadoop Input Format
  HadoopInputFormat<LongWritable, Text> hadoopInputFormat = new HadoopInputFormat<LongWritable, Text>(new TextInputFormat(), LongWritable.class, Text.class, new JobConf());
  TextInputFormat.addInputPath(hadoopInputFormat.getJobConf(), new Path(inputPath));
  // Create a Flink job with it
  DataSet<Tuple2<LongWritable, Text>> text = env.createInput(hadoopInputFormat);
  DataSet<Tuple2<Text, LongWritable>> words =
      text.flatMap(new HadoopMapFunction<LongWritable, Text, Text, LongWritable>(new Tokenizer()))
        .groupBy(0).reduceGroup(new HadoopReduceCombineFunction<Text, LongWritable, Text, LongWritable>(new Counter(), new Counter()));
  // Set up Hadoop Output Format
  HadoopOutputFormat<Text, LongWritable> hadoopOutputFormat =
      new HadoopOutputFormat<Text, LongWritable>(new TextOutputFormat<Text, LongWritable>(), new JobConf());
  hadoopOutputFormat.getJobConf().set("mapred.textoutputformat.separator", " ");
  TextOutputFormat.setOutputPath(hadoopOutputFormat.getJobConf(), new Path(outputPath));
  // Output & Execute
  words.output(hadoopOutputFormat).setParallelism(1);
  env.execute("Hadoop Compat WordCount");
}

代码示例来源：origin: com.alibaba.blink/flink-java

private <T> GenericDataSinkBase<T> translate(DataSink<T> sink) {
  // translate the input recursively
  Operator<T> input = translate(sink.getDataSet());
  // translate the sink itself and connect it to the input
  GenericDataSinkBase<T> translatedSink = sink.translateToDataFlow(input);
  translatedSink.setResources(sink.getMinResources(), sink.getPreferredResources());
  return translatedSink;
}

代码示例来源：origin: apache/flink

@Override
public Count<T> run(DataSet<T> input)
    throws Exception {
  super.run(input);
  countHelper = new CountHelper<>();
  input
    .output(countHelper)
      .name("Count");
  return this;
}

代码示例来源：origin: apache/flink

private void createCsvSink(PythonOperationInfo info) {
  DataSet<byte[]> parent = sets.getDataSet(info.parentID);
  parent.map(new StringTupleDeserializerMap()).setParallelism(info.parallelism).name("CsvSinkPreStep")
      .writeAsCsv(info.path, info.lineDelimiter, info.fieldDelimiter, info.writeMode).setParallelism(info.parallelism).name("CsvSink");
}

代码示例来源：origin: apache/flink

@Test
public void testPojoSortingDualParallelism1() throws Exception {
  final ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
  DataSet<CollectionDataSets.POJO> ds = CollectionDataSets.getMixedPojoDataSet(env);
  ds.writeAsText(resultPath)
    .sortLocalOutput("str", Order.ASCENDING)
    .sortLocalOutput("number", Order.DESCENDING)
    .setParallelism(1);
  env.execute();
  String expected =
      "5 First (11,102,2000,One) 10100\n" +
      "3 First (11,102,3000,One) 10200\n" +
      "1 First (10,100,1000,One) 10100\n" +
      "4 First_ (11,106,1000,One) 10300\n" +
      "2 First_ (10,105,1000,One) 10200\n" +
      "6 Second_ (20,200,2000,Two) 10100\n" +
      "7 Third (31,301,2000,Three) 10200\n" +
      "8 Third_ (30,300,1000,Three) 10100\n";
  compareResultsByLinesInMemoryWithStrictOrder(expected, resultPath);
}

代码示例来源：origin: apache/flink

.writeAsText(outputPath, FileSystem.WriteMode.OVERWRITE).setParallelism(1);

代码示例来源：origin: org.apache.flink/flink-java

private <T> GenericDataSinkBase<T> translate(DataSink<T> sink) {
  // translate the input recursively
  Operator<T> input = translate(sink.getDataSet());
  // translate the sink itself and connect it to the input
  GenericDataSinkBase<T> translatedSink = sink.translateToDataFlow(input);
  translatedSink.setResources(sink.getMinResources(), sink.getPreferredResources());
  return translatedSink;
}

代码示例来源：origin: org.apache.flink/flink-java

/**
 * Emits a DataSet using an {@link OutputFormat}. This method adds a data sink to the program.
 * Programs may have multiple data sinks. A DataSet may also have multiple consumers (data sinks
 * or transformations) at the same time.
 *
 * @param outputFormat The OutputFormat to process the DataSet.
 * @return The DataSink that processes the DataSet.
 *
 * @see OutputFormat
 * @see DataSink
 */
public DataSink<T> output(OutputFormat<T> outputFormat) {
  Preconditions.checkNotNull(outputFormat);
  // configure the type if needed
  if (outputFormat instanceof InputTypeConfigurable) {
    ((InputTypeConfigurable) outputFormat).setInputType(getType(), context.getConfig());
  }
  DataSink<T> sink = new DataSink<>(this, outputFormat, getType());
  this.context.registerDataSink(sink);
  return sink;
}

代码示例来源：origin: apache/flink

@Override
public ChecksumHashCode<T> run(DataSet<T> input)
    throws Exception {
  super.run(input);
  checksumHashCodeHelper = new ChecksumHashCodeHelper<>();
  input
    .output(checksumHashCodeHelper)
      .name("ChecksumHashCode");
  return this;
}

代码示例来源：origin: apache/flink

@Override
public EdgeMetrics<K, VV, EV> run(Graph<K, VV, EV> input)
    throws Exception {
  super.run(input);
  // s, t, (d(s), d(t))
  DataSet<Edge<K, Tuple3<EV, LongValue, LongValue>>> edgeDegreePair = input
    .run(new EdgeDegreePair<K, VV, EV>()
      .setReduceOnTargetId(reduceOnTargetId)
      .setParallelism(parallelism));
  // s, d(s), count of (u, v) where deg(u) < deg(v) or (deg(u) == deg(v) and u < v)
  DataSet<Tuple3<K, LongValue, LongValue>> edgeStats = edgeDegreePair
    .map(new EdgeStats<>())
      .setParallelism(parallelism)
      .name("Edge stats")
    .groupBy(0)
    .reduce(new SumEdgeStats<>())
    .setCombineHint(CombineHint.HASH)
      .setParallelism(parallelism)
      .name("Sum edge stats");
  edgeMetricsHelper = new EdgeMetricsHelper<>();
  edgeStats
    .output(edgeMetricsHelper)
      .setParallelism(parallelism)
      .name("Edge metrics");
  return this;
}

代码示例来源：origin: apache/flink

@Test
public void testTupleSortingNestedParallelism1() throws Exception {
  final ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
  DataSet<Tuple3<Tuple2<Integer, Integer>, String, Integer>> ds =
      CollectionDataSets.getGroupSortedNestedTupleDataSet2(env);
  ds.writeAsText(resultPath)
    .sortLocalOutput("f0.f1", Order.ASCENDING)
    .sortLocalOutput("f1", Order.DESCENDING)
    .setParallelism(1);
  env.execute();
  String expected =
      "((2,1),a,3)\n" +
      "((2,2),b,4)\n" +
      "((1,2),a,1)\n" +
      "((3,3),c,5)\n" +
      "((1,3),a,2)\n" +
      "((3,6),c,6)\n" +
      "((4,9),c,7)\n";
  compareResultsByLinesInMemoryWithStrictOrder(expected, resultPath);
}

代码示例来源：origin: apache/flink

.output(new DiscardingOutputFormat<Long>()).setParallelism(5);

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