本文整理了Java中org.apache.flink.api.java.operators.UnsortedGrouping.min()方法的一些代码示例，展示了UnsortedGrouping.min()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。UnsortedGrouping.min()方法的具体详情如下：
包路径：org.apache.flink.api.java.operators.UnsortedGrouping
类名称：UnsortedGrouping
方法名：min

UnsortedGrouping.min介绍

[英]Syntactic sugar for aggregate (MIN, field).
[中]聚合的语法糖（MIN，field）。

代码示例

代码示例来源：origin: apache/flink

@Test
  public void testNestedAggregate() throws Exception {
    /*
     * Nested Aggregate
     */

    final ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();

    DataSet<Tuple3<Integer, Long, String>> ds = CollectionDataSets.get3TupleDataSet(env);
    DataSet<Tuple1<Integer>> aggregateDs = ds.groupBy(1)
        .min(0)
        .min(0)
        .project(0);

    List<Tuple1<Integer>> result = aggregateDs.collect();

    String expected = "1\n";

    compareResultAsTuples(result, expected);
  }
}

代码示例来源：origin: apache/flink

@Test
public void testConnectedComponentsWithParametrizableConvergence() throws Exception {
  // name of the aggregator that checks for convergence
  final String updatedElements = "updated.elements.aggr";
  // the iteration stops if less than this number of elements change value
  final long convergenceThreshold = 3;
  final ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
  DataSet<Tuple2<Long, Long>> initialSolutionSet = env.fromCollection(verticesInput);
  DataSet<Tuple2<Long, Long>> edges = env.fromCollection(edgesInput);
  IterativeDataSet<Tuple2<Long, Long>> iteration = initialSolutionSet.iterate(10);
  // register the convergence criterion
  iteration.registerAggregationConvergenceCriterion(updatedElements,
    new LongSumAggregator(), new UpdatedElementsConvergenceCriterion(convergenceThreshold));
  DataSet<Tuple2<Long, Long>> verticesWithNewComponents = iteration.join(edges).where(0).equalTo(0)
    .with(new NeighborWithComponentIDJoin())
    .groupBy(0).min(1);
  DataSet<Tuple2<Long, Long>> updatedComponentId =
    verticesWithNewComponents.join(iteration).where(0).equalTo(0)
      .flatMap(new MinimumIdFilter(updatedElements));
  List<Tuple2<Long, Long>> result = iteration.closeWith(updatedComponentId).collect();
  Collections.sort(result, new TestBaseUtils.TupleComparator<Tuple2<Long, Long>>());
  assertEquals(expectedResult, result);
}

代码示例来源：origin: apache/flink

@Test
public void testDeltaConnectedComponentsWithParametrizableConvergence() throws Exception {
  // name of the aggregator that checks for convergence
  final String updatedElements = "updated.elements.aggr";
  // the iteration stops if less than this number of elements change value
  final long convergenceThreshold = 3;
  final ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
  DataSet<Tuple2<Long, Long>> initialSolutionSet = env.fromCollection(verticesInput);
  DataSet<Tuple2<Long, Long>> edges = env.fromCollection(edgesInput);
  DeltaIteration<Tuple2<Long, Long>, Tuple2<Long, Long>> iteration =
    initialSolutionSet.iterateDelta(initialSolutionSet, 10, 0);
  // register the convergence criterion
  iteration.registerAggregationConvergenceCriterion(updatedElements,
    new LongSumAggregator(), new UpdatedElementsConvergenceCriterion(convergenceThreshold));
  DataSet<Tuple2<Long, Long>> verticesWithNewComponents = iteration.getWorkset().join(edges).where(0).equalTo(0)
    .with(new NeighborWithComponentIDJoin())
    .groupBy(0).min(1);
  DataSet<Tuple2<Long, Long>> updatedComponentId =
    verticesWithNewComponents.join(iteration.getSolutionSet()).where(0).equalTo(0)
      .flatMap(new MinimumIdFilter(updatedElements));
  List<Tuple2<Long, Long>> result = iteration.closeWith(updatedComponentId, updatedComponentId).collect();
  Collections.sort(result, new TestBaseUtils.TupleComparator<Tuple2<Long, Long>>());
  assertEquals(expectedResult, result);
}

代码示例来源：origin: apache/flink

.groupBy(0).min(1);

代码示例来源：origin: apache/flink

.min(1)
.name("Find Minimum Candidate Id");