本文整理了Java中org.apache.spark.api.java.JavaPairRDD.countApproxDistinctByKey()方法的一些代码示例，展示了JavaPairRDD.countApproxDistinctByKey()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.countApproxDistinctByKey()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：countApproxDistinctByKey

JavaPairRDD.countApproxDistinctByKey介绍

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代码示例

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

@Test
public void countApproxDistinctByKey() {
 List<Tuple2<Integer, Integer>> arrayData = new ArrayList<>();
 for (int i = 10; i < 100; i++) {
  for (int j = 0; j < i; j++) {
   arrayData.add(new Tuple2<>(i, j));
  }
 }
 double relativeSD = 0.001;
 JavaPairRDD<Integer, Integer> pairRdd = sc.parallelizePairs(arrayData);
 List<Tuple2<Integer, Long>> res =  pairRdd.countApproxDistinctByKey(relativeSD, 8).collect();
 for (Tuple2<Integer, Long> resItem : res) {
  double count = resItem._1();
  long resCount = resItem._2();
  double error = Math.abs((resCount - count) / count);
  assertTrue(error < 0.1);
 }
}

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

@Test
public void countApproxDistinctByKey() {
 List<Tuple2<Integer, Integer>> arrayData = new ArrayList<>();
 for (int i = 10; i < 100; i++) {
  for (int j = 0; j < i; j++) {
   arrayData.add(new Tuple2<>(i, j));
  }
 }
 double relativeSD = 0.001;
 JavaPairRDD<Integer, Integer> pairRdd = sc.parallelizePairs(arrayData);
 List<Tuple2<Integer, Long>> res =  pairRdd.countApproxDistinctByKey(relativeSD, 8).collect();
 for (Tuple2<Integer, Long> resItem : res) {
  double count = resItem._1();
  long resCount = resItem._2();
  double error = Math.abs((resCount - count) / count);
  assertTrue(error < 0.1);
 }
}

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

@Test
public void countApproxDistinctByKey() {
 List<Tuple2<Integer, Integer>> arrayData = new ArrayList<>();
 for (int i = 10; i < 100; i++) {
  for (int j = 0; j < i; j++) {
   arrayData.add(new Tuple2<>(i, j));
  }
 }
 double relativeSD = 0.001;
 JavaPairRDD<Integer, Integer> pairRdd = sc.parallelizePairs(arrayData);
 List<Tuple2<Integer, Long>> res =  pairRdd.countApproxDistinctByKey(relativeSD, 8).collect();
 for (Tuple2<Integer, Long> resItem : res) {
  double count = resItem._1();
  long resCount = resItem._2();
  double error = Math.abs((resCount - count) / count);
  assertTrue(error < 0.1);
 }
}