Java Code Examples for org.apache.spark.api.java.JavaRDD#cartesian()
The following examples show how to use
org.apache.spark.api.java.JavaRDD#cartesian() .
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Example 1
Source File: Cartesian.java From SparkDemo with MIT License | 6 votes |
private static void cartesian(JavaSparkContext sc) { List<String> names = Arrays.asList("张三", "李四", "王五"); List<Integer> scores = Arrays.asList(60, 70, 80); JavaRDD<String> namesRDD = sc.parallelize(names); JavaRDD<Integer> scoreRDD = sc.parallelize(scores); /** * ===================================== * | 两个RDD进行笛卡尔积合并 | * | The two RDD are Cartesian product merging | | * ===================================== */ JavaPairRDD<String, Integer> cartesianRDD = namesRDD.cartesian(scoreRDD); cartesianRDD.foreach(new VoidFunction<Tuple2<String, Integer>>() { public void call(Tuple2<String, Integer> t) throws Exception { System.out.println(t._1 + "\t" + t._2()); } }); }
Example 2
Source File: TransformationRDD.java From hui-bigdata-spark with Apache License 2.0 | 5 votes |
/** * 笛卡尔积. * demo计算目的:超人VS怪兽所有组合 * * @since hui_project 1.0.0 */ public void testCartesain() { SparkConf sparkConf = new SparkConf().setMaster("local[4]").setAppName("test"); JavaSparkContext sparkContext = new JavaSparkContext(sparkConf); JavaRDD<String> list1 = sparkContext.parallelize(Arrays.asList("咸蛋超人VS", "蒙面超人VS", "奥特曼VS")); JavaRDD<String> list2 = sparkContext.parallelize(Arrays.asList("小怪兽", "中怪兽", "大怪兽")); JavaPairRDD<String, String> cartesian = list1.cartesian(list2); checkResult(cartesian.collect()); }
Example 3
Source File: TransformationRDDTest.java From hui-bigdata-spark with Apache License 2.0 | 5 votes |
/** * 笛卡尔积. * demo计算目的:超人VS怪兽所有组合 * @since hui_project 1.0.0 */ @Test public void testCartesain() { JavaRDD<String> list1 = sparkContext.parallelize(Arrays.asList("咸蛋超人VS", "蒙面超人VS", "奥特曼VS")); JavaRDD<String> list2 = sparkContext.parallelize(Arrays.asList("小怪兽", "中怪兽", "大怪兽")); JavaPairRDD<String, String> cartesian = list1.cartesian(list2); checkResult(cartesian.collect()); }