【Spark学习笔记】2、Java版-算子系列之filter(f:T => Boolean) : RDD[T] => RDD[T]

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本文深入探讨了Spark中filter算子的源码实现及其工作原理。通过Java代码示例展示了如何使用filter算子从RDD中筛选出特定元素，具体演示了筛选偶数的过程。filter算子是Spark的重要算子之一，用于数据清洗和预处理。

filter算子源码

def filter(f: T => Boolean): RDD[T] = withScope {
  val cleanF = sc.clean(f)
  new MapPartitionsRDD[T, T](
    this,
    (context, pid, iter) => iter.filter(cleanF),
    preservesPartitioning = true)
}

Java代码demo

public class FilterOperator {

	public static void main(String[] args) {
		SparkConf conf = new SparkConf().setAppName("FilterOperator").setMaster("local[2]");
		JavaSparkContext sc = new JavaSparkContext(conf);

		List<Integer> numbers = Arrays.asList(1, 2, 3, 4, 5);
		JavaRDD<Integer> numberRDD = sc.parallelize(numbers);

		/**
		 * Return a new dataset formed by selecting those elements of the source on which func returns true.
		 * 
		 * filter算子是过滤，逻辑返回true保留，false就过滤掉
		 */

		JavaRDD<Integer> results = numberRDD.filter(new Function<Integer, Boolean>() {
			private static final long serialVersionUID = 1L;

			@Override
			public Boolean call(Integer number) throws Exception {
				return number % 2 == 0;
			}
		});
		results.foreach(new VoidFunction<Integer>() {
			private static final long serialVersionUID = 1L;

			@Override
			public void call(Integer result) throws Exception {
				System.out.println(result);
			}
		});
		sc.close();
	}
}

输出