java - Spark DirectStream问题

我正在尝试从Kafka创建一个Spark Direct流，但是在创建directStream对象时出现以下错误：

类型为kafkaUtils的createDirectStream方法不适用于（我传递的HashMap参数之一）。

在这一行：
JavaPairInputDStream directKafkaStream = KafkaUtils.createDirectStream（ssc，String.class，
        String.class，StringDecoder.class，StringDecoder.class，kafkaParams，主题）；

完整代码：

package kafkatest2;



import java.util.Collections;
import java.util.HashMap;
import java.util.Map;
import java.util.Set;

import org.apache.commons.codec.StringDecoder;
import org.apache.spark.SparkConf;
import org.apache.spark.api.java.JavaSparkContext;
import org.apache.spark.streaming.Duration;
import org.apache.spark.streaming.api.java.JavaPairInputDStream;
import org.apache.spark.streaming.api.java.JavaStreamingContext;
import org.apache.spark.streaming.kafka.KafkaUtils;
import org.apache.spark.streaming.Duration;
import org.apache.spark.streaming.kafka010.*;
public class SparkStream {

    public static void main(String[] args) {

        SparkConf conf = new SparkConf()
                .setAppName("kafka-sandbox")
                .setMaster("local[*]");
        JavaSparkContext sc = new JavaSparkContext(conf);
        JavaStreamingContext ssc = new JavaStreamingContext(sc, new Duration(2000));

        // TODO: processing pipeline
       Map<String,String> kafkaParams = new HashMap<String,String>();
       kafkaParams.put("metadata.broker.list", "localhost:9092");

        Set<String> topics = Collections.singleton("topic5");

JavaPairInputDStream<String, String> directKafkaStream = KafkaUtils.createDirectStream(ssc,String.class,
        String.class, StringDecoder.class, StringDecoder.class, kafkaParams, topics);


        directKafkaStream.foreachRDD(rdd -> {
            System.out.println("--- New RDD with " + rdd.partitions().size()
                    + " partitions and " + rdd.count() + " records");
            rdd.foreach(record -> System.out.println(record._2));
        });
        ssc.start();
        ssc.awaitTermination();
    }
}

最佳答案

在您的代码中，使用了错误的StringDecoder。它应该是kafka.serializer.StringDecoder而不是org.apache.commons.codec.StringDecoder。

正确的代码如下：

package kafkatest2;



import java.util.Collections;
import java.util.HashMap;
import java.util.Map;
import java.util.Set;

import kafka.serializer.StringDecoder;
import org.apache.spark.SparkConf;
import org.apache.spark.api.java.JavaSparkContext;
import org.apache.spark.streaming.Duration;
import org.apache.spark.streaming.api.java.JavaPairInputDStream;
import org.apache.spark.streaming.api.java.JavaStreamingContext;
import org.apache.spark.streaming.kafka.KafkaUtils;
import org.apache.spark.streaming.Duration;
import org.apache.spark.streaming.kafka010.*;
public class SparkStream {

    public static void main(String[] args) {

        SparkConf conf = new SparkConf()
                .setAppName("kafka-sandbox")
                .setMaster("local[*]");
        JavaSparkContext sc = new JavaSparkContext(conf);
        JavaStreamingContext ssc = new JavaStreamingContext(sc, new Duration(2000));

        // TODO: processing pipeline
       Map<String,String> kafkaParams = new HashMap<String,String>();
       kafkaParams.put("metadata.broker.list", "localhost:9092");

        Set<String> topics = Collections.singleton("topic5");

JavaPairInputDStream<String, String> directKafkaStream = KafkaUtils.createDirectStream(ssc,String.class,
        String.class, StringDecoder.class, StringDecoder.class, kafkaParams, topics);


        directKafkaStream.foreachRDD(rdd -> {
            System.out.println("--- New RDD with " + rdd.partitions().size()
                    + " partitions and " + rdd.count() + " records");
            rdd.foreach(record -> System.out.println(record._2));
        });
        ssc.start();
        ssc.awaitTermination();
    }
}

希望对您有所帮助！