Hi Akil, It didnt work. Here is the code...
package com.paypal; import org.apache.spark.SparkConf; import org.apache.spark.storage.StorageLevel; import org.apache.spark.streaming.api.java.JavaPairInputDStream; import org.apache.spark.streaming.api.java.JavaStreamingContext; import org.apache.spark.api.java.*; import org.apache.spark.api.java.function.*; import org.apache.spark.streaming.*; import org.apache.spark.streaming.api.java.*; import com.google.common.collect.Lists; import org.apache.spark.streaming.receiver.Receiver; import scala.Tuple2; import java.net.ConnectException; import java.net.Socket; import java.util.Arrays; import java.util.regex.Pattern; import java.io.*; /** * Hello world! * */ public class App3 { private static final Pattern SPACE = Pattern.compile(" "); public static void main(String[] args) { // Create the context with a 1 second batch size SparkConf sparkConf = new SparkConf().setAppName("JavaNetworkWordCount"); // ******* always give local[4] to execute and see the output JavaStreamingContext ssc = new JavaStreamingContext("local[4]", "JavaNetworkWordCount", new Duration(5000)); // throws an error saying requires JavaPairDstream and not JavaDstream. JavaDStream<String> lines = ssc.fileStream("/Users/../Desktop/alarms.log"); JavaDStream<String> words = lines.flatMap( new FlatMapFunction<String, String>() { public Iterable<String> call(String s) { return Arrays.asList(s.split(" ")); } } ); JavaPairDStream<String, Integer> ones = words.map( new Function<String, Integer>() { public Tuple2<String, Integer> call(String s) { return new Tuple2(s, 1); } } ); JavaPairDStream<String, Integer> counts = ones.reduceByKey( new Function2<Integer, Integer, Integer>() { public Integer call(Integer i1, Integer i2) { return i1 + i2; } } ); System.out.println("Hello world"); wordCounts.print(); ssc.start(); ssc.awaitTermination(); } } I am not able to figure out how to type cast the objects of Type JavaPairDStream to JDstream. Can you provide me a working code for the same. Thanks in advance. Regards Aravindan -- View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/Spark-Streaming-using-File-Stream-in-Java-tp9115p9204.html Sent from the Apache Spark User List mailing list archive at Nabble.com.