How to integrate Spark and Kafka for direct stream

问题

I am having difficulties creating a basic spark streaming application.

Right now, am trying it on my local machine.

I have done following setup.

-Setup Zookeeper

-Setup Kafka ( Version : kafka_2.10-0.9.0.1)

-Created a topic using below command

kafka-topics.bat --create --zookeeper localhost:2181 --replication-factor 1 --partitions 1 --topic test

-Started producer and consumer on two different cmd terminals using below commands

Producer :

kafka-console-producer.bat --broker-list localhost:9092 --topic test

Consumer :

kafka-console-consumer.bat --zookeeper localhost:2181 --topic test

Now I can receive the data which I enter in the producer terminal in consumer console.

Now am trying to integrate Kafka into Apache Spark streaming.

Below is a sample code which I referenced from official documents. Kafka & Spark Setup and Kafka & Spark Integration

public class KafkaStreamingTry {
    static Map<String, Object> kafkaParams = new HashMap<>();


    public static void main(String[] args) throws InterruptedException, StreamingQueryException {
        // Create a local StreamingContext with two working thread and batch interval of 1 second
        SparkConf conf = new SparkConf().setMaster("local[*]").setAppName("Sampleapp");
        JavaStreamingContext jssc = new JavaStreamingContext(conf, Durations.seconds(10));

        kafkaParams.put("bootstrap.servers", "localhost:9092");
        kafkaParams.put("key.deserializer", StringDeserializer.class);
        kafkaParams.put("value.deserializer", StringDeserializer.class);
        kafkaParams.put("group.id", "0");
        kafkaParams.put("auto.offset.reset", "earliest"); // from-beginning?
        kafkaParams.put("enable.auto.commit", false);

        Collection<String> topics = Arrays.asList("test");

        final JavaInputDStream<ConsumerRecord<String, String>> stream =
                KafkaUtils.createDirectStream(
                        jssc,
                        LocationStrategies.PreferConsistent(),
                        ConsumerStrategies.<String, String>Subscribe(topics, kafkaParams)
                );


        System.out.println("Direct Stream created? ");
        stream.mapToPair(
                new PairFunction<ConsumerRecord<String, String>, String, String>() {
                    @Override
                    public Tuple2<String, String> call(ConsumerRecord<String, String> record) throws Exception {
                        System.out.println("record key : "+record.key()+" value is : "+record.value());
                        return new Tuple2<>(record.key(), record.value());
                    }
                });

        System.out.println("Reached the end.");
    }
}

If I run this program, following is the log.

    "C:\Program Files\Java\jdk1.8.0_11\bin\java" "-javaagent:C:\Program Files\JetBrains\IntelliJ IDEA Community Edition 2017.1.4\lib\idea_rt.jar=51332:C:\Program Files\JetBrains\IntelliJ IDEA Community Edition 2017.1.4\bin" -Dfile.encoding=UTF-8 -classpath "C:\Program Files\Java\jdk1.8.0_11\jre\lib\charsets.jar;C:\Program Files\Java\jdk1.8.0_11\jre\lib\deploy.jar;C:\Program Files\Java\jdk1.8.0_11\jre\lib\ext\access-bridge-64.jar;C:\Program Files\Java\jdk1.8.0_11\jre\lib\ext\cldrdata.jar;C:\Program Files\Java\jdk1.8.0_11\jre\lib\ext\dnsns.jar;C:\Program Files\Java\jdk1.8.0_11\jre\lib\ext\jaccess.jar;C:\Program Files\Java\jdk1.8.0_11\jre\lib\ext\jfxrt.jar;C:\Program Files\Java\jdk1.8.0_11\jre\lib\ext\localedata.jar;C:\Program Files\Java\jdk1.8.0_11\jre\lib\ext\nashorn.jar;C:\Program Files\Java\jdk1.8.0_11\jre\lib\ext\sunec.jar;C:\Program Files\Java\jdk1.8.0_11\jre\lib\ext\sunjce_provider.jar;C:\Program Files\Java\jdk1.8.0_11\jre\lib\ext\sunmscapi.jar;C:\Program 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kafkatry
    Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
    17/07/03 01:23:55 INFO SparkContext: Running Spark version 2.1.0
    17/07/03 01:23:55 WARN SparkContext: Support for Scala 2.10 is deprecated as of Spark 2.1.0
    17/07/03 01:23:56 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
    17/07/03 01:23:56 INFO SecurityManager: Changing view acls to: driftking9987
    17/07/03 01:23:56 INFO SecurityManager: Changing modify acls to: driftking9987
    17/07/03 01:23:56 INFO SecurityManager: Changing view acls groups to: 
    17/07/03 01:23:56 INFO SecurityManager: Changing modify acls groups to: 
    17/07/03 01:23:56 INFO SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users  with view permissions: Set(driftking9987); groups with view permissions: Set(); users  with modify permissions: Set(driftking9987); groups with modify permissions: Set()
    17/07/03 01:23:57 INFO Utils: Successfully started service 'sparkDriver' on port 51353.
    17/07/03 01:23:57 INFO SparkEnv: Registering MapOutputTracker
    17/07/03 01:23:57 INFO SparkEnv: Registering BlockManagerMaster
    17/07/03 01:23:57 INFO BlockManagerMasterEndpoint: Using org.apache.spark.storage.DefaultTopologyMapper for getting topology information
    17/07/03 01:23:57 INFO BlockManagerMasterEndpoint: BlockManagerMasterEndpoint up
    17/07/03 01:23:58 INFO DiskBlockManager: Created local directory at C:\Users\driftking9987\AppData\Local\Temp\blockmgr-4535fb48-e3c2-4af7-a57a-c5c54c2d9ed1
    17/07/03 01:23:58 INFO MemoryStore: MemoryStore started with capacity 352.5 MB
    17/07/03 01:23:58 INFO SparkEnv: Registering OutputCommitCoordinator
    17/07/03 01:23:58 INFO Utils: Successfully started service 'SparkUI' on port 4040.
    17/07/03 01:23:58 INFO SparkUI: Bound SparkUI to 0.0.0.0, and started at http://192.168.56.1:4040
    17/07/03 01:23:59 INFO Executor: Starting executor ID driver on host localhost
    17/07/03 01:23:59 INFO Utils: Successfully started service 'org.apache.spark.network.netty.NettyBlockTransferService' on port 51374.
    17/07/03 01:23:59 INFO NettyBlockTransferService: Server created on 192.168.56.1:51374
    17/07/03 01:23:59 INFO BlockManager: Using org.apache.spark.storage.RandomBlockReplicationPolicy for block replication policy
    17/07/03 01:23:59 INFO BlockManagerMaster: Registering BlockManager BlockManagerId(driver, 192.168.56.1, 51374, None)
    17/07/03 01:23:59 INFO BlockManagerMasterEndpoint: Registering block manager 192.168.56.1:51374 with 352.5 MB RAM, BlockManagerId(driver, 192.168.56.1, 51374, None)
    17/07/03 01:23:59 INFO BlockManagerMaster: Registered BlockManager BlockManagerId(driver, 192.168.56.1, 51374, None)
    17/07/03 01:23:59 INFO BlockManager: Initialized BlockManager: BlockManagerId(driver, 192.168.56.1, 51374, None)
    17/07/03 01:24:00 WARN KafkaUtils: overriding enable.auto.commit to false for executor
    17/07/03 01:24:00 WARN KafkaUtils: overriding auto.offset.reset to none for executor
    17/07/03 01:24:00 WARN KafkaUtils: overriding executor group.id to spark-executor-0
    17/07/03 01:24:00 WARN KafkaUtils: overriding receive.buffer.bytes to 65536 see KAFKA-3135
    17/07/03 01:24:00 INFO SparkContext: Invoking stop() from shutdown hook
    17/07/03 01:24:00 INFO SparkUI: Stopped Spark web UI at http://192.168.56.1:4040
    17/07/03 01:24:00 INFO MapOutputTrackerMasterEndpoint: MapOutputTrackerMasterEndpoint stopped!
    17/07/03 01:24:00 INFO MemoryStore: MemoryStore cleared
    17/07/03 01:24:00 INFO BlockManager: BlockManager stopped
    17/07/03 01:24:00 INFO BlockManagerMaster: BlockManagerMaster stopped
    17/07/03 01:24:00 INFO OutputCommitCoordinator$OutputCommitCoordinatorEndpoint: OutputCommitCoordinator stopped!
    17/07/03 01:24:00 INFO SparkContext: Successfully stopped SparkContext
    17/07/03 01:24:00 INFO ShutdownHookManager: Shutdown hook called
    17/07/03 01:24:00 INFO ShutdownHookManager: Deleting directory C:\Users\driftking9987\AppData\Local\Temp\spark-cd270e2f-257c-4878-88b4-8f908d65f76a

Process finished with exit code 0

Now if I add

jssc.start();// Start the computation
jssc.awaitTermination();

It gives below following error,

17/07/03 01:26:46 ERROR StreamingContext: Error starting the context, marking it as stopped
java.lang.IllegalArgumentException: requirement failed: No output operations registered, so nothing to execute
    at scala.Predef$.require(Predef.scala:233)
    at org.apache.spark.streaming.DStreamGraph.validate(DStreamGraph.scala:163)
    at org.apache.spark.streaming.StreamingContext.validate(StreamingContext.scala:513)
    at org.apache.spark.streaming.StreamingContext.liftedTree1$1(StreamingContext.scala:573)
    at org.apache.spark.streaming.StreamingContext.start(StreamingContext.scala:572)
    at org.apache.spark.streaming.api.java.JavaStreamingContext.start(JavaStreamingContext.scala:556)
    at KafkaStreamingTry.main(KafkaStreamingTry.java:74)
Exception in thread "main" java.lang.IllegalArgumentException: requirement failed: No output operations registered, so nothing to execute
    at scala.Predef$.require(Predef.scala:233)
    at org.apache.spark.streaming.DStreamGraph.validate(DStreamGraph.scala:163)
    at org.apache.spark.streaming.StreamingContext.validate(StreamingContext.scala:513)
    at org.apache.spark.streaming.StreamingContext.liftedTree1$1(StreamingContext.scala:573)
    at org.apache.spark.streaming.StreamingContext.start(StreamingContext.scala:572)
    at org.apache.spark.streaming.api.java.JavaStreamingContext.start(JavaStreamingContext.scala:556)
    at KafkaStreamingTry.main(KafkaStreamingTry.java:74)
17/07/03 01:26:46 INFO SparkContext: Invoking stop() from shutdown hook
17/07/03 01:26:46 INFO SparkUI: Stopped Spark web UI at http://192.168.56.1:4040
17/07/03 01:26:46 INFO MapOutputTrackerMasterEndpoint: MapOutputTrackerMasterEndpoint stopped!
17/07/03 01:26:46 INFO MemoryStore: MemoryStore cleared
17/07/03 01:26:46 INFO BlockManager: BlockManager stopped
17/07/03 01:26:46 INFO BlockManagerMaster: BlockManagerMaster stopped
17/07/03 01:26:46 INFO OutputCommitCoordinator$OutputCommitCoordinatorEndpoint: OutputCommitCoordinator stopped!
17/07/03 01:26:46 INFO SparkContext: Successfully stopped SparkContext
17/07/03 01:26:46 INFO ShutdownHookManager: Shutdown hook called

Which is obvious.

Can please tell me how can I make it run? My requirement is that whenever I enter any data in producer terminal, the java application should acknowledge it and atleast print it once. I will try to figure out the calculation part on the json which I will receive.

This is a question which I asked before and trying to follow the suggested architecture.

Thanks

EDIT:

POM.XML

<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0"
         xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
         xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
    <modelVersion>4.0.0</modelVersion>

    <groupId>com.cs</groupId>
    <artifactId>sparktest</artifactId>
    <version>1.0-SNAPSHOT</version>
    <build>
        <plugins>
            <plugin>
                <groupId>org.apache.maven.plugins</groupId>
                <artifactId>maven-compiler-plugin</artifactId>
                <configuration>
                    <source>1.8</source>
                    <target>1.8</target>
                </configuration>
            </plugin>
        </plugins>
    </build>
    <dependencies>
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-streaming_2.10</artifactId>
            <version>2.1.0</version>
        </dependency>
        <!-- https://mvnrepository.com/artifact/org.apache.spark/spark-core_2.10 -->
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-core_2.10</artifactId>
            <version>2.1.0</version>
        </dependency>


        <dependency>
            <groupId>org.scala-lang</groupId>
            <artifactId>scala-library</artifactId>
            <version>2.10.6</version>
        </dependency>
        <!--For kafka integgration-->
        <!-- https://mvnrepository.com/artifact/org.apache.spark/spark-streaming-kafka-0-10_2.10 -->
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-streaming-kafka-0-10_2.10</artifactId>
            <version>2.1.1</version>
        </dependency>

        <!-- https://mvnrepository.com/artifact/org.apache.kafka/kafka_2.10 -->
        <dependency>
            <groupId>org.apache.kafka</groupId>
            <artifactId>kafka_2.10</artifactId>
            <version>0.10.2.1</version>
        </dependency>
        <!-- https://mvnrepository.com/artifact/org.apache.spark/spark-sql_2.10 -->
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-sql_2.10</artifactId>
            <version>2.1.1</version>
        </dependency>
        <!-- https://mvnrepository.com/artifact/org.apache.spark/spark-sql-kafka-0-10_2.11 -->
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-sql-kafka-0-10_2.11</artifactId>
            <version>2.1.1</version>
        </dependency>



    </dependencies>
</project>

回答1:

After creating the direct stream with Kafka you create JavaPairDStream. Now you can iterate the JavaPairDStream and print the key and value of your Kafka messages.

JavaPairDStream<String, String> jPairDStream =  stream.mapToPair(
        new PairFunction<ConsumerRecord<String, String>, String, String>() {
            @Override
            public Tuple2<String, String> call(ConsumerRecord<String, String> record) throws Exception {
                return new Tuple2<>(record.key(), record.value());
            }
        });

jPairDStream.foreachRDD(jPairRDD -> {
       jPairRDD.foreach(rdd -> {
            System.out.println("key="+rdd._1()+" value="+rdd._2());
        });
    });

jssc.start();            
jssc.awaitTermination(); 

The command you are using with kafka-console-producer.bat will produce message in which key will be null. In order to produce messages with both key and value on topic test use below command. Enter comma separated key and value in console like key1,value1

kafka-console-producer.bat --property parse.key=true --property key.separator=, --broker-list localhost:9092 --topic test

Your pom file has different versions for spark artifacts. Make sure you use same version for all artifacts. You need following dependencies to run your program.

<dependencies>
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-core_2.11</artifactId>
            <version>2.1.0</version>
        </dependency>
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-sql_2.11</artifactId>
            <version>2.1.0</version>
        </dependency>
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-streaming_2.11</artifactId>
            <version>2.1.0</version>
        </dependency>
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-streaming-kafka-0-10_2.11</artifactId>
            <version>2.1.0</version>
        </dependency>
</dependencies>

回答2:

I think that logs says everything you need :)

IllegalArgumentException: requirement failed: No output operations registered, so nothing to execute

What are output operations? For example:

• foreachRDD
• print
• saveAsHadoopFile
• and other. More you can get in this link to the documentation.

You must add some operation to your application, for example save stream.mapToPair to variable and then invoke foreachRDD on this variable or print() to show values

回答3:

for your code add a action may help

stream.print()

Have a try and wish you good luck

回答4:

i think you are not starting the stream using ssc.start()

来源：https://stackoverflow.com/questions/44874873/how-to-integrate-spark-and-kafka-for-direct-stream