如何将Spark和Kafka集成到直接流

时间：2017-07-02 20:19:18

标签： java apache-spark apache-kafka spark-streaming

我在创建基本的火花流应用程序时遇到了困难。

现在，我正在我的本地机器上尝试。

我已完成以下设置。

-Setup Zookeeper

-Setup Kafka（版本：kafka_2.10-0.9.0.1）

使用以下命令

处理主题

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

- 使用以下命令在两个不同的cmd终端上启动生产者和消费者

制片人：

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

消费者：

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

现在我可以收到我在消费者控制台的生产者终端中输入的数据。

现在我正在尝试将Kafka集成到Apache Spark流媒体中。

以下是我从官方文档中引用的示例代码。 Kafka & Spark Setup和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.");
    }
}

如果我运行此程序，则以下是日志。

    "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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container-servlet-2.22.2.jar;C:\Users\driftking9987\.m2\repository\org\glassfish\jersey\containers\jersey-container-servlet-core\2.22.2\jersey-container-servlet-core-2.22.2.jar;C:\Users\driftking9987\.m2\repository\io\netty\netty-all\4.0.42.Final\netty-all-4.0.42.Final.jar;C:\Users\driftking9987\.m2\repository\io\netty\netty\3.8.0.Final\netty-3.8.0.Final.jar;C:\Users\driftking9987\.m2\repository\com\clearspring\analytics\stream\2.7.0\stream-2.7.0.jar;C:\Users\driftking9987\.m2\repository\io\dropwizard\metrics\metrics-core\3.1.2\metrics-core-3.1.2.jar;C:\Users\driftking9987\.m2\repository\io\dropwizard\metrics\metrics-jvm\3.1.2\metrics-jvm-3.1.2.jar;C:\Users\driftking9987\.m2\repository\io\dropwizard\metrics\metrics-json\3.1.2\metrics-json-3.1.2.jar;C:\Users\driftking9987\.m2\repository\io\dropwizard\metrics\metrics-graphite\3.1.2\metrics-graphite-3.1.2.jar;C:\Users\driftking9987\.m2\repository\com\fasterxml\jackson\core\jackson-databind\2.6.5\jackson-databind-2.6.5.jar;C:\Users\driftking9987\.m2\repository\com\fasterxml\jackson\core\jackson-core\2.6.5\jackson-core-2.6.5.jar;C:\Users\driftking9987\.m2\repository\com\fasterxml\jackson\module\jackson-module-scala_2.10\2.6.5\jackson-module-scala_2.10-2.6.5.jar;C:\Users\driftking9987\.m2\repository\org\scala-lang\scala-reflect\2.10.6\scala-reflect-2.10.6.jar;C:\Users\driftking9987\.m2\repository\com\fasterxml\jackson\module\jackson-module-paranamer\2.6.5\jackson-module-paranamer-2.6.5.jar;C:\Users\driftking9987\.m2\repository\org\apache\ivy\ivy\2.4.0\ivy-2.4.0.jar;C:\Users\driftking9987\.m2\repository\oro\oro\2.0.8\oro-2.0.8.jar;C:\Users\driftking9987\.m2\repository\net\razorvine\pyrolite\4.13\pyrolite-4.13.jar;C:\Users\driftking9987\.m2\repository\net\sf\py4j\py4j\0.10.4\py4j-0.10.4.jar;C:\Users\driftking9987\.m2\repository\org\apache\commons\commons-crypto\1.0.0\commons-crypto-1.0.0.jar;C:\Users\driftking9987\.m2\repository\org\scala-lang\scala-library\2.10.6\scala-library-2.10.6.jar;C:\Users\driftking9987\.m2\repository\org\apache\spark\spark-streaming-kafka-0-10_2.10\2.1.1\spark-streaming-kafka-0-10_2.10-2.1.1.jar;C:\Users\driftking9987\.m2\repository\org\apache\kafka\kafka_2.10\0.10.2.1\kafka_2.10-0.10.2.1.jar;C:\Users\driftking9987\.m2\repository\org\apache\kafka\kafka-clients\0.10.2.1\kafka-clients-0.10.2.1.jar;C:\Users\driftking9987\.m2\repository\net\sf\jopt-simple\jopt-simple\5.0.3\jopt-simple-5.0.3.jar;C:\Users\driftking9987\.m2\repository\com\yammer\metrics\metrics-core\2.2.0\metrics-core-2.2.0.jar;C:\Users\driftking9987\.m2\repository\com\101tec\zkclient\0.10\zkclient-0.10.jar;C:\Users\driftking9987\.m2\repository\org\apache\zookeeper\zookeeper\3.4.9\zookeeper-3.4.9.jar;C:\Users\driftking9987\.m2\repository\org\apache\spark\spark-sql_2.10\2.1.1\spark-sql_2.10-2.1.1.jar;C:\Users\driftking9987\.m2\repository\com\univocity\univocity-parsers\2.2.1\univocity-parsers-2.2.1.jar;C:\Users\driftking9987\.m2\repository\org\apache\spark\spark-sketch_2.10\2.1.1\spark-sketch_2.10-2.1.1.jar;C:\Users\driftking9987\.m2\repository\org\apache\spark\spark-catalyst_2.10\2.1.1\spark-catalyst_2.10-2.1.1.jar;C:\Users\driftking9987\.m2\repository\org\codehaus\janino\janino\3.0.0\janino-3.0.0.jar;C:\Users\driftking9987\.m2\repository\org\codehaus\janino\commons-compiler\3.0.0\commons-compiler-3.0.0.jar;C:\Users\driftking9987\.m2\repository\org\antlr\antlr4-runtime\4.5.3\antlr4-runtime-4.5.3.jar;C:\Users\driftking9987\.m2\repository\org\apache\parquet\parquet-column\1.8.1\parquet-column-1.8.1.jar;C:\Users\driftking9987\.m2\repository\org\apache\parquet\parquet-common\1.8.1\parquet-common-1.8.1.jar;C:\Users\driftking9987\.m2\repository\org\apache\parquet\parquet-encoding\1.8.1\parquet-encoding-1.8.1.jar;C:\Users\driftking9987\.m2\repository\org\apache\parquet\parquet-hadoop\1.8.1\parquet-hadoop-1.8.1.jar;C:\Users\driftking9987\.m2\repository\org\apache\parquet\parquet-format\2.3.0-incubating\parquet-format-2.3.0-incubating.jar;C:\Users\driftking9987\.m2\repository\org\apache\parquet\parquet-jackson\1.8.1\parquet-jackson-1.8.1.jar;C:\Users\driftking9987\.m2\repository\org\apache\spark\spark-sql-kafka-0-10_2.11\2.1.1\spark-sql-kafka-0-10_2.11-2.1.1.jar;C:\Users\driftking9987\.m2\repository\org\apache\spark\spark-tags_2.11\2.1.1\spark-tags_2.11-2.1.1.jar" 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

现在如果我添加

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

它给出了以下错误，

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

这是显而易见的。

请告诉我如何让它运行？我的要求是每当我在生产者终端中输入任何数据时，java应用程序应该确认它并且至少打印一次。我将尝试弄清楚我将收到的json上的计算部分。

This是我之前提出的问题，并尝试遵循建议的架构。

由于

修改

的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>

4 个答案:

答案 0 :(得分：3)

我认为日志说明了你需要的一切:)

  

IllegalArgumentException：要求失败：未注册任何输出操作，因此无需执行任何操作

什么是输出操作？例如：

  • foreachRDD
  • 打印
  • saveAsHadoopFile
  • 等。您可以通过此link获取更多文档。

您必须向应用程序添加一些操作，例如将stream.mapToPair保存到变量，然后在此变量上调用foreachRDD或print（）以显示值

答案 1 :(得分：3)

使用Kafka创建直接流后，您可以创建JavaPairDStream。现在，您可以迭代JavaPairDStream并打印Kafka消息的密钥和值。

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();

您与kafka-console-producer.bat一起使用的命令将生成一个消息，其中键将为空。为了在主题test上生成具有键和值的消息，请使用以下命令。在控制台中输入逗号分隔的键和值，例如key1,value1 

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

你的pom文件有不同版本的spark构件。确保对所有工件使用相同的版本。您需要以下依赖项来运行您的程序。

<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>

答案 2 :(得分：0)

为您的代码添加操作可能会有所帮助

stream.print()

试一试，祝你好运

答案 3 :(得分：0)

我认为您不是在使用ssc.start（）启动流

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