如何整合Spark和Kafka直接流

我在創建基本Spark流應用程序時遇到困難。如何整合Spark和Kafka直接流

現在，我在本地機器上試用它。

我已經完成以下設置。

-SETUP動物園管理員

-SETUP卡夫卡（版本：kafka_2.10-0.9.0.1）

使用以下命令

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

-Started生產者和消費者-Created話題在兩個不同的CMD終端上使用以下命令：

生產者：

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

消費者：

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

現在，我可以接受，我在消費控制檯生產者終端輸入數據。

現在我試圖將Kafka整合到Apache Spark流中。

下面是我從官方文檔中引用的示例代碼。 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."); 
    } 
}

如果我運行這個程序，以下是日誌。

"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

現在，如果我添加

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

它給出以下以下錯誤，

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

這是顯而易見的。

可以請告訴我如何讓它運行？我的要求是，只要我在生產者終端中輸入任何數據，java應用程序應該承認它並至少打印一次。我將嘗試弄清楚我將收到的json的計算部分。

This是我之前詢問過的問題，並試圖按照建議的架構。

感謝

編輯：

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>

來源

2017-07-02 driftking9987

創建與卡夫卡創建JavaPairDStream直接流之後。現在，您可以遍歷JavaPairDStream並打印卡夫卡消息的鍵和值。

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();

您使用的是帶有kafka-console-producer.bat將產生消息，其中重點將是無效的命令。爲了產生與兩個鍵和值的對以下命令主題test使用消息。在控制檯輸入以逗號分隔鍵和值像key1,value1

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

你的POM文件有不同的版本火花文物。確保對所有工件使用相同的版本。您需要以下依賴項來運行您的程序。

<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>

來源

2017-07-03 05:25:18 abaghel

我做了上面的更改，現在至少不會退出。但我得到'INFO AppInfoParser：卡夫卡版本：0.10.2.1 信息AppInfoParser：卡夫卡的commitid：e89bffd6b2eff799 '我認爲這意味着卡夫卡正在運行，但是當我寫的生產者終端東西，沒有什麼是在程序中發生的事情。 – driftking9987

流的應用程序產生的日誌繼續，你必須滾動查看消息。嘗試在kafka-console-producer中放置更多的消息。我測試了你的代碼，它工作正常。 – abaghel

它必須是我，誰是失去了一些東西，但我所做的一切，如上所述。我在生產者終端中添加了50條新消息，但仍未打印任何內容。 – driftking9987

我認爲日誌說，你所需要的一切:)

拋出：IllegalArgumentException：要求失敗：註冊號輸出操作，所以沒有執行

什麼是輸出操作？例如：

foreachRDD
打印
saveAsHadoopFile
等。更多你可以在這個文件link。

您必須添加一些操作您的應用程序，例如保存stream.mapToPair變量，然後調用foreachRDD該變量或打印（）顯示值

來源

2017-07-02 21:22:44

你能告訴我應該是什麼stream.mapToPair'的'的數據類型，以及如何對此進行輸出操作？ – driftking9987

爲您的代碼添加一個動作可以幫助

stream.print()

有一個嘗試，祝你好運

來源

2017-07-03 06:20:05

對不起，我已經試過了。它不起作用。 – driftking9987

如何整合Spark和Kafka直接流

回答

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