java spark应用程序给出错误：org.apache.spark.sparkexception:无法获取广播\u 1的广播\u 1 \u piece0

我想实现一个sparkjava应用程序，它使用表上的一些过滤器执行select，并将结果与另一个表连接起来。
我使用rdd制作了一个演示应用程序，它可以在本地环境（LocalSpark和cassandra）上完美地工作。
但是，当我将应用程序放在带有远程cassandra数据库的spark群集上时，它给了我以下错误：

Exception in thread "main" org.apache.spark.SparkException: Job aborted due to stage failure: Task 17 in stage 1.0 failed 4 times, most recent failure: Lost task 17.3 in stage 1.0 (TID 64, 53.55.75.24
3, executor 3): java.io.IOException: org.apache.spark.SparkException: Failed to get broadcast_1_piece0 of broadcast_1
        at org.apache.spark.util.Utils$.tryOrIOException(Utils.scala:1333)
        at org.apache.spark.broadcast.TorrentBroadcast.readBroadcastBlock(TorrentBroadcast.scala:207)
        at org.apache.spark.broadcast.TorrentBroadcast._value$lzycompute(TorrentBroadcast.scala:66)
        at org.apache.spark.broadcast.TorrentBroadcast._value(TorrentBroadcast.scala:66)
        at org.apache.spark.broadcast.TorrentBroadcast.getValue(TorrentBroadcast.scala:96)
        at org.apache.spark.broadcast.Broadcast.value(Broadcast.scala:70)
        at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:84)
        at org.apache.spark.scheduler.Task.run(Task.scala:121)
        at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:408)
        at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
        at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:414)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
        at java.lang.Thread.run(Thread.java:748)
Caused by: org.apache.spark.SparkException: Failed to get broadcast_1_piece0 of broadcast_1
        at org.apache.spark.broadcast.TorrentBroadcast$$anonfun$org$apache$spark$broadcast$TorrentBroadcast$$readBlocks$1.apply$mcVI$sp(TorrentBroadcast.scala:179)
        at org.apache.spark.broadcast.TorrentBroadcast$$anonfun$org$apache$spark$broadcast$TorrentBroadcast$$readBlocks$1.apply(TorrentBroadcast.scala:151)
        at org.apache.spark.broadcast.TorrentBroadcast$$anonfun$org$apache$spark$broadcast$TorrentBroadcast$$readBlocks$1.apply(TorrentBroadcast.scala:151)
        at scala.collection.immutable.List.foreach(List.scala:392)
        at org.apache.spark.broadcast.TorrentBroadcast$$anonfun$readBroadcastBlock$1$$anonfun$apply$2.apply(TorrentBroadcast.scala:231)51)
        at org.apache.spark.broadcast.TorrentBroadcast$$anonfun$readBroadcastBlock$1.apply(TorrentBroadcast.scala:211)
        ... 13 morehe.spark.util.Utils$.tryOrIOException(Utils.scala:1326)
        at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1889)
Driver sat org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1877)
        at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)er.scala:1876)
        at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1876)
        at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:926)
        at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:926)
        at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2059)0)
        at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)ve(DAGScheduler.scala:2048)
        at org.apache.spark.SparkContext.runJob(SparkContext.scala:2061)cala:737)
        at org.apache.spark.SparkContext.runJob(SparkContext.scala:2101)
        at org.apache.spark.rdd.RDD.count(RDD.scala:1168)ext.scala:2126)
        at org.apache.spark.api.java.AbstractJavaRDDLike.count(JavaRDDLike.scala:45)
        at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
        at java.lang.reflect.Method.invoke(Method.java:498)DelegatingMethodAccessorImpl.java:43)
        at org.apache.spark.deploy.SparkSubmit.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:849)
        at org.apache.spark.deploy.SparkSubmit.doRunMain$1(SparkSubmit.scala:167)
        at org.apache.spark.deploy.SparkSubmit.doSubmit(SparkSubmit.scala:86)
        at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:933).scala:924)
        at org.apache.spark.util.Utils$.tryOrIOException(Utils.scala:1333)
Caused bat org.apache.spark.broadcast.TorrentBroadcast.readBroadcastBlock(TorrentBroadcast.scala:207)broadcast_1
        at org.apache.spark.broadcast.TorrentBroadcast._value(TorrentBroadcast.scala:66)t.scala:66)
        at org.apache.spark.broadcast.Broadcast.value(Broadcast.scala:70)oadcast.scala:96)
        at org.apache.spark.scheduler.Task.run(Task.scala:121)tTask.scala:84)
        at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)xecutor.scala:408)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
        at java.lang.Thread.run(Thread.java:748)or$Worker.run(ThreadPoolExecutor.java:624)

我将在这里附上代码和配置类：
pom.xml文件

<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>
    <version>0.0.2</version>

    <properties>
        <java.version>1.8</java.version>
        <maven.compiler.source>1.8</maven.compiler.source>
        <maven.compiler.target>1.8</maven.compiler.target>
        <spark-core.version>2.4.3</spark-core.version>
        <spark-sql.version>2.4.3</spark-sql.version>
        <spark-cassandra-connector.version>2.4.1</spark-cassandra-connector.version>
    </properties>
    <dependencies>
        <dependency>
            <groupId>junit</groupId>
            <artifactId>junit</artifactId>
            <version>4.11</version>
            <scope>test</scope>
        </dependency>
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-sql_2.11</artifactId>
            <version>${spark-sql.version}</version>
        </dependency>
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-core_2.11</artifactId>
            <version>${spark-core.version}</version>
        </dependency>
        <dependency>
            <groupId>com.datastax.spark</groupId>
            <artifactId>spark-cassandra-connector_2.11</artifactId>
            <version>2.4.1</version>
        </dependency>
    </dependencies>
        <build>
        <plugins>
            <plugin>
                <version>3.5.1</version>
                <artifactId>maven-compiler-plugin</artifactId>
                <configuration>
                    <source>1.8</source>
                    <target>1.8</target>
                </configuration>
            </plugin>

       </build>
</project>

dto的：

public class AirportCityDTO implements Serializable {

    private static final long serialVersionUID = 1L;

    private int id;
    private String name;
    private String city;

    public AirportCityDTO() {
        super();
    }

    public AirportCityDTO(int id, String name, String city) {
        super();
        this.id = id;
        this.name = name;
        this.city = city;
    }

}

public class AirportCityStateDTO implements Serializable {

    private static final long serialVersionUID = 1L;

    private String city;
    private String state;

    public AirportCityStateDTO() {
        super();
    }

    public AirportCityStateDTO(String city, String state) {
        super();
        this.city = city;
        this.state = state;
    }
}

public class AirportCityStateJoinDTO implements Serializable {

    private static final long serialVersionUID = 1L;

    private String name;
    private String city;
    private String state;

    public AirportCityStateJoinDTO() {
        super();
    }

    public AirportCityStateJoinDTO(String name, String city, String state) {
        super();
        this.name = name;
        this.city = city;
        this.state = state;
    }
}

public class SparkConfiguration implements Serializable {

    private static final long serialVersionUID = 1L;
    private static final Logger LOG = LoggerFactory.getLogger(SparkConfiguration.class);

    public SparkConfiguration() {
        super();
    }

    public SparkSession initializeSparkSession() {
        ClassLoader classLoader = this.getClass().getClassLoader();

        try (InputStream input = classLoader.getResourceAsStream("config.properties")) {
            Properties applicationPoperties = new Properties();
            applicationPoperties.load(input);
            String profile = applicationPoperties.getProperty("application.profile");
            try (InputStream profileInput = classLoader.getResourceAsStream(profile.concat("-config.properties"))) {
                Properties properties = new Properties();
                properties.load(profileInput);

                return SparkSession.builder().appName("AppName").master(properties.getProperty("spark.master.url"))
                        .config("spark.cassandra.connection.ssl.enabled",
                                "dev".equals(profile.trim()) ? "true" : "false")
                        .config("spark.cassandra.auth.username", properties.getProperty("cassandra.configuration.user"))
                        .config("spark.cassandra.auth.password",
                                properties.getProperty("cassandra.configuration.password"))
                        .config("spark.cassandra.connection.host",
                                properties.getProperty("cassandra.configuration.contactPoint"))
                        .config("spark.cassandra.connection.port",
                                properties.getProperty("cassandra.configuration.port"))
                        .getOrCreate();

            } catch (IOException e) {
                LOG.error(e.getLocalizedMessage());
            }
        } catch (IOException e) {
            LOG.error(e.getLocalizedMessage());
        }

        return null;

    }

public class Main extends SparkConfiguration {

    private static final long serialVersionUID = 1L;
    private static final Logger LOG = LoggerFactory.getLogger(Main .class);

    public Main () {
        super();
    }

    public static void main(String[] args) {
        Main mainClass = new Main ();
        final SparkSession sparkSession = mainClass.initializeSparkSession();
        AirportCityStatesRepository allocationRepo = new AirportCityStatesRepository ();
        if (sparkSession != null) {
            allocationRepo.performJoin(sparkSession);
        } else {
            LOG.warn("Spark Session couldn't be initialized! Exiting program...");
            return;
        }
    }
}

public class AirportCityStatesRepository implements Serializable {

    private static final long serialVersionUID = 1L;
        private static final String CASSANDRA_KEYSPACE = ApplicationProperties.getInstance().getKeyspace();

    public AirportCityStatesRepository() {
        super();
    }

    public void performJoin() {

        JavaPairRDD<String, AirportCityDTO> airportCityPairRows = javaFunctions(sparkContext)
                .cassandraTable(CASSANDRA_KEYSPACE, "airport_city", mapRowTo(AirportCityDTO.class)).keyBy(

                        new Function<AirportCityDTO, String>() {
                            private static final long serialVersionUID = 1L;

                            @Override
                            public String call(AirportCityDTO v1) throws Exception {
                                return v1.getCity();
                            }
                        });

        JavaPairRDD<String, AirportCityStateDTO> airportCityStatePairRows = javaFunctions(sparkContext)
                .cassandraTable(CASSANDRA_KEYSPACE, "airport_city_state", mapRowTo(AirportCityStateDTO.class))
                .keyBy(new Function<AirportCityStateDTO, String>() {
                    private static final long serialVersionUID = 1L;

                    @Override
                    public String call(AirportCityStateDTO v1) throws Exception {
                        return v1.getCity();
                    }
                });

        JavaPairRDD<String, Tuple2<AirportCityDTO, AirportCityStateDTO>> joinRows = airportCityPairRows
                .join(airportCityStatePairRows);

        JavaRDD<AirportCityStateJoinDTO> finalResult = joinRows.map(
                new Function<Tuple2<String, Tuple2<AirportCityDTO, AirportCityStateDTO>>, AirportCityStateJoinDTO>() {
                    private static final long serialVersionUID = 1L;

                    @Override
                    public AirportCityStateJoinDTO call(Tuple2<String, Tuple2<AirportCityDTO, AirportCityStateDTO>> v1)
                            throws Exception {
                        AirportCityStateJoinDTO obj = new AirportCityStateJoinDTO();
                        obj.setCity(v1._1());
                        obj.setName(v1._2()._1().getName());
                        obj.setState(v1._2()._2().getState());
                        return obj;
                    }

                });

        List<AirportCityStateJoinDTO> list = finalResult.collect();
        for (AirportCityStateJoinDTO l : list) {
            System.err.println(l.getName() + " | " + l.getCity() + " | " + l.getState());
        }

    }

}

配置属性


# local, dev

application.profile=dev

local-config.properties属性


# Cassandra connection properties

cassandra.configuration.contactPoint: 53.118.16.40
cassandra.configuration.keyspace: test
cassandra.configuration.port: 9042
cassandra.consistency.level = ONE
cassandra.configuration.user = 
cassandra.configuration.password = 

spark.app.name=App Name
spark.master.url=local[2]
spark.master.port=7077

dev-config.properties文件

cassandra.configuration.contactPoint: 53.55.79.246
cassandra.configuration.keyspace: test
cassandra.configuration.port: 9042
cassandra.consistency.level = QUORUM
spark.app.name= App Name
spark.master.url= spark://53.55.75.246:7077
spark.master.port = 7077

我设法找到了问题所在。当我在javardd中从cassandra检索数据时，一切都正常。
问题是当我对包含来自cassandra的数据的javardd应用转换操作时。在我的例子中，我应用了keyby（）。
在没有keyby（）的情况下，在rdd上调用collect（）或count（）方法之后，它在带有远程cassandra数据库的spark集群上也可以正常工作。
我真的很感激你的帮助。。我试了所有我能找到的办法，但没有一个奏效。
我还在集群的spark主机上安装了一个本地cassandra数据库，试图复制我在开发pc上的本地环境，但它给了我相同的错误。我猜这是spark配置错误。。
运行应用程序的命令：

/spark-2.4.3-bin-hadoop2.7/bin/spark-submit \
 --class com.spark.example.Main \
 --master spark://53.55.75.246:7077  \
 --executor-memory 1G \
 --executor-cores 5 \
 --conf spark.executor.userClassPathFirst=true \
 --conf spark.driver.userClasspathFirst=true \
 --verbose \
 spark-example.jar

java spark应用程序给出错误：org.apache.spark.sparkexception:无法获取广播\u 1的广播\u 1 \u piece0

暂无答案！

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