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为什么Spark 1.5.2在独立模式下抛出“本地类不兼容”?

[英]Why does Spark 1.5.2 throw “local class incompatible” in standalone mode?

Got the local class incompatible error today with Spark 1.5.2. 今天在Spark 1.5.2中获得了本地类不兼容错误。

I know, that this type of errors is related with mixing few versions of Spark, but I totally don't know where I can do this... 我知道,这种类型的错误与混合几个版本的Spark有关,但是我完全不知道该在哪里执行此操作...

My application is a simple example, where I handle to mysql database with JDBC. 我的应用程序是一个简单的示例,其中我使用JDBC处理mysql数据库。 There I want to get a DataFrame with some data, that could be received after joining two tables. 我想在其中获得一个包含一些数据的DataFrame,可以在加入两个表之后接收这些数据。

I downloaded Spark's pre-build version for Hadoop 2.6. 我下载了Spark的Hadoop 2.6的预构建版本。

As usual I build the fat jar with Maven and set the path to jar in SparkConf. 像往常一样,我使用Maven构建胖罐,并在SparkConf中设置jar的路径。

After that I start Master node, and then - this command: 之后,我启动主节点,然后-此命令:

./spark-class org.apache.spark.deploy.worker.Worker spark://dima:7077

for launching Worker. 发射工人。

Then I start the application from IDE. 然后,我从IDE启动应用程序。

Here is the code of application: 这是应用程序代码:

public class Main implements Serializable  {

public static void main(String[] args) throws ClassNotFoundException {

    SparkConf conf = new SparkConf()
                            .setAppName("sparkproject")
                            .setMaster("spark://dima:7077")
                            .setJars(new String[] {"target/sparkproject-1.0-SNAPSHOT-jar-with-dependencies.jar"})
                            .set("spark.home","/home/dima/PROGRA~1/spark-1.5.2");
    JavaSparkContext sc = new JavaSparkContext(conf);

    SQLContext sqlContext = new org.apache.spark.sql.SQLContext(sc);

    Map<String, String> options = new HashMap<String, String>();
    options.put("driver", "com.mysql.jdbc.Driver");
    options.put("url", "jdbc:mysql://localhost:3306/db?user=root");
    options.put("dbtable", "db.enreg_karta");

    sqlContext.read().format("jdbc").options(options).load()
                                            .toDF()
                                            .registerTempTable("enreg_karta");

    options.put("dbtable", "db.entem_rubr");

    sqlContext.read().format("jdbc").options(options).load()
                                            .toDF()
                                            .registerTempTable("entem_rubr");

    DataFrame jdbcDF = sqlContext.sql("select rk.enf_namew, rk.enf_referatw from enreg_karta rk join entem_rubr tr on rk.syrecordidw = tr.enrel_inf_tehnw").toDF();
    jdbcDF.show();
}}

Here is the pom.xml 这是pom.xml

<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>dima.study.spark</groupId>
<artifactId>sparkproject</artifactId>
<version>1.0-SNAPSHOT</version>
<packaging>jar</packaging>
<properties>
    <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
    <maven.compiler.source>1.8</maven.compiler.source>
    <maven.compiler.target>1.8</maven.compiler.target>
</properties>
<dependencies>
    <dependency>
        <groupId>org.apache.spark</groupId>
        <artifactId>spark-core_2.10</artifactId>
        <version>1.5.2</version>
    </dependency>
    <dependency>
        <groupId>org.apache.spark</groupId>
        <artifactId>spark-sql_2.10</artifactId>
        <version>1.5.1</version>
    </dependency>
    <dependency>
        <groupId>mysql</groupId>
        <artifactId>mysql-connector-java</artifactId>
        <version>5.1.23</version>
    </dependency>
</dependencies>
<build>
    <plugins>
        <plugin>
            <groupId>org.apache.maven.plugins</groupId>
            <artifactId>maven-assembly-plugin</artifactId>
            <version>2.2</version>
            <configuration>
                <descriptorRefs>
                    <descriptorRef>jar-with-dependencies</descriptorRef>
                </descriptorRefs>
            </configuration>
            <executions>
                <execution>
                    <id>assemble-all</id>
                    <phase>package</phase>
                    <goals>
                        <goal>single</goal>
                    </goals>
                </execution>
            </executions>
        </plugin>
    </plugins>
</build>

My application crashes on the jdbcDF.show(); 我的应用程序在jdbcDF.show()上崩溃了 command. 命令。

Here is the stacktrace: 这是堆栈跟踪:

5/11/29 23:07:23 WARN TaskSetManager: Lost task 0.0 in stage 0.0 (TID 0, 10.205.17.81): java.io.InvalidClassException: org.apache.spark.sql.catalyst.expressions.AttributeReference; local class incompatible: stream classdesc serialVersionUID = 370695178000872136, local class serialVersionUID = -8877631944444173448
at java.io.ObjectStreamClass.initNonProxy(ObjectStreamClass.java:616)
at java.io.ObjectInputStream.readNonProxyDesc(ObjectInputStream.java:1623)
at java.io.ObjectInputStream.readClassDesc(ObjectInputStream.java:1518)
at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1774)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
at java.io.ObjectInputStream.readArray(ObjectInputStream.java:1707)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1345)
at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2000)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1924)
at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2000)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1924)
at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2000)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1924)
at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2000)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1924)
at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2000)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1924)
at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2000)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1924)
at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2000)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1924)
at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
at java.io.ObjectInputStream.readObject(ObjectInputStream.java:371)
at scala.collection.immutable.$colon$colon.readObject(List.scala:362)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:497)
at java.io.ObjectStreamClass.invokeReadObject(ObjectStreamClass.java:1058)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1900)
at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2000)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1924)
at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:2000)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1924)
at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
at java.io.ObjectInputStream.readObject(ObjectInputStream.java:371)
at org.apache.spark.serializer.JavaDeserializationStream.readObject(JavaSerializer.scala:72)
at org.apache.spark.serializer.JavaSerializerInstance.deserialize(JavaSerializer.scala:98)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:64)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
at org.apache.spark.scheduler.Task.run(Task.scala:88)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)

PS I have the only JVM on my laptop. PS我的笔记本电脑上只有JVM。

Somebody knows whats wrong? 有人知道怎么了吗?

Thank You. 谢谢。

Couple of things you can try: - 您可以尝试以下几种方法:-

  1. remove ".setMaster", ".setJars", ".set" from the Spark Conf. 从Spark Conf中删除“ .setMaster”,“。setJars”,“。set”。
  2. Set environment variable SPARK_HOME= 设置环境变量SPARK_HOME =
  3. Ensure you have only 1 JDK/ JVM (preferred is JDK7) installed in your machine. 确保您的计算机上仅安装了1个JDK / JVM(最好是JDK7)。 and using the same JDK compile and create a fat jar file with all your project dependencies (except Spark or scala). 并使用相同的JDK编译并创建一个包含所有项目依赖项(Spark或scala除外)的胖jar文件。
  4. Finally try "spark-submit" to submit your job. 最后尝试“火花提交”来提交您的工作。

That's a much cleaner way. 这是一种更清洁的方法。 try and see if it works. 尝试看看是否可行。

Thanks, Sumit 谢谢Sumit

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