来自：http://*.com/questions/26892389/org-apache-spark-sparkexception-job-aborted-due-to-stage-failure-task-from-app

1. Create a Fat Jar ( One which includes all dependencies ). Use Shade Plugin for this. Example pom :

<plugin>

    <groupId>org.apache.maven.plugins</groupId>

    <artifactId>maven-shade-plugin</artifactId>

    <version>2.2</version>

    <configuration>

        <filters>

            <filter>

                <artifact>*:*</artifact>

                <excludes>

                    <exclude>META-INF/*.SF</exclude>

                    <exclude>META-INF/*.DSA</exclude>

                    <exclude>META-INF/*.RSA</exclude>

                </excludes>

            </filter>

        </filters>

    </configuration>

    <executions>

        <execution>

            <id>job-driver-jar</id>

            <phase>package</phase>

            <goals>

                <goal>shade</goal>

            </goals>

            <configuration>

                <shadedArtifactAttached>true</shadedArtifactAttached>

                <shadedClassifierName>driver</shadedClassifierName>

                <transformers>

                    <transformer implementation="org.apache.maven.plugins.shade.resource.ServicesResourceTransformer"/>

                    <!--

                    Some care is required:

                    http://doc.akka.io/docs/akka/snapshot/general/configuration.html

                    -->

                    <transformer implementation="org.apache.maven.plugins.shade.resource.AppendingTransformer">

                        <resource>reference.conf</resource>

                    </transformer>

                    <transformer implementation="org.apache.maven.plugins.shade.resource.ManifestResourceTransformer">

                        <mainClass>mainClass</mainClass>

                    </transformer>

                </transformers>

            </configuration>

        </execution>

        <execution>

            <id>worker-library-jar</id>

            <phase>package</phase>

            <goals>

                <goal>shade</goal>

            </goals>

            <configuration>

                <shadedArtifactAttached>true</shadedArtifactAttached>

                <shadedClassifierName>worker</shadedClassifierName>

                <transformers>

                    <transformer implementation="org.apache.maven.plugins.shade.resource.ServicesResourceTransformer"/>

                </transformers>

            </configuration>

        </execution>

    </executions>

</plugin>

1. Now we have to send the compiled jar file to the cluster. For this, specify the jar file in the spark config like this :

SparkConf conf = new SparkConf().setAppName("appName").setMaster("spark://machineName:7077").setJars(new String[] {"target/appName-1.0-SNAPSHOT-driver.jar"});

1. Run mvn clean package to create the Jar file. It will be created in your target folder.

2. Run using your IDE or using maven command :

mvn exec:java -Dexec.mainClass="className"

This does not require spark-submit. Just remember to package file before running

If you don't want to hardcode the jar path, you can do this :

1. In the config, write :

SparkConf conf = new SparkConf() .setAppName("appName") .setMaster("spark://machineName:7077") .setJars(JavaSparkContext.jarOfClass(this.getClass()));

1. Create the fat jar ( as above ) and run using maven after running package command :

java -jar target/application-1.0-SNAPSHOT-driver.jar

This will take the jar from the jar the class was loaded.