Spark运行时错误：spark.metrics.sink.MetricsServlet无法实例化 [英] Spark runtime error: spark.metrics.sink.MetricsServlet cannot be instantialized
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问题描述
在IntelliJ中使用maven中的spark 1.3 lib运行项目时，我遇到了调用目标异常。
I got invocation target exception when running project with spark 1.3 lib in maven in IntelliJ.
我只在IntelliJ IDE中遇到此错误。在我部署jar并通过spark-submit运行后，错误消失了。
I got met this error only in IntelliJ IDE. After I deployed the jar and ran via spark-submit, the error went out.
之前有人遇到过同样的问题吗？我希望解决这个问题，以便进行简单的调试。否则每次我想运行代码时都要打包jar。
Any one has met with the same problem before? I hope to fix this problem so as to do easy-debugging. otherwise I have to package the jar every time when I want to run the code.
详情如下：
2015-04-21 09:39:13 ERROR MetricsSystem:75 - Sink class org.apache.spark.metrics.sink.MetricsServlet cannot be instantialized
2015-04-21 09:39:13 ERROR TrainingSFERunner:144 - java.lang.reflect.InvocationTargetException
2015-04-20 16:08:44 INFO BlockManagerMaster:59 - Registered BlockManager
Exception in thread "main" java.lang.reflect.InvocationTargetException
at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:57)
at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
at java.lang.reflect.Constructor.newInstance(Constructor.java:526)
at org.apache.spark.metrics.MetricsSystem$$anonfun$registerSinks$1.apply(MetricsSystem.scala:187)
at org.apache.spark.metrics.MetricsSystem$$anonfun$registerSinks$1.apply(MetricsSystem.scala:181)
at scala.collection.mutable.HashMap$$anonfun$foreach$1.apply(HashMap.scala:98)
at scala.collection.mutable.HashMap$$anonfun$foreach$1.apply(HashMap.scala:98)
at scala.collection.mutable.HashTable$class.foreachEntry(HashTable.scala:226)
at scala.collection.mutable.HashMap.foreachEntry(HashMap.scala:39)
at scala.collection.mutable.HashMap.foreach(HashMap.scala:98)
at org.apache.spark.metrics.MetricsSystem.registerSinks(MetricsSystem.scala:181)
at org.apache.spark.metrics.MetricsSystem.start(MetricsSystem.scala:98)
at org.apache.spark.SparkContext.<init>(SparkContext.scala:390)
at org.apache.spark.api.java.JavaSparkContext.<init>(JavaSparkContext.scala:61)
at spark.mllibClassifier.JavaRandomForests.run(JavaRandomForests.java:105)
at spark.mllibClassifier.SparkMLlibMain.runMain(SparkMLlibMain.java:263)
at spark.mllibClassifier.JavaRandomForests.main(JavaRandomForests.java:221)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:606)
at com.intellij.rt.execution.application.AppMain.main(AppMain.java:134)
Caused by: java.lang.NoSuchMethodError: com.fasterxml.jackson.databind.module.SimpleSerializers.<init>(Ljava/util/List;)V
at com.codahale.metrics.json.MetricsModule.setupModule(MetricsModule.java:223)
at com.fasterxml.jackson.databind.ObjectMapper.registerModule(ObjectMapper.java:469)
at org.apache.spark.metrics.sink.MetricsServlet.<init>(MetricsServlet.scala:45)
我的pom文件如下。
My pom file is as follows.
<?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>projects</groupId>
<artifactId>project1</artifactId>
<version>1.0-SNAPSHOT</version>
<dependencies>
<dependency>
<groupId>org.apache.commons</groupId>
<artifactId>commons-lang3</artifactId>
<version>3.0</version>
</dependency>
<dependency>
<groupId>org.apache.lucene</groupId>
<artifactId>lucene-core</artifactId>
<version>5.0.0</version>
</dependency>
<dependency>
<groupId>org.apache.lucene</groupId>
<artifactId>lucene-analyzers-common</artifactId>
<version>5.0.0</version>
</dependency>
<dependency>
<groupId>log4j</groupId>
<artifactId>log4j</artifactId>
<version>1.2.17</version>
</dependency>
<dependency>
<groupId>junit</groupId>
<artifactId>junit</artifactId>
<version>3.8.1</version>
<scope>test</scope>
</dependency>
<dependency>
<groupId>commons-io</groupId>
<artifactId>commons-io</artifactId>
<version>2.1</version>
<scope>test</scope>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-core_2.10</artifactId>
<version>1.3.0</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-mllib_2.10</artifactId>
<version>1.3.0</version>
</dependency>
<dependency>
<groupId>colt</groupId>
<artifactId>colt</artifactId>
<version>1.2.0</version>
</dependency>
</dependencies>
<build>
<plugins>
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-compiler-plugin</artifactId>
<version>3.2</version>
<configuration>
<source>1.7</source>
<target>1.7</target>
</configuration>
</plugin>
<plugin>
<artifactId>maven-assembly-plugin</artifactId>
<executions>
<execution>
<phase>package</phase>
<goals>
<goal>single</goal>
</goals>
</execution>
</executions>
<configuration>
<descriptorRefs>
<descriptorRef>jar-with-dependencies</descriptorRef>
</descriptorRefs>
</configuration>
</plugin>
</plugins>
</build>
</project>
推荐答案
奇怪的是，我发现错误没有出来当我将火花相关的依赖项移到前面时。
Strangely, I found the error didn't come out any more when I move the spark related dependencies to the front.
<dependencies>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-core_2.10</artifactId>
<version>1.3.0</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-mllib_2.10</artifactId>
<version>1.3.0</version>
</dependency>
//....the rest dependencies....
</dependencies>
所以依赖关系的顺序很重要！任何人都知道为什么？
So the sequence of the dependencies matters! Any one knows why?
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