Hadoop MapReduce作业出现OptionConverter.convertLevel间歇性错误求助
错误详情
执行MapReduce作业时出现间歇性错误,报错信息:
2022-12-28 01:20:53,882 ERROR [main] org.apache.hadoop.mapred.YarnChild: Error running child : java.lang.NoSuchMethodError: org/apache/log4j/helpers/OptionConverter.convertLevel(Ljava/lang/String;Lorg/apache/logging/log4j/Level;)Lorg/apache/logging/log4j/Level; (loaded from file:/opt/hadoop-3.3.0/share/hadoop/common/lib/log4j-1.2.17.jar by sun.misc.Launcher$AppClassLoader@350ed555) called from class org.apache.log4j.config.PropertiesConfiguration (loaded from file:/data/hadoop/yarn/usercache/hdfs-user/appcache/application_1671477750397_6197/filecache/10/job.jar/job.jar by sun.misc.Launcher$AppClassLoader@350ed555).
错误随机出现:有时导致Mapper失败,有时作业能正常完成。项目Gradle配置如下:
plugins { id 'java' id "com.github.davidmc24.gradle.plugin.avro" version "1.3.0" } dependencies { compileOnly group: 'org.apache.hadoop', name: 'hadoop-client', version: '3.3.0' implementation group: 'org.apache.avro', name: 'avro', version: '1.8.1' implementation group: 'org.apache.avro', name: 'avro-mapred', version: '1.10.2' implementation group: 'io.netty', name: 'netty-buffer', version: '4.1.51.Final' implementation group: 'joda-time', name: 'joda-time', version:'2.8.1' implementation group: 'org.javatuples', name: 'javatuples', version: '1.2' implementation group: 'com.fasterxml.jackson.dataformat', name: 'jackson-dataformat-yaml', version: '2.12.4' testImplementation group: 'junit', name: 'junit', version: "$junit4Version" implementation project(':libraries:java-dcl') implementation project(':libraries:sdp') testImplementation group: 'org.assertj', name: 'assertj-core', version: '3.6.1' } generateAvroJava { source("${projectDir}/src/main/avro")//sourcepath avrofile } // The alternative to below is to put all java that is dependent on scala (or on the java dependent on the scala) in the src/main/scala dir // https://stackoverflow.com/questions/23261075/compiling-scala-before-alongside-java-with-gradle sourceSets { main { java { srcDirs = ['src/main/java'] } } }
问题根源
这是典型的log4j版本冲突:
- Hadoop 3.3.0内置log4j 1.2.17,该版本的
OptionConverter类没有convertLevel(String, org.apache.logging.log4j.Level)方法。 - 作业jar中包含了高版本log4j相关组件(大概率来自avro-mapred依赖),其中
PropertiesConfiguration类调用了这个不存在的方法。 - 类加载顺序的随机性导致间歇性报错:当集群先加载Hadoop的旧log4j时触发错误;若先加载作业jar中的组件,且未执行到该方法调用,作业就能正常运行。
解决办法
1. 排除依赖中的冲突log4j包
修改Gradle依赖,排除avro等依赖引入的log4j相关组件,确保作业使用集群自带的版本:
dependencies { // 保留原有依赖,对avro-mapred添加排除规则 implementation('org.apache.avro:avro-mapred:1.10.2') { exclude group: 'org.apache.logging.log4j' exclude group: 'log4j' } // 其他可能引入log4j的依赖也做同样处理 }
2. 强制统一log4j版本
在Gradle中强制指定与Hadoop兼容的log4j版本,覆盖所有依赖的版本:
configurations.all { resolutionStrategy { force 'log4j:log4j:1.2.17' // 若需log4j2 API,指定Hadoop兼容的版本 force 'org.apache.logging.log4j:log4j-api:2.17.1' } }
3. 调整打包策略
确保作业jar中不包含log4j相关文件:
- 执行
gradle dependencies查看依赖树,确认无多余log4j包被引入。 - 若使用打包插件(如shadowJar),添加规则排除log4j的jar和类文件。
4. 使用桥接包(可选)
如果代码需要log4j 2.x特性,引入log4j 1.x到2.x的桥接包,并设置为compileOnly避免打包到作业jar:
dependencies { compileOnly 'org.apache.logging.log4j:log4j-1.2-api:2.17.1' }
内容的提问来源于stack exchange,提问作者Sitakant Mishra

