xiaohei88 opened a new issue, #11449: URL: https://github.com/apache/dolphinscheduler/issues/11449
### Search before asking - [X] I had searched in the [issues](https://github.com/apache/dolphinscheduler/issues?q=is%3Aissue) and found no similar issues. ### What happened 跑数据质量流程后，任务快结束的时候报错 ```java 22/08/12 05:59:06 ERROR Client: Application diagnostics message: User class threw exception: java.lang.IllegalArgumentException: java.net.UnknownHostException: mycluster at org.apache.hadoop.security.SecurityUtil.buildTokenService(SecurityUtil.java:447) at org.apache.hadoop.hdfs.NameNodeProxiesClient.createProxyWithClientProtocol(NameNodeProxiesClient.java:139) at org.apache.hadoop.hdfs.DFSClient.<init>(DFSClient.java:356) at org.apache.hadoop.hdfs.DFSClient.<init>(DFSClient.java:290) at org.apache.hadoop.hdfs.DistributedFileSystem.initialize(DistributedFileSystem.java:171) at org.apache.hadoop.fs.FileSystem.createFileSystem(FileSystem.java:3364) at org.apache.hadoop.fs.FileSystem.access$200(FileSystem.java:123) at org.apache.hadoop.fs.FileSystem$Cache.getInternal(FileSystem.java:3413) at org.apache.hadoop.fs.FileSystem$Cache.get(FileSystem.java:3381) at org.apache.hadoop.fs.FileSystem.get(FileSystem.java:486) at org.apache.hadoop.fs.Path.getFileSystem(Path.java:365) at org.apache.spark.sql.execution.datasources.DataSource.planForWritingFileFormat(DataSource.scala:470) at org.apache.spark.sql.execution.datasources.DataSource.planForWriting(DataSource.scala:572) at org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:438) at org.apache.spark.sql.DataFrameWriter.saveInternal(DataFrameWriter.scala:415) at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:293) at org.apache.spark.sql.DataFrameWriter.csv(DataFrameWriter.scala:979) at org.apache.dolphinscheduler.data.quality.flow.batch.writer.file.BaseFileWriter.outputImpl(BaseFileWriter.java:113) at org.apache.dolphinscheduler.data.quality.flow.batch.writer.file.HdfsFileWriter.write(HdfsFileWriter.java:40) at org.apache.dolphinscheduler.data.quality.execution.SparkBatchExecution.executeWriter(SparkBatchExecution.java:130) at org.apache.dolphinscheduler.data.quality.execution.SparkBatchExecution.execute(SparkBatchExecution.java:58) at org.apache.dolphinscheduler.data.quality.context.DataQualityContext.execute(DataQualityContext.java:62) at org.apache.dolphinscheduler.data.quality.DataQualityApplication.main(DataQualityApplication.java:70) 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:498) at org.apache.spark.deploy.yarn.ApplicationMaster$$anon$2.run(ApplicationMaster.scala:735) Caused by: java.net.UnknownHostException: mycluster ... 28 more ``` ### What you expected to happen [INFO] 2022-08-12 05:58:36.927 +0000 [taskAppId=TASK-20220812-6487978935456_7-26-30] TaskLogLogger-class org.apache.dolphinscheduler.plugin.task.dq.DataQualityTask:[181] - data quality task command: .... 'hdfs://mycluster:8020/user/hadoop/data_quality_error_data/0_26_onlyone' .... 这个地址是不对的。我猜测任务会写的时候报错了。 看源码，我以为：org.apache.dolphinscheduler.common.utils.PropertyUtils加载有问题。 ```java try (InputStream fis = PropertyUtils.class.getResourceAsStream("/common.properties");) { properties.load(fis); } catch (IOException e) { logger.error(e.getMessage(), e); System.exit(1); } ``` work节点下的common properties我是改过hdfs地址 ### How to reproduce 新建一个数据质量流程。 ### Anything else _No response_ ### Version 3.0.0 ### Are you willing to submit PR? - [X] Yes I am willing to submit a PR! ### Code of Conduct - [X] I agree to follow this project's [Code of Conduct](https://www.apache.org/foundation/policies/conduct) -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
