{"action":"created","issue":{"url":"https://api.github.com/repos/dmlc/xgboost/issues/3824","repository_url":"https://api.github.com/repos/dmlc/xgboost","labels_url":"https://api.github.com/repos/dmlc/xgboost/issues/3824/labels{/name}","comments_url":"https://api.github.com/repos/dmlc/xgboost/issues/3824/comments","events_url":"https://api.github.com/repos/dmlc/xgboost/issues/3824/events","html_url":"https://github.com/dmlc/xgboost/issues/3824","id":373387172,"node_id":"MDU6SXNzdWUzNzMzODcxNzI=","number":3824,"title":"[jvm-packages] Some errors in model training","user":{"login":"haitongwan","id":30080404,"node_id":"MDQ6VXNlcjMwMDgwNDA0","avatar_url":"https://avatars3.githubusercontent.com/u/30080404?v=4","gravatar_id":"","url":"https://api.github.com/users/haitongwan","html_url":"https://github.com/haitongwan","followers_url":"https://api.github.com/users/haitongwan/followers","following_url":"https://api.github.com/users/haitongwan/following{/other_user}","gists_url":"https://api.github.com/users/haitongwan/gists{/gist_id}","starred_url":"https://api.github.com/users/haitongwan/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/haitongwan/subscriptions","organizations_url":"https://api.github.com/users/haitongwan/orgs","repos_url":"https://api.github.com/users/haitongwan/repos","events_url":"https://api.github.com/users/haitongwan/events{/privacy}","received_events_url":"https://api.github.com/users/haitongwan/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":2,"created_at":"2018-10-24T09:25:15Z","updated_at":"2018-10-25T01:05:43Z","closed_at":null,"author_association":"NONE","body":"When I train the model, there's some errors.\r\nError Meassages:\r\n\r\nERROR ApplicationMaster: User class threw exception: ml.dmlc.xgboost4j.java.XGBoostError: XGBoostModel training failed\r\nml.dmlc.xgboost4j.java.XGBoostError: XGBoostModel training failed\r\n\tat ml.dmlc.xgboost4j.scala.spark.XGBoost$.ml$dmlc$xgboost4j$scala$spark$XGBoost$$postTrackerReturnProcessing(XGBoost.scala:283)\r\n\tat ml.dmlc.xgboost4j.scala.spark.XGBoost$$anonfun$trainDistributed$4.apply(XGBoost.scala:240)\r\n\tat ml.dmlc.xgboost4j.scala.spark.XGBoost$$anonfun$trainDistributed$4.apply(XGBoost.scala:222)\r\n\tat scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)\r\n\tat scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)\r\n\tat scala.collection.immutable.List.foreach(List.scala:381)\r\n\tat scala.collection.TraversableLike$class.map(TraversableLike.scala:234)\r\n\tat scala.collection.immutable.List.map(List.scala:285)\r\n\tat ml.dmlc.xgboost4j.scala.spark.XGBoost$.trainDistributed(XGBoost.scala:221)\r\n\tat ml.dmlc.xgboost4j.scala.spark.XGBoostClassifier.train(XGBoostClassifier.scala:191)\r\n\tat ml.dmlc.xgboost4j.scala.spark.XGBoostClassifier.train(XGBoostClassifier.scala:48)\r\n\tat org.apache.spark.ml.Predictor.fit(Predictor.scala:118)\r\n\tat com.qunar.train.xgboostdemo$.main(xgboostdemo.scala:53)\r\n\tat com.qunar.train.xgboostdemo.main(xgboostdemo.scala)\r\n\tat sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)\r\n\tat sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)\r\n\tat sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)\r\n\tat java.lang.reflect.Method.invoke(Method.java:498)\r\n\tat org.apache.spark.deploy.yarn.ApplicationMaster$$anon$4.run(ApplicationMaster.scala:721)\r\n\r\nI am looking forward to your reply."},"comment":{"url":"https://api.github.com/repos/dmlc/xgboost/issues/comments/432878197","html_url":"https://github.com/dmlc/xgboost/issues/3824#issuecomment-432878197","issue_url":"https://api.github.com/repos/dmlc/xgboost/issues/3824","id":432878197,"node_id":"MDEyOklzc3VlQ29tbWVudDQzMjg3ODE5Nw==","user":{"login":"hcho3","id":2532981,"node_id":"MDQ6VXNlcjI1MzI5ODE=","avatar_url":"https://avatars0.githubusercontent.com/u/2532981?v=4","gravatar_id":"","url":"https://api.github.com/users/hcho3","html_url":"https://github.com/hcho3","followers_url":"https://api.github.com/users/hcho3/followers","following_url":"https://api.github.com/users/hcho3/following{/other_user}","gists_url":"https://api.github.com/users/hcho3/gists{/gist_id}","starred_url":"https://api.github.com/users/hcho3/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/hcho3/subscriptions","organizations_url":"https://api.github.com/users/hcho3/orgs","repos_url":"https://api.github.com/users/hcho3/repos","events_url":"https://api.github.com/users/hcho3/events{/privacy}","received_events_url":"https://api.github.com/users/hcho3/received_events","type":"User","site_admin":false},"created_at":"2018-10-25T01:05:43Z","updated_at":"2018-10-25T01:05:43Z","author_association":"COLLABORATOR","body":"@CodingCat @yanboliang Is there a way to obtain a more informative error message other than \"XGBoostModel training failed\"?"}}
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