{"action":"created","issue":{"url":"https://api.github.com/repos/dmlc/xgboost/issues/3649","repository_url":"https://api.github.com/repos/dmlc/xgboost","labels_url":"https://api.github.com/repos/dmlc/xgboost/issues/3649/labels{/name}","comments_url":"https://api.github.com/repos/dmlc/xgboost/issues/3649/comments","events_url":"https://api.github.com/repos/dmlc/xgboost/issues/3649/events","html_url":"https://github.com/dmlc/xgboost/issues/3649","id":355044111,"node_id":"MDU6SXNzdWUzNTUwNDQxMTE=","number":3649,"title":"`Segmentation Fault / Killed` when run on Python inside Docker Container (Alpine)","user":{"login":"aekazitt","id":3035165,"node_id":"MDQ6VXNlcjMwMzUxNjU=","avatar_url":"https://avatars2.githubusercontent.com/u/3035165?v=4","gravatar_id":"","url":"https://api.github.com/users/aekazitt","html_url":"https://github.com/aekazitt","followers_url":"https://api.github.com/users/aekazitt/followers","following_url":"https://api.github.com/users/aekazitt/following{/other_user}","gists_url":"https://api.github.com/users/aekazitt/gists{/gist_id}","starred_url":"https://api.github.com/users/aekazitt/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/aekazitt/subscriptions","organizations_url":"https://api.github.com/users/aekazitt/orgs","repos_url":"https://api.github.com/users/aekazitt/repos","events_url":"https://api.github.com/users/aekazitt/events{/privacy}","received_events_url":"https://api.github.com/users/aekazitt/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":22,"created_at":"2018-08-29T08:04:58Z","updated_at":"2018-11-23T09:58:23Z","closed_at":null,"author_association":"NONE","body":"Within a docker container (based on alpine linux) with Python 2.7 installed, I receive a `Segmentation Fault` error that kills the entire process and then the container exits.\r\n\r\nThis DOES NOT happen during fitting but only happens when I use the loaded model to predict. My current script uses XGBoost alongside SKLearn's GridSearchCV. The `gsv.fit` method runs perfectly fine and then I save the `gsv.best_estimator_` as a pickle to be later used. When I load the model from pickle and calls method `predict`, the container hangs for a while and exits with `Segmentation Fault` error message. (or sometimes the python script is Killed by the container.)\r\n\r\n**Build Specifications**\r\nCurrently using Xgboost with Sklearn's GridSearchCV inside a Docker Container based on Alpine linux.\r\nThe build specifications closely resembles this base image\r\nhttps://github.com/Nexosis/alpine-xgboost/blob/master/Dockerfile\r\n\r\nWhen I run `pip list` here is the result for xgboost\r\n```\r\nxgboost                       0.80 \r\n```\r\n\r\nHere is a full list of other python libraries just in case\r\n```\r\nPackage                       Version\r\n----------------------------- -------\r\narrow                         0.12.1 \r\nbackports.functools-lru-cache 1.5    \r\nnumpy                         1.14.5 \r\npandas                        0.23.4 \r\npip                           18.0   \r\nPyMySQL                       0.8.0  \r\npython-dateutil               2.7.3  \r\npytz                          2018.5 \r\nscikit-learn                  0.19.2 \r\nscipy                         1.1.0  \r\nsetuptools                    39.0.1 \r\nsix                           1.11.0 \r\nSQLAlchemy                    1.2.11 \r\nthrift                        0.11.0 \r\nwheel                         0.31.0 \r\nxgboost                       0.80\r\n```\r\n\r\n**Steps to Reproduce**\r\n1. Create Training Model with GridSearchCV\r\n2. Save Training Model into a pickle file\r\n...\r\n3. Load model from pickle file\r\n4. Use `model.predict(dataframe)`\r\n\r\n**What happens next**\r\nEither the container Kills this python process OR I get an error that says `Segmentation fault` and the container dies."},"comment":{"url":"https://api.github.com/repos/dmlc/xgboost/issues/comments/441197677","html_url":"https://github.com/dmlc/xgboost/issues/3649#issuecomment-441197677","issue_url":"https://api.github.com/repos/dmlc/xgboost/issues/3649","id":441197677,"node_id":"MDEyOklzc3VlQ29tbWVudDQ0MTE5NzY3Nw==","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":"2018-11-23T09:58:23Z","updated_at":"2018-11-23T09:58:23Z","author_association":"COLLABORATOR","body":"@eblancost Yeah the use of backtrace needs to be disabled in CMake when MUSL is used. Let me submit a pull request soon."}}
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