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RabitTracker:179 - FAULT: failed to start tracker process #8191
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Could you please share the specification of the environment where we can try to reproduce it? |
hi i am running it on docker with following versions |
code works fine on local environment |
hii kindly help me on this issue
i am completely stuck
i am using a docker image
with python version 3.7.11
spark 3.1
…On Mon, Aug 22, 2022 at 8:35 PM Jiaming Yuan ***@***.***> wrote:
Could you please share the specification of the environment where we can
try to reproduce it?
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Hi, we need more information on how to reproduce it. We run XGBoost jobs almost daily and haven't seen it. |
hi Dmlc/Xgboost
i am using redhat/ubi8:8.4 linux for docker image
and i am using code from this repo https://github.com/sllynn/spark-xgboost
spark 3.1.1 python 3.7.11
and xgboost4j and xgboost4j spark 2.12-1.6.1
kindly help
regards
|
How can i specify tracker propertise
…On Wed, Aug 31, 2022 at 8:59 AM Muhammad Bin Azeem < ***@***.***> wrote:
hi Dmlc/Xgboost
i am using redhat/ubi8:8.4 linux for docker image
and i am using code from this repo https://github.com/sllynn/spark-xgboost
spark 3.1.1 python 3.7.11
and xgboost4j and xgboost4j spark 2.12-1.6.1
kindly help
regards
|
@Ayyan-droid Consider using the pyspark in xgboost with the nightly build. Nightly build: Pyspark tutorial: |
@Ayyan-droid if you're using the XGBoost jvm packages, you can specify the Tracker configuration by
See case class TrackerConf(workerConnectionTimeout: Long, trackerImpl: String,
hostIp: String = "", pythonExec: String = "") |
hi i am getting this error can any guide me
spark version 3.1
xgboost4j_2.12-1.6.1.jar
xgboost4j-spark_2.12-1.6.1.jar
ERROR RabitTracker:179 - FAULT: failed to start tracker process
ERROR XGBoostSpark:643 - the job was aborted due to
java.lang.IllegalArgumentException: requirement failed: FAULT: Failed to start tracker
at scala.Predef$.require(Predef.scala:281)
at ml.dmlc.xgboost4j.scala.spark.XGBoost$.startTracker(XGBoost.scala:436)
at ml.dmlc.xgboost4j.scala.spark.XGBoost$.trainDistributed(XGBoost.scala:593)
at ml.dmlc.xgboost4j.scala.spark.XGBoostClassifier.train(XGBoostClassifier.scala:199)
at ml.dmlc.xgboost4j.scala.spark.XGBoostClassifier.train(XGBoostClassifier.scala:40)
at org.apache.spark.ml.Predictor.fit(Predictor.scala:151)
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 py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:282)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:238)
at java.lang.Thread.run(Thread.java:750)
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