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scheduler.error() will mask the error if there are active tasks. Being removed is a cataclysmic event for Spark applications, and should probably be treated as such.
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asfgit
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May 20, 2014
scheduler.error() will mask the error if there are active tasks. Being removed is a cataclysmic event for Spark applications, and should probably be treated as such. Author: Aaron Davidson <aaron@databricks.com> Closes #832 from aarondav/i-love-u and squashes the following commits: 9f1200f [Aaron Davidson] SPARK-1689: Spark application should die when removed by Master (cherry picked from commit b0ce22e) Signed-off-by: Tathagata Das <tathagata.das1565@gmail.com>
markhamstra
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May 21, 2014
scheduler.error() will mask the error if there are active tasks. Being removed is a cataclysmic event for Spark applications, and should probably be treated as such. Author: Aaron Davidson <aaron@databricks.com> Closes apache#832 from aarondav/i-love-u and squashes the following commits: 9f1200f [Aaron Davidson] SPARK-1689: Spark application should die when removed by Master Conflicts: core/src/main/scala/org/apache/spark/scheduler/cluster/SparkDeploySchedulerBackend.scala
markhamstra
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May 28, 2014
scheduler.error() will mask the error if there are active tasks. Being removed is a cataclysmic event for Spark applications, and should probably be treated as such. Author: Aaron Davidson <aaron@databricks.com> Closes apache#832 from aarondav/i-love-u and squashes the following commits: 9f1200f [Aaron Davidson] SPARK-1689: Spark application should die when removed by Master Conflicts: core/src/main/scala/org/apache/spark/scheduler/cluster/SparkDeploySchedulerBackend.scala
pdeyhim
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Jun 25, 2014
scheduler.error() will mask the error if there are active tasks. Being removed is a cataclysmic event for Spark applications, and should probably be treated as such. Author: Aaron Davidson <aaron@databricks.com> Closes apache#832 from aarondav/i-love-u and squashes the following commits: 9f1200f [Aaron Davidson] SPARK-1689: Spark application should die when removed by Master
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scheduler.error() will mask the error if there are active tasks. Being removed is a cataclysmic event for Spark applications, and should probably be treated as such.