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Stavros Kontopoulos edited comment on SPARK-23153 at 10/5/18 5:10 PM: ---------------------------------------------------------------------- The question is what can you do when you dont have a distributed cache like in the yarn case. Do we need to upload artifacts in the first place or fetch them remotely (eg. cluster mode)? Mesos has the same issue AFAIK. Having pre-populated PVs is not different to me as a mechanism compared to images since no uploading takes place from the submission side to the driver via spark submit. Someone has to approve PVs contents too as well when it comes to security. If we can do it in Spark without going down the path of using K8s constructs like init containers without performance issues then we should be ok. Even now, if not mistaken, executors on k8s fetch jars from the driver when they update their dependencies and that contradicts the third point. But what do you do when you need driver HA (many people use that)? Then you need check-pointing and you need to store artifacts to some storage like PVs or custom images or hdfs (distributed storage in general). If we omit the last two then the only option I see is PVs where client artifacts are uploaded via the PVs thing. On the other hand PVs can be hard to manage in general from an administration perspective and that breaks a bit the UX. On the other hand you cant really expose the driver's internal file server because it is not persistent unless you make it store its artifacts to a PV. was (Author: skonto): The question is what can you do when you dont have a distributed cache like in the yarn case. Do we need to upload artifacts in the first place or fetch them remotely (eg. cluster mode)? Mesos has the same issue AFAIK. Having pre-populated PVs is not different to me as a mechanism compared to images since no uploading takes place from the submission side to the driver via spark submit. Someone has to approve PVs contents too as well when it comes to security. If we can do it in Spark without going down the path of using K8s constructs like init containers without performance issues then we should be ok. Even now, if not mistaken, executors on k8s fetch jars from the driver when they update their dependencies and that contradicts the third point. But what do you do when you need driver HA (many people use that)? Then you need check-pointing and you need to store artifacts to some storage like PVs or custom images or hdfs (distributed storage in general). If we omit the last two then the only option I see is PVs where client artifacts are uploaded via the PVs thing. > Support application dependencies in submission client's local file system > ------------------------------------------------------------------------- > > Key: SPARK-23153 > URL: https://issues.apache.org/jira/browse/SPARK-23153 > Project: Spark > Issue Type: Improvement > Components: Kubernetes > Affects Versions: 2.4.0 > Reporter: Yinan Li > Priority: Major > > Currently local dependencies are not supported with Spark on K8S i.e. if the > user has code or dependencies only on the client where they run > {{spark-submit}} then the current implementation has no way to make those > visible to the Spark application running inside the K8S pods that get > launched. This limits users to only running applications where the code and > dependencies are either baked into the Docker images used or where those are > available via some external and globally accessible file system e.g. HDFS > which are not viable options for many users and environments -- This message was sent by Atlassian JIRA (v7.6.3#76005) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org