[jira] [Commented] (SPARK-3682) Add helpful warnings to the UI
[ https://issues.apache.org/jira/browse/SPARK-3682?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14206891#comment-14206891 ] Kay Ousterhout commented on SPARK-3682: --- Some of the metrics you mentioned fall under the additional metrics that are hidden by default; as part of this, it might be nice to automatically show a metric as part of warning a user that the value is problematic. Add helpful warnings to the UI -- Key: SPARK-3682 URL: https://issues.apache.org/jira/browse/SPARK-3682 Project: Spark Issue Type: New Feature Components: Web UI Affects Versions: 1.1.0 Reporter: Sandy Ryza Attachments: SPARK-3682Design.pdf Spark has a zillion configuration options and a zillion different things that can go wrong with a job. Improvements like incremental and better metrics and the proposed spark replay debugger provide more insight into what's going on under the covers. However, it's difficult for non-advanced users to synthesize this information and understand where to direct their attention. It would be helpful to have some sort of central location on the UI users could go to that would provide indications about why an app/job is failing or performing poorly. Some helpful messages that we could provide: * Warn that the tasks in a particular stage are spending a long time in GC. * Warn that spark.shuffle.memoryFraction does not fit inside the young generation. * Warn that tasks in a particular stage are very short, and that the number of partitions should probably be decreased. * Warn that tasks in a particular stage are spilling a lot, and that the number of partitions should probably be increased. * Warn that a cached RDD that gets a lot of use does not fit in memory, and a lot of time is being spent recomputing it. To start, probably two kinds of warnings would be most helpful. * Warnings at the app level that report on misconfigurations, issues with the general health of executors. * Warnings at the job level that indicate why a job might be performing slowly. -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-3682) Add helpful warnings to the UI
[ https://issues.apache.org/jira/browse/SPARK-3682?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14147730#comment-14147730 ] Arun Ahuja commented on SPARK-3682: --- We've been running to a lot of these issues so this would be very helpful - could you explain this one however Warn that tasks in a particular stage are spilling a lot, and that the number of partitions should probably be decreased.? Thanks! Add helpful warnings to the UI -- Key: SPARK-3682 URL: https://issues.apache.org/jira/browse/SPARK-3682 Project: Spark Issue Type: New Feature Components: Web UI Affects Versions: 1.1.0 Reporter: Sandy Ryza Spark has a zillion configuration options and a zillion different things that can go wrong with a job. Improvements like incremental and better metrics and the proposed spark replay debugger provide more insight into what's going on under the covers. However, it's difficult for non-advanced users to synthesize this information and understand where to direct their attention. It would be helpful to have some sort of central location on the UI users could go to that would provide indications about why an app/job is failing or performing poorly. Some helpful messages that we could provide: * Warn that the tasks in a particular stage are spending a long time in GC. * Warn that spark.shuffle.memoryFraction does not fit inside the young generation. * Warn that tasks in a particular stage are very short, and that the number of partitions should probably be decreased. * Warn that tasks in a particular stage are spilling a lot, and that the number of partitions should probably be decreased. * Warn that a cached RDD that gets a lot of use does not fit in memory, and a lot of time is being spent recomputing it. To start, probably two kinds of warnings would be most helpful. * Warnings at the app level that report on misconfigurations, issues with the general health of executors. * Warnings at the job level that indicate why a job might be performing slowly. -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-3682) Add helpful warnings to the UI
[ https://issues.apache.org/jira/browse/SPARK-3682?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14148379#comment-14148379 ] Sandy Ryza commented on SPARK-3682: --- Oops, that should have read increased. When a task fetches more shuffle data from the previous stage than it can fit in memory, it needs to spill the extra data to disk. Increasing the number of partitions makes it so that each task will be responsible for dealing with less data and will need to spill less. Add helpful warnings to the UI -- Key: SPARK-3682 URL: https://issues.apache.org/jira/browse/SPARK-3682 Project: Spark Issue Type: New Feature Components: Web UI Affects Versions: 1.1.0 Reporter: Sandy Ryza Spark has a zillion configuration options and a zillion different things that can go wrong with a job. Improvements like incremental and better metrics and the proposed spark replay debugger provide more insight into what's going on under the covers. However, it's difficult for non-advanced users to synthesize this information and understand where to direct their attention. It would be helpful to have some sort of central location on the UI users could go to that would provide indications about why an app/job is failing or performing poorly. Some helpful messages that we could provide: * Warn that the tasks in a particular stage are spending a long time in GC. * Warn that spark.shuffle.memoryFraction does not fit inside the young generation. * Warn that tasks in a particular stage are very short, and that the number of partitions should probably be decreased. * Warn that tasks in a particular stage are spilling a lot, and that the number of partitions should probably be increased. * Warn that a cached RDD that gets a lot of use does not fit in memory, and a lot of time is being spent recomputing it. To start, probably two kinds of warnings would be most helpful. * Warnings at the app level that report on misconfigurations, issues with the general health of executors. * Warnings at the job level that indicate why a job might be performing slowly. -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
