[jira] [Updated] (SPARK-17637) Packed scheduling for Spark tasks across executors
[ https://issues.apache.org/jira/browse/SPARK-17637?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Sean Owen updated SPARK-17637: -- Target Version/s: (was: 2.2.0) > Packed scheduling for Spark tasks across executors > -- > > Key: SPARK-17637 > URL: https://issues.apache.org/jira/browse/SPARK-17637 > Project: Spark > Issue Type: Improvement > Components: Scheduler >Reporter: Zhan Zhang >Assignee: Zhan Zhang >Priority: Minor > > Currently Spark scheduler implements round robin scheduling for tasks to > executors. Which is great as it distributes the load evenly across the > cluster, but this leads to significant resource waste in some cases, > especially when dynamic allocation is enabled. -- This message was sent by Atlassian JIRA (v6.3.15#6346) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Updated] (SPARK-17637) Packed scheduling for Spark tasks across executors
[ https://issues.apache.org/jira/browse/SPARK-17637?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Herman van Hovell updated SPARK-17637: -- Target Version/s: 2.2.0 (was: 2.1.0) > Packed scheduling for Spark tasks across executors > -- > > Key: SPARK-17637 > URL: https://issues.apache.org/jira/browse/SPARK-17637 > Project: Spark > Issue Type: Improvement > Components: Scheduler >Reporter: Zhan Zhang >Assignee: Zhan Zhang >Priority: Minor > > Currently Spark scheduler implements round robin scheduling for tasks to > executors. Which is great as it distributes the load evenly across the > cluster, but this leads to significant resource waste in some cases, > especially when dynamic allocation is enabled. -- 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] [Updated] (SPARK-17637) Packed scheduling for Spark tasks across executors
[ https://issues.apache.org/jira/browse/SPARK-17637?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Reynold Xin updated SPARK-17637: Affects Version/s: (was: 2.1.0) Target Version/s: 2.1.0 > Packed scheduling for Spark tasks across executors > -- > > Key: SPARK-17637 > URL: https://issues.apache.org/jira/browse/SPARK-17637 > Project: Spark > Issue Type: Improvement > Components: Scheduler >Reporter: Zhan Zhang >Assignee: Zhan Zhang >Priority: Minor > > Currently Spark scheduler implements round robin scheduling for tasks to > executors. Which is great as it distributes the load evenly across the > cluster, but this leads to significant resource waste in some cases, > especially when dynamic allocation is enabled. -- 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] [Updated] (SPARK-17637) Packed scheduling for Spark tasks across executors
[ https://issues.apache.org/jira/browse/SPARK-17637?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Sean Owen updated SPARK-17637: -- Target Version/s: (was: 2.1.0) > Packed scheduling for Spark tasks across executors > -- > > Key: SPARK-17637 > URL: https://issues.apache.org/jira/browse/SPARK-17637 > Project: Spark > Issue Type: Improvement > Components: Scheduler >Affects Versions: 2.1.0 >Reporter: Zhan Zhang >Assignee: Zhan Zhang >Priority: Minor > > Currently Spark scheduler implements round robin scheduling for tasks to > executors. Which is great as it distributes the load evenly across the > cluster, but this leads to significant resource waste in some cases, > especially when dynamic allocation is enabled. -- 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] [Updated] (SPARK-17637) Packed scheduling for Spark tasks across executors
[ https://issues.apache.org/jira/browse/SPARK-17637?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Sean Owen updated SPARK-17637: -- Fix Version/s: (was: 2.1.0) > Packed scheduling for Spark tasks across executors > -- > > Key: SPARK-17637 > URL: https://issues.apache.org/jira/browse/SPARK-17637 > Project: Spark > Issue Type: Improvement > Components: Scheduler >Affects Versions: 2.1.0 >Reporter: Zhan Zhang >Assignee: Zhan Zhang >Priority: Minor > > Currently Spark scheduler implements round robin scheduling for tasks to > executors. Which is great as it distributes the load evenly across the > cluster, but this leads to significant resource waste in some cases, > especially when dynamic allocation is enabled. -- 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] [Updated] (SPARK-17637) Packed scheduling for Spark tasks across executors
[ https://issues.apache.org/jira/browse/SPARK-17637?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Mridul Muralidharan updated SPARK-17637: Affects Version/s: 2.1.0 > Packed scheduling for Spark tasks across executors > -- > > Key: SPARK-17637 > URL: https://issues.apache.org/jira/browse/SPARK-17637 > Project: Spark > Issue Type: Improvement > Components: Scheduler >Affects Versions: 2.1.0 >Reporter: Zhan Zhang >Assignee: Zhan Zhang >Priority: Minor > Fix For: 2.1.0 > > > Currently Spark scheduler implements round robin scheduling for tasks to > executors. Which is great as it distributes the load evenly across the > cluster, but this leads to significant resource waste in some cases, > especially when dynamic allocation is enabled. -- 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] [Updated] (SPARK-17637) Packed scheduling for Spark tasks across executors
[ https://issues.apache.org/jira/browse/SPARK-17637?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Mridul Muralidharan updated SPARK-17637: Fix Version/s: 2.1.0 > Packed scheduling for Spark tasks across executors > -- > > Key: SPARK-17637 > URL: https://issues.apache.org/jira/browse/SPARK-17637 > Project: Spark > Issue Type: Improvement > Components: Scheduler >Reporter: Zhan Zhang >Priority: Minor > Fix For: 2.1.0 > > > Currently Spark scheduler implements round robin scheduling for tasks to > executors. Which is great as it distributes the load evenly across the > cluster, but this leads to significant resource waste in some cases, > especially when dynamic allocation is enabled. -- 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
