[jira] [Updated] (SPARK-3174) Under YARN, add and remove executors based on load
[ https://issues.apache.org/jira/browse/SPARK-3174?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Sandy Ryza updated SPARK-3174: -- Attachment: SPARK-3174design.pdf > Under YARN, add and remove executors based on load > -- > > Key: SPARK-3174 > URL: https://issues.apache.org/jira/browse/SPARK-3174 > Project: Spark > Issue Type: Improvement > Components: YARN >Affects Versions: 1.0.2 >Reporter: Sandy Ryza >Assignee: Andrew Or > Attachments: SPARK-3174design.pdf > > > A common complaint with Spark in a multi-tenant environment is that > applications have a fixed allocation that doesn't grow and shrink with their > resource needs. We're blocked on YARN-1197 for dynamically changing the > resources within executors, but we can still allocate and discard whole > executors. > I think it would be useful to have some heuristics that > * Request more executors when many pending tasks are building up > * Request more executors when RDDs can't fit in memory > * Discard executors when few tasks are running / pending and there's not much > in memory > Bonus points: migrate blocks from executors we're about to discard to > executors with free space. -- 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-3174) Under YARN, add and remove executors based on load
[ https://issues.apache.org/jira/browse/SPARK-3174?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Patrick Wendell updated SPARK-3174: --- Assignee: Andrew Or > Under YARN, add and remove executors based on load > -- > > Key: SPARK-3174 > URL: https://issues.apache.org/jira/browse/SPARK-3174 > Project: Spark > Issue Type: Improvement > Components: YARN >Affects Versions: 1.0.2 >Reporter: Sandy Ryza >Assignee: Andrew Or > > A common complaint with Spark in a multi-tenant environment is that > applications have a fixed allocation that doesn't grow and shrink with their > resource needs. We're blocked on YARN-1197 for dynamically changing the > resources within executors, but we can still allocate and discard whole > executors. > I think it would be useful to have some heuristics that > * Request more executors when many pending tasks are building up > * Request more executors when RDDs can't fit in memory > * Discard executors when few tasks are running / pending and there's not much > in memory > Bonus points: migrate blocks from executors we're about to discard to > executors with free space. -- 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-3174) Under YARN, add and remove executors based on load
[ https://issues.apache.org/jira/browse/SPARK-3174?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Patrick Wendell updated SPARK-3174: --- Target Version/s: 1.2.0 > Under YARN, add and remove executors based on load > -- > > Key: SPARK-3174 > URL: https://issues.apache.org/jira/browse/SPARK-3174 > Project: Spark > Issue Type: Improvement > Components: YARN >Affects Versions: 1.0.2 >Reporter: Sandy Ryza > > A common complaint with Spark in a multi-tenant environment is that > applications have a fixed allocation that doesn't grow and shrink with their > resource needs. We're blocked on YARN-1197 for dynamically changing the > resources within executors, but we can still allocate and discard whole > executors. > I think it would be useful to have some heuristics that > * Request more executors when many pending tasks are building up > * Request more executors when RDDs can't fit in memory > * Discard executors when few tasks are running / pending and there's not much > in memory > Bonus points: migrate blocks from executors we're about to discard to > executors with free space. -- 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
