[jira] [Updated] (MAPREDUCE-1380) Adaptive Scheduler
[ https://issues.apache.org/jira/browse/MAPREDUCE-1380?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] ericson yang updated MAPREDUCE-1380: Assignee: Jordà Polo (was: ericson yang) Adaptive Scheduler -- Key: MAPREDUCE-1380 URL: https://issues.apache.org/jira/browse/MAPREDUCE-1380 Project: Hadoop Map/Reduce Issue Type: New Feature Affects Versions: 2.4.1 Reporter: Jordà Polo Assignee: Jordà Polo Priority: Minor Attachments: MAPREDUCE-1380-branch-1.2.patch, MAPREDUCE-1380_0.1.patch, MAPREDUCE-1380_1.1.patch, MAPREDUCE-1380_1.1.pdf The Adaptive Scheduler is a pluggable Hadoop scheduler that automatically adjusts the amount of used resources depending on the performance of jobs and on user-defined high-level business goals. Existing Hadoop schedulers are focused on managing large, static clusters in which nodes are added or removed manually. On the other hand, the goal of this scheduler is to improve the integration of Hadoop and the applications that run on top of it with environments that allow a more dynamic provisioning of resources. The current implementation is quite straightforward. Users specify a deadline at job submission time, and the scheduler adjusts the resources to meet that deadline (at the moment, the scheduler can be configured to either minimize or maximize the amount of resources). If multiple jobs are run simultaneously, the scheduler prioritizes them by deadline. Note that the current approach to estimate the completion time of jobs is quite simplistic: it is based on the time it takes to finish each task, so it works well with regular jobs, but there is still room for improvement for unpredictable jobs. The idea is to further integrate it with cloud-like and virtual environments (such as Amazon EC2, Emotive, etc.) so that if, for instance, a job isn't able to meet its deadline, the scheduler automatically requests more resources. -- This message was sent by Atlassian JIRA (v6.3.4#6332)
[jira] [Updated] (MAPREDUCE-1380) Adaptive Scheduler
[ https://issues.apache.org/jira/browse/MAPREDUCE-1380?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Allen Wittenauer updated MAPREDUCE-1380: Labels: (was: BB2015-05-TBR) Adaptive Scheduler -- Key: MAPREDUCE-1380 URL: https://issues.apache.org/jira/browse/MAPREDUCE-1380 Project: Hadoop Map/Reduce Issue Type: New Feature Affects Versions: 2.4.1 Reporter: Jordà Polo Assignee: Jordà Polo Priority: Minor Attachments: MAPREDUCE-1380-branch-1.2.patch, MAPREDUCE-1380_0.1.patch, MAPREDUCE-1380_1.1.patch, MAPREDUCE-1380_1.1.pdf The Adaptive Scheduler is a pluggable Hadoop scheduler that automatically adjusts the amount of used resources depending on the performance of jobs and on user-defined high-level business goals. Existing Hadoop schedulers are focused on managing large, static clusters in which nodes are added or removed manually. On the other hand, the goal of this scheduler is to improve the integration of Hadoop and the applications that run on top of it with environments that allow a more dynamic provisioning of resources. The current implementation is quite straightforward. Users specify a deadline at job submission time, and the scheduler adjusts the resources to meet that deadline (at the moment, the scheduler can be configured to either minimize or maximize the amount of resources). If multiple jobs are run simultaneously, the scheduler prioritizes them by deadline. Note that the current approach to estimate the completion time of jobs is quite simplistic: it is based on the time it takes to finish each task, so it works well with regular jobs, but there is still room for improvement for unpredictable jobs. The idea is to further integrate it with cloud-like and virtual environments (such as Amazon EC2, Emotive, etc.) so that if, for instance, a job isn't able to meet its deadline, the scheduler automatically requests more resources. -- This message was sent by Atlassian JIRA (v6.3.4#6332)
[jira] [Updated] (MAPREDUCE-1380) Adaptive Scheduler
[ https://issues.apache.org/jira/browse/MAPREDUCE-1380?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Allen Wittenauer updated MAPREDUCE-1380: Assignee: Jordà Polo Adaptive Scheduler -- Key: MAPREDUCE-1380 URL: https://issues.apache.org/jira/browse/MAPREDUCE-1380 Project: Hadoop Map/Reduce Issue Type: New Feature Affects Versions: 2.4.1 Reporter: Jordà Polo Assignee: Jordà Polo Priority: Minor Attachments: MAPREDUCE-1380-branch-1.2.patch, MAPREDUCE-1380_0.1.patch, MAPREDUCE-1380_1.1.patch, MAPREDUCE-1380_1.1.pdf The Adaptive Scheduler is a pluggable Hadoop scheduler that automatically adjusts the amount of used resources depending on the performance of jobs and on user-defined high-level business goals. Existing Hadoop schedulers are focused on managing large, static clusters in which nodes are added or removed manually. On the other hand, the goal of this scheduler is to improve the integration of Hadoop and the applications that run on top of it with environments that allow a more dynamic provisioning of resources. The current implementation is quite straightforward. Users specify a deadline at job submission time, and the scheduler adjusts the resources to meet that deadline (at the moment, the scheduler can be configured to either minimize or maximize the amount of resources). If multiple jobs are run simultaneously, the scheduler prioritizes them by deadline. Note that the current approach to estimate the completion time of jobs is quite simplistic: it is based on the time it takes to finish each task, so it works well with regular jobs, but there is still room for improvement for unpredictable jobs. The idea is to further integrate it with cloud-like and virtual environments (such as Amazon EC2, Emotive, etc.) so that if, for instance, a job isn't able to meet its deadline, the scheduler automatically requests more resources. -- This message was sent by Atlassian JIRA (v6.3.4#6332)
[jira] [Updated] (MAPREDUCE-1380) Adaptive Scheduler
[ https://issues.apache.org/jira/browse/MAPREDUCE-1380?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Allen Wittenauer updated MAPREDUCE-1380: Status: Open (was: Patch Available) Cancelling the patch. Work on branch-1 has effectively stopped. Unless there is some interesting in porting this work to branch-2, we should close this as won't fix. Thanks. Adaptive Scheduler -- Key: MAPREDUCE-1380 URL: https://issues.apache.org/jira/browse/MAPREDUCE-1380 Project: Hadoop Map/Reduce Issue Type: New Feature Affects Versions: 2.4.1 Reporter: Jordà Polo Assignee: Jordà Polo Priority: Minor Attachments: MAPREDUCE-1380-branch-1.2.patch, MAPREDUCE-1380_0.1.patch, MAPREDUCE-1380_1.1.patch, MAPREDUCE-1380_1.1.pdf The Adaptive Scheduler is a pluggable Hadoop scheduler that automatically adjusts the amount of used resources depending on the performance of jobs and on user-defined high-level business goals. Existing Hadoop schedulers are focused on managing large, static clusters in which nodes are added or removed manually. On the other hand, the goal of this scheduler is to improve the integration of Hadoop and the applications that run on top of it with environments that allow a more dynamic provisioning of resources. The current implementation is quite straightforward. Users specify a deadline at job submission time, and the scheduler adjusts the resources to meet that deadline (at the moment, the scheduler can be configured to either minimize or maximize the amount of resources). If multiple jobs are run simultaneously, the scheduler prioritizes them by deadline. Note that the current approach to estimate the completion time of jobs is quite simplistic: it is based on the time it takes to finish each task, so it works well with regular jobs, but there is still room for improvement for unpredictable jobs. The idea is to further integrate it with cloud-like and virtual environments (such as Amazon EC2, Emotive, etc.) so that if, for instance, a job isn't able to meet its deadline, the scheduler automatically requests more resources. -- This message was sent by Atlassian JIRA (v6.3.4#6332)
[jira] [Updated] (MAPREDUCE-1380) Adaptive Scheduler
[ https://issues.apache.org/jira/browse/MAPREDUCE-1380?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Allen Wittenauer updated MAPREDUCE-1380: Labels: BB2015-05-TBR (was: ) Adaptive Scheduler -- Key: MAPREDUCE-1380 URL: https://issues.apache.org/jira/browse/MAPREDUCE-1380 Project: Hadoop Map/Reduce Issue Type: New Feature Affects Versions: 2.4.1 Reporter: Jordà Polo Priority: Minor Labels: BB2015-05-TBR Attachments: MAPREDUCE-1380-branch-1.2.patch, MAPREDUCE-1380_0.1.patch, MAPREDUCE-1380_1.1.patch, MAPREDUCE-1380_1.1.pdf The Adaptive Scheduler is a pluggable Hadoop scheduler that automatically adjusts the amount of used resources depending on the performance of jobs and on user-defined high-level business goals. Existing Hadoop schedulers are focused on managing large, static clusters in which nodes are added or removed manually. On the other hand, the goal of this scheduler is to improve the integration of Hadoop and the applications that run on top of it with environments that allow a more dynamic provisioning of resources. The current implementation is quite straightforward. Users specify a deadline at job submission time, and the scheduler adjusts the resources to meet that deadline (at the moment, the scheduler can be configured to either minimize or maximize the amount of resources). If multiple jobs are run simultaneously, the scheduler prioritizes them by deadline. Note that the current approach to estimate the completion time of jobs is quite simplistic: it is based on the time it takes to finish each task, so it works well with regular jobs, but there is still room for improvement for unpredictable jobs. The idea is to further integrate it with cloud-like and virtual environments (such as Amazon EC2, Emotive, etc.) so that if, for instance, a job isn't able to meet its deadline, the scheduler automatically requests more resources. -- This message was sent by Atlassian JIRA (v6.3.4#6332)
[jira] [Updated] (MAPREDUCE-1380) Adaptive Scheduler
[ https://issues.apache.org/jira/browse/MAPREDUCE-1380?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Anonymous updated MAPREDUCE-1380: - Target Version/s: 2.4.1 Affects Version/s: 2.4.1 Hadoop Flags: Incompatible change,Reviewed Status: Patch Available (was: Reopened) Adaptive Scheduler -- Key: MAPREDUCE-1380 URL: https://issues.apache.org/jira/browse/MAPREDUCE-1380 Project: Hadoop Map/Reduce Issue Type: New Feature Affects Versions: 2.4.1 Reporter: Jordà Polo Priority: Minor Attachments: MAPREDUCE-1380-branch-1.2.patch, MAPREDUCE-1380_0.1.patch, MAPREDUCE-1380_1.1.patch, MAPREDUCE-1380_1.1.pdf The Adaptive Scheduler is a pluggable Hadoop scheduler that automatically adjusts the amount of used resources depending on the performance of jobs and on user-defined high-level business goals. Existing Hadoop schedulers are focused on managing large, static clusters in which nodes are added or removed manually. On the other hand, the goal of this scheduler is to improve the integration of Hadoop and the applications that run on top of it with environments that allow a more dynamic provisioning of resources. The current implementation is quite straightforward. Users specify a deadline at job submission time, and the scheduler adjusts the resources to meet that deadline (at the moment, the scheduler can be configured to either minimize or maximize the amount of resources). If multiple jobs are run simultaneously, the scheduler prioritizes them by deadline. Note that the current approach to estimate the completion time of jobs is quite simplistic: it is based on the time it takes to finish each task, so it works well with regular jobs, but there is still room for improvement for unpredictable jobs. The idea is to further integrate it with cloud-like and virtual environments (such as Amazon EC2, Emotive, etc.) so that if, for instance, a job isn't able to meet its deadline, the scheduler automatically requests more resources. -- This message was sent by Atlassian JIRA (v6.2#6252)
[jira] [Updated] (MAPREDUCE-1380) Adaptive Scheduler
[ https://issues.apache.org/jira/browse/MAPREDUCE-1380?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Harsh J updated MAPREDUCE-1380: --- Hadoop Flags: (was: Incompatible change,Reviewed) Adaptive Scheduler -- Key: MAPREDUCE-1380 URL: https://issues.apache.org/jira/browse/MAPREDUCE-1380 Project: Hadoop Map/Reduce Issue Type: New Feature Affects Versions: 2.4.1 Reporter: Jordà Polo Priority: Minor Attachments: MAPREDUCE-1380-branch-1.2.patch, MAPREDUCE-1380_0.1.patch, MAPREDUCE-1380_1.1.patch, MAPREDUCE-1380_1.1.pdf The Adaptive Scheduler is a pluggable Hadoop scheduler that automatically adjusts the amount of used resources depending on the performance of jobs and on user-defined high-level business goals. Existing Hadoop schedulers are focused on managing large, static clusters in which nodes are added or removed manually. On the other hand, the goal of this scheduler is to improve the integration of Hadoop and the applications that run on top of it with environments that allow a more dynamic provisioning of resources. The current implementation is quite straightforward. Users specify a deadline at job submission time, and the scheduler adjusts the resources to meet that deadline (at the moment, the scheduler can be configured to either minimize or maximize the amount of resources). If multiple jobs are run simultaneously, the scheduler prioritizes them by deadline. Note that the current approach to estimate the completion time of jobs is quite simplistic: it is based on the time it takes to finish each task, so it works well with regular jobs, but there is still room for improvement for unpredictable jobs. The idea is to further integrate it with cloud-like and virtual environments (such as Amazon EC2, Emotive, etc.) so that if, for instance, a job isn't able to meet its deadline, the scheduler automatically requests more resources. -- This message was sent by Atlassian JIRA (v6.2#6252)
[jira] [Updated] (MAPREDUCE-1380) Adaptive Scheduler
[ https://issues.apache.org/jira/browse/MAPREDUCE-1380?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Jordà Polo updated MAPREDUCE-1380: -- Attachment: MAPREDUCE-1380-branch-1.2.patch Attaching a more up-to-date version of the scheduler that should apply cleanly against 1.2.x. Adaptive Scheduler -- Key: MAPREDUCE-1380 URL: https://issues.apache.org/jira/browse/MAPREDUCE-1380 Project: Hadoop Map/Reduce Issue Type: New Feature Reporter: Jordà Polo Priority: Minor Attachments: MAPREDUCE-1380-branch-1.2.patch, MAPREDUCE-1380_0.1.patch, MAPREDUCE-1380_1.1.patch, MAPREDUCE-1380_1.1.pdf The Adaptive Scheduler is a pluggable Hadoop scheduler that automatically adjusts the amount of used resources depending on the performance of jobs and on user-defined high-level business goals. Existing Hadoop schedulers are focused on managing large, static clusters in which nodes are added or removed manually. On the other hand, the goal of this scheduler is to improve the integration of Hadoop and the applications that run on top of it with environments that allow a more dynamic provisioning of resources. The current implementation is quite straightforward. Users specify a deadline at job submission time, and the scheduler adjusts the resources to meet that deadline (at the moment, the scheduler can be configured to either minimize or maximize the amount of resources). If multiple jobs are run simultaneously, the scheduler prioritizes them by deadline. Note that the current approach to estimate the completion time of jobs is quite simplistic: it is based on the time it takes to finish each task, so it works well with regular jobs, but there is still room for improvement for unpredictable jobs. The idea is to further integrate it with cloud-like and virtual environments (such as Amazon EC2, Emotive, etc.) so that if, for instance, a job isn't able to meet its deadline, the scheduler automatically requests more resources. -- This message was sent by Atlassian JIRA (v6.1.5#6160)
[jira] Updated: (MAPREDUCE-1380) Adaptive Scheduler
[ https://issues.apache.org/jira/browse/MAPREDUCE-1380?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Jordà Polo updated MAPREDUCE-1380: -- Attachment: MAPREDUCE-1380_1.1.patch Patch against trunk. Adaptive Scheduler -- Key: MAPREDUCE-1380 URL: https://issues.apache.org/jira/browse/MAPREDUCE-1380 Project: Hadoop Map/Reduce Issue Type: New Feature Reporter: Jordà Polo Priority: Minor Attachments: MAPREDUCE-1380_0.1.patch, MAPREDUCE-1380_1.1.patch The Adaptive Scheduler is a pluggable Hadoop scheduler that automatically adjusts the amount of used resources depending on the performance of jobs and on user-defined high-level business goals. Existing Hadoop schedulers are focused on managing large, static clusters in which nodes are added or removed manually. On the other hand, the goal of this scheduler is to improve the integration of Hadoop and the applications that run on top of it with environments that allow a more dynamic provisioning of resources. The current implementation is quite straightforward. Users specify a deadline at job submission time, and the scheduler adjusts the resources to meet that deadline (at the moment, the scheduler can be configured to either minimize or maximize the amount of resources). If multiple jobs are run simultaneously, the scheduler prioritizes them by deadline. Note that the current approach to estimate the completion time of jobs is quite simplistic: it is based on the time it takes to finish each task, so it works well with regular jobs, but there is still room for improvement for unpredictable jobs. The idea is to further integrate it with cloud-like and virtual environments (such as Amazon EC2, Emotive, etc.) so that if, for instance, a job isn't able to meet its deadline, the scheduler automatically requests more resources. -- This message is automatically generated by JIRA. - For more information on JIRA, see: http://www.atlassian.com/software/jira
[jira] Updated: (MAPREDUCE-1380) Adaptive Scheduler
[ https://issues.apache.org/jira/browse/MAPREDUCE-1380?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Jordà Polo updated MAPREDUCE-1380: -- Attachment: MAPREDUCE-1380_1.1.pdf Adaptive Scheduler -- Key: MAPREDUCE-1380 URL: https://issues.apache.org/jira/browse/MAPREDUCE-1380 Project: Hadoop Map/Reduce Issue Type: New Feature Reporter: Jordà Polo Priority: Minor Attachments: MAPREDUCE-1380_0.1.patch, MAPREDUCE-1380_1.1.patch, MAPREDUCE-1380_1.1.pdf The Adaptive Scheduler is a pluggable Hadoop scheduler that automatically adjusts the amount of used resources depending on the performance of jobs and on user-defined high-level business goals. Existing Hadoop schedulers are focused on managing large, static clusters in which nodes are added or removed manually. On the other hand, the goal of this scheduler is to improve the integration of Hadoop and the applications that run on top of it with environments that allow a more dynamic provisioning of resources. The current implementation is quite straightforward. Users specify a deadline at job submission time, and the scheduler adjusts the resources to meet that deadline (at the moment, the scheduler can be configured to either minimize or maximize the amount of resources). If multiple jobs are run simultaneously, the scheduler prioritizes them by deadline. Note that the current approach to estimate the completion time of jobs is quite simplistic: it is based on the time it takes to finish each task, so it works well with regular jobs, but there is still room for improvement for unpredictable jobs. The idea is to further integrate it with cloud-like and virtual environments (such as Amazon EC2, Emotive, etc.) so that if, for instance, a job isn't able to meet its deadline, the scheduler automatically requests more resources. -- This message is automatically generated by JIRA. - For more information on JIRA, see: http://www.atlassian.com/software/jira
[jira] Updated: (MAPREDUCE-1380) Adaptive Scheduler
[ https://issues.apache.org/jira/browse/MAPREDUCE-1380?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Jordà Polo updated MAPREDUCE-1380: -- Attachment: MAPREDUCE-1380_0.1.patch I'm attaching a patch with an initial version of the scheduler. As I said, this is still a work in progress and I'll be posting new versions as they are ready. There is still some work left to make it useful for everyone and not just for our own needs, but I wanted to contribute it now since it may be of interest to other people. (I'll also be posting a PDF with additional documentation later today.) Adaptive Scheduler -- Key: MAPREDUCE-1380 URL: https://issues.apache.org/jira/browse/MAPREDUCE-1380 Project: Hadoop Map/Reduce Issue Type: New Feature Reporter: Jordà Polo Priority: Minor Attachments: MAPREDUCE-1380_0.1.patch The Adaptive Scheduler is a pluggable Hadoop scheduler that automatically adjusts the amount of used resources depending on the performance of jobs and on user-defined high-level business goals. Existing Hadoop schedulers are focused on managing large, static clusters in which nodes are added or removed manually. On the other hand, the goal of this scheduler is to improve the integration of Hadoop and the applications that run on top of it with environments that allow a more dynamic provisioning of resources. The current implementation is quite straightforward. Users specify a deadline at job submission time, and the scheduler adjusts the resources to meet that deadline (at the moment, the scheduler can be configured to either minimize or maximize the amount of resources). If multiple jobs are run simultaneously, the scheduler prioritizes them by deadline. Note that the current approach to estimate the completion time of jobs is quite simplistic: it is based on the time it takes to finish each task, so it works well with regular jobs, but there is still room for improvement for unpredictable jobs. The idea is to further integrate it with cloud-like and virtual environments (such as Amazon EC2, Emotive, etc.) so that if, for instance, a job isn't able to meet its deadline, the scheduler automatically requests more resources. -- This message is automatically generated by JIRA. - You can reply to this email to add a comment to the issue online.
