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JackHOO commented on MAPREDUCE-1380: ------------------------------------ I download the patch v1.2,then apply it to the hadoop-1.2.1.but it do not work on the cluster,when JobClient sumbit the job,then the task is pending all the time and never running ,what can I do ? I hope you can help me ,my email : 460759...@qq.com > 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)