YARN-381. Improve fair scheduler docs. Contributed by Sandy Ryza.
git-svn-id: https://svn.apache.org/repos/asf/hadoop/common/trunk@1464130 13f79535-47bb-0310-9956-ffa450edef68
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@ -249,7 +249,7 @@ Hadoop MapReduce Next Generation - Cluster Setup
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*-------------------------+-------------------------+------------------------+
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*-------------------------+-------------------------+------------------------+
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| <<<yarn.resourcemanager.scheduler.class>>> | | |
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| <<<yarn.resourcemanager.scheduler.class>>> | | |
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| | <<<ResourceManager>>> Scheduler class. | |
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| | <<<ResourceManager>>> Scheduler class. | |
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| | | <<<CapacityScheduler>>> (recommended) or <<<FifoScheduler>>> |
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| | | <<<CapacityScheduler>>> (recommended), <<<FairScheduler>>> (also recommended), or <<<FifoScheduler>>> |
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*-------------------------+-------------------------+------------------------+
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*-------------------------+-------------------------+------------------------+
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| <<<yarn.scheduler.minimum-allocation-mb>>> | | |
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| <<<yarn.scheduler.minimum-allocation-mb>>> | | |
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| | Minimum limit of memory to allocate to each container request at the <<<Resource Manager>>>. | |
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| | Minimum limit of memory to allocate to each container request at the <<<Resource Manager>>>. | |
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@ -115,6 +115,8 @@ Release 2.0.5-beta - UNRELEASED
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YARN-447. Move ApplicationComparator in CapacityScheduler to use comparator
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YARN-447. Move ApplicationComparator in CapacityScheduler to use comparator
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in ApplicationId. (Nemon Lou via vinodkv)
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in ApplicationId. (Nemon Lou via vinodkv)
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YARN-381. Improve fair scheduler docs. (Sandy Ryza via tomwhite)
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OPTIMIZATIONS
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OPTIMIZATIONS
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BUG FIXES
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BUG FIXES
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@ -85,8 +85,9 @@ Hadoop MapReduce Next Generation - Fair Scheduler
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cause too much intermediate data to be created or too much context-switching.
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cause too much intermediate data to be created or too much context-switching.
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Limiting the apps does not cause any subsequently submitted apps to fail,
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Limiting the apps does not cause any subsequently submitted apps to fail,
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only to wait in the scheduler's queue until some of the user's earlier apps
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only to wait in the scheduler's queue until some of the user's earlier apps
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finish. apps to run from each user/queue are chosen in order of priority and
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finish. Apps to run from each user/queue are chosen in the same fair sharing
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then submit time, as in the default FIFO scheduler in Hadoop.
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manner, but can alternatively be configured to be chosen in order of submit
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time, as in the default FIFO scheduler in Hadoop.
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Certain add-ons are not yet supported which existed in the original (MR1)
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Certain add-ons are not yet supported which existed in the original (MR1)
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Fair Scheduler. Among them, is the use of a custom policies governing
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Fair Scheduler. Among them, is the use of a custom policies governing
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@ -142,7 +143,9 @@ Hadoop MapReduce Next Generation - Fair Scheduler
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* <<<yarn.scheduler.fair.sizebasedweight>>>
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* <<<yarn.scheduler.fair.sizebasedweight>>>
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* Whether to assign shares to individual apps based on their size, rather than
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* Whether to assign shares to individual apps based on their size, rather than
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providing an equal share to all apps regardless of size. Defaults to false.
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providing an equal share to all apps regardless of size. When set to true,
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apps are weighted by the natural logarithm of one plus the app's total
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requested memory, divided by the natural logarithm of 2. Defaults to false.
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* <<<yarn.scheduler.fair.assignmultiple>>>
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* <<<yarn.scheduler.fair.assignmultiple>>>
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@ -180,16 +183,29 @@ Allocation file format
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* <<Queue elements>>, which represent queues. Each may contain the following
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* <<Queue elements>>, which represent queues. Each may contain the following
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properties:
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properties:
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* minResources: minimum amount of aggregate memory
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* minResources: minimum MB of aggregate memory the queue expects. If a queue
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demands resources, and its current allocation is below its configured minimum,
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it will be assigned available resources before any queue that is not in this
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situation. If multiple queues are in this situation, resources go to the
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queue with the smallest ratio between allocation and minimum. Note that it is
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possible that a queue that is below its minimum may not immediately get up to
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its minimum when it submits an application, because already-running jobs may
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be using those resources.
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* maxResources: maximum amount of aggregate memory
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* maxResources: maximum MB of aggregate memory a queue is allowed. A queue
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will never be assigned a container that would put it over this limit.
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* maxRunningApps: limit the number of apps from the queue to run at once
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* maxRunningApps: limit the number of apps from the queue to run at once
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* weight: to share the cluster non-proportionally with other queues
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* weight: to share the cluster non-proportionally with other queues. Weights
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default to 1, and a queue with weight 2 should receive approximately twice
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as many resources as a queue with the default weight.
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* schedulingMode: either "fifo" or "fair" depending on the in-queue scheduling
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* schedulingMode: either "fifo" or "fair" depending on the in-queue scheduling
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policy desired
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policy desired. Defaults to "fair". If "fifo", apps with earlier submit
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times are given preference for containers, but apps submitted later may
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run concurrently if there is leftover space on the cluster after satisfying
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the earlier app's requests.
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* aclSubmitApps: a list of users that can submit apps to the queue. A (default)
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* aclSubmitApps: a list of users that can submit apps to the queue. A (default)
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value of "*" means that any users can submit apps. A queue inherits the ACL of
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value of "*" means that any users can submit apps. A queue inherits the ACL of
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