Merge pull request #39270 from Zhuzhenghao/resource-bin-package

[zh] Resync resource-bin-package.md
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---
title: 扩展资源的资源装箱
title: 资源装箱
content_type: concept
weight: 80
---
@ -9,7 +9,7 @@ reviewers:
- bsalamat
- k82cn
- ahg-g
title: Resource Bin Packing for Extended Resources
title: Resource Bin Packing
content_type: concept
weight: 80
---
@ -18,7 +18,7 @@ weight: 80
<!-- overview -->
<!--
In the [scheduling-plugin](/docs/reference/scheduling/config/#scheduling-plugins) `NodeResourcesFit` of kube-scheduler, there are two
In the [scheduling-plugin](/docs/reference/scheduling/config/#scheduling-plugins) `NodeResourcesFit` of kube-scheduler, there are two
scoring strategies that support the bin packing of resources: `MostAllocated` and `RequestedToCapacityRatio`.
-->
在 kube-scheduler 的[调度插件](/zh-cn/docs/reference/scheduling/config/#scheduling-plugins)
@ -65,7 +65,7 @@ profiles:
```
<!--
To learn more about other parameters and their default configuration, see the API documentation for
To learn more about other parameters and their default configuration, see the API documentation for
[`NodeResourcesFitArgs`](/docs/reference/config-api/kube-scheduler-config.v1beta3/#kubescheduler-config-k8s-io-v1beta3-NodeResourcesFitArgs).
-->
要进一步了解其它参数及其默认配置,请参阅
@ -83,10 +83,10 @@ configured function of the allocated resources. The behavior of the `RequestedTo
the `NodeResourcesFit` score function can be controlled by the
[scoringStrategy](/docs/reference/config-api/kube-scheduler-config.v1beta3/#kubescheduler-config-k8s-io-v1beta3-ScoringStrategy) field.
Within the `scoringStrategy` field, you can configure two parameters: `requestedToCapacityRatio` and
`resources`. The `shape` in `requestedToCapacityRatio`
parameter allows the user to tune the function as least requested or most
requested based on `utilization` and `score` values. The `resources` parameter
consists of `name` of the resource to be considered during scoring and `weight`
`resources`. The `shape` in the `requestedToCapacityRatio`
parameter allows the user to tune the function as least requested or most
requested based on `utilization` and `score` values. The `resources` parameter
consists of `name` of the resource to be considered during scoring and `weight`
specify the weight of each resource.
-->
## 使用 RequestedToCapacityRatio 策略来启用资源装箱 {#enabling-bin-packing-using-requestedtocapacityratio}
@ -133,15 +133,15 @@ profiles:
```
<!--
Referencing the `KubeSchedulerConfiguration` file with the kube-scheduler
flag `--config=/path/to/config/file` will pass the configuration to the
Referencing the `KubeSchedulerConfiguration` file with the kube-scheduler
flag `--config=/path/to/config/file` will pass the configuration to the
scheduler.
-->
使用 kube-scheduler 标志 `--config=/path/to/config/file`
引用 `KubeSchedulerConfiguration` 文件,可以将配置传递给调度器。
<!--
To learn more about other parameters and their default configuration, see the API documentation for
To learn more about other parameters and their default configuration, see the API documentation for
[`NodeResourcesFitArgs`](/docs/reference/config-api/kube-scheduler-config.v1beta3/#kubescheduler-config-k8s-io-v1beta3-NodeResourcesFitArgs).
-->
要进一步了解其它参数及其默认配置,可以参阅
@ -159,10 +159,10 @@ To learn more about other parameters and their default configuration, see the AP
```yaml
shape:
- utilization: 0
score: 0
- utilization: 100
score: 10
- utilization: 0
score: 0
- utilization: 100
score: 10
```
<!--
@ -175,7 +175,7 @@ requested the score value must be reversed as follows.
要启用最少请求least requested模式必须按如下方式反转得分值。
```yaml
shape:
shape:
- utilization: 0
score: 10
- utilization: 100
@ -183,11 +183,11 @@ requested the score value must be reversed as follows.
```
<!--
`resources` is an optional parameter which by defaults is set to:
`resources` is an optional parameter which defaults to:
-->
`resources` 是一个可选参数,默认情况下设置为:
`resources` 是一个可选参数,默认为:
``` yaml
```yaml
resources:
- name: cpu
weight: 1
@ -262,8 +262,8 @@ Node 1 spec:
```
可用:
intel.com/foo : 4
memory : 1 GB
intel.com/foo: 4
memory: 1 GB
cpu: 8
已用:
@ -282,8 +282,8 @@ intel.com/foo = resourceScoringFunction((2+1),4)
= (100 - ((4-3)*100/4)
= (100 - 25)
= 75 # requested + used = 75% * available
= rawScoringFunction(75)
= 7 # floor(75/10)
= rawScoringFunction(75)
= 7 # floor(75/10)
memory = resourceScoringFunction((256+256),1024)
= (100 -((1024-512)*100/1024))
@ -355,4 +355,3 @@ NodeScore = (5 * 5) + (7 * 1) + (10 * 3) / (5 + 1 + 3)
-->
- 继续阅读[调度器框架](/zh-cn/docs/concepts/scheduling-eviction/scheduling-framework/)
- 继续阅读[调度器配置](/zh-cn/docs/reference/scheduling/config/)