update zh-trans content/zh/docs/tasks/job/parallel-processing-expansion.md (#19636)
This commit is contained in:
chentanjun
@@ -1,302 +1,341 @@
|
|||||||
---
|
---
|
||||||
title: 使用扩展进行并行处理
|
title: 使用扩展进行并行处理
|
||||||
content_template: templates/concept
|
content_template: templates/concept
|
||||||
weight: 20
|
min-kubernetes-server-version: v1.8
|
||||||
---
|
weight: 20
|
||||||
|
---
|
||||||
<!--
|
|
||||||
---
|
<!--
|
||||||
title: Parallel Processing using Expansions
|
---
|
||||||
content_template: templates/concept
|
title: Parallel Processing using Expansions
|
||||||
weight: 20
|
content_template: templates/concept
|
||||||
---
|
min-kubernetes-server-version: v1.8
|
||||||
-->
|
weight: 20
|
||||||
|
---
|
||||||
{{% capture overview %}}
|
-->
|
||||||
|
|
||||||
<!--
|
{{% capture overview %}}
|
||||||
In this example, we will run multiple Kubernetes Jobs created from
|
|
||||||
a common template. You may want to be familiar with the basic,
|
<!--
|
||||||
non-parallel, use of [Jobs](/docs/concepts/workloads/controllers/jobs-run-to-completion/) first.
|
In this example, we will run multiple Kubernetes Jobs created from
|
||||||
-->
|
a common template. You may want to be familiar with the basic,
|
||||||
在这个示例中，我们将运行从一个公共模板创建的多个 Kubernetes 作业。您可能希望熟悉
|
non-parallel, use of [Jobs](/docs/concepts/workloads/controllers/jobs-run-to-completion/) first.
|
||||||
[Jobs](/docs/concepts/workloads/controllers/jobs-run-to-completion/) 的基本、非并行使用。
|
-->
|
||||||
|
在这个示例中，我们将运行从一个公共模板创建的多个 Kubernetes Job。您可能需要先熟悉 [Jobs](/docs/concepts/workloads/controllers/jobs-run-to-completion/) 的基本概念、非并行以及如何使用它。
|
||||||
{{% /capture %}}
|
|
||||||
|
{{% /capture %}}
|
||||||
|
|
||||||
{{% capture body %}}
|
|
||||||
|
{{% capture body %}}
|
||||||
<!--
|
|
||||||
## Basic Template Expansion
|
<!--
|
||||||
-->
|
## Basic Template Expansion
|
||||||
|
-->
|
||||||
## 基本模板扩展
|
|
||||||
|
## 基本模板扩展
|
||||||
<!--
|
|
||||||
First, download the following template of a job to a file called `job-tmpl.yaml`
|
<!--
|
||||||
-->
|
First, download the following template of a job to a file called `job-tmpl.yaml`
|
||||||
首先，将以下作业模板下载到名为 `job-tmpl.yaml` 的文件中
|
-->
|
||||||
|
首先，将以下作业模板下载到名为 `job-tmpl.yaml` 的文件中。
|
||||||
{{< codenew file="application/job/job-tmpl.yaml" >}}
|
|
||||||
|
{{< codenew file="application/job/job-tmpl.yaml" >}}
|
||||||
<!--
|
|
||||||
Unlike a *pod template*, our *job template* is not a Kubernetes API type. It is just
|
<!--
|
||||||
a yaml representation of a Job object that has some placeholders that need to be filled
|
Unlike a *pod template*, our *job template* is not a Kubernetes API type. It is just
|
||||||
in before it can be used. The `$ITEM` syntax is not meaningful to Kubernetes.
|
a yaml representation of a Job object that has some placeholders that need to be filled
|
||||||
-->
|
in before it can be used. The `$ITEM` syntax is not meaningful to Kubernetes.
|
||||||
与 *pod 模板*不同，我们的 *job 模板*不是 Kubernetes API 类型。它只是作业对象的 yaml 表示，
|
-->
|
||||||
YAML 文件有一些占位符，在使用它之前需要填充这些占位符。`$ITEM` 语法对 Kubernetes 没有意义。
|
与 *pod 模板*不同，我们的 *job 模板*不是 Kubernetes API 类型。它只是 Job 对象的 yaml 表示，
|
||||||
|
YAML 文件有一些占位符，在使用它之前需要填充这些占位符。`$ITEM` 语法对 Kubernetes 没有意义。
|
||||||
<!--
|
|
||||||
In this example, the only processing the container does is to `echo` a string and sleep for a bit.
|
<!--
|
||||||
In a real use case, the processing would be some substantial computation, such as rendering a frame
|
In this example, the only processing the container does is to `echo` a string and sleep for a bit.
|
||||||
of a movie, or processing a range of rows in a database. The `$ITEM` parameter would specify for
|
In a real use case, the processing would be some substantial computation, such as rendering a frame
|
||||||
example, the frame number or the row range.
|
of a movie, or processing a range of rows in a database. The `$ITEM` parameter would specify for
|
||||||
-->
|
example, the frame number or the row range.
|
||||||
在这个例子中，容器所做的唯一处理是 `echo` 一个字符串并休眠一段时间。
|
-->
|
||||||
在真实的用例中，处理将是一些重要的计算，例如呈现电影的帧，或者处理数据库中的一系列行。例如，`$ITEM` 参数将指定帧号或行范围。
|
在这个例子中，容器所做的唯一处理是 `echo` 一个字符串并睡眠一段时间。
|
||||||
|
在真实的用例中，处理将是一些重要的计算，例如渲染电影的一帧，或者处理数据库中的若干行。这时，`$ITEM` 参数将指定帧号或行范围。
|
||||||
<!--
|
|
||||||
This Job and its Pod template have a label: `jobgroup=jobexample`. There is nothing special
|
<!--
|
||||||
to the system about this label.
|
This Job and its Pod template have a label: `jobgroup=jobexample`. There is nothing special
|
||||||
This label makes it convenient to operate on all the jobs in this group at once.
|
to the system about this label. This label
|
||||||
We also put the same label on the pod template so that we can check on all Pods of these Jobs
|
makes it convenient to operate on all the jobs in this group at once.
|
||||||
with a single command.
|
We also put the same label on the pod template so that we can check on all Pods of these Jobs
|
||||||
After the job is created, the system will add more labels that distinguish one Job's pods
|
with a single command.
|
||||||
from another Job's pods.
|
After the job is created, the system will add more labels that distinguish one Job's pods
|
||||||
Note that the label key `jobgroup` is not special to Kubernetes. You can pick your own label scheme.
|
from another Job's pods.
|
||||||
-->
|
Note that the label key `jobgroup` is not special to Kubernetes. You can pick your own label scheme.
|
||||||
这个作业及其 Pod 模板有一个标签: `jobgroup=jobexample`。这个标签在系统中没有什么特别之处。
|
-->
|
||||||
这个标签使得我们可以方便地同时操作组中的所有作业。
|
这个 Job 及其 Pod 模板有一个标签: `jobgroup=jobexample`。这个标签在系统中没有什么特别之处。
|
||||||
我们还将相同的标签放在 pod 模板上，这样我们就可以用一个命令检查这些作业的所有 pod。
|
这个标签使得我们可以方便地同时操作组中的所有作业。
|
||||||
创建作业之后，系统将添加更多的标签来区分一个作业的 pod 和另一个作业的 pod。
|
我们还将相同的标签放在 pod 模板上，这样我们就可以用一个命令检查这些 Job 的所有 pod。
|
||||||
注意，标签键 `jobgroup` 对 Kubernetes 并无特殊含义。您可以选择自己的标签方案。
|
创建作业之后，系统将添加更多的标签来区分一个 Job 的 pod 和另一个 Job 的 pod。
|
||||||
|
注意，标签键 `jobgroup` 对 Kubernetes 并无特殊含义。您可以选择自己的标签方案。
|
||||||
<!--
|
|
||||||
Next, expand the template into multiple files, one for each item to be processed.
|
<!--
|
||||||
-->
|
Next, expand the template into multiple files, one for each item to be processed.
|
||||||
下一步，将模板展开到多个文件中，每个文件对应要处理的项。
|
-->
|
||||||
|
下一步，将模板展开到多个文件中，每个文件对应要处理的项。
|
||||||
```shell
|
|
||||||
# Expand files into a temporary directory
|
```shell
|
||||||
$ mkdir ./jobs
|
# 下载 job-templ.yaml
|
||||||
$ for i in apple banana cherry
|
curl -L -s -O https://k8s.io/examples/application/job/job-tmpl.yaml
|
||||||
do
|
|
||||||
cat job-tmpl.yaml | sed "s/\$ITEM/$i/" > ./jobs/job-$i.yaml
|
# 创建临时目录，并且在目录中创建 job yaml 文件
|
||||||
done
|
mkdir ./jobs
|
||||||
```
|
for i in apple banana cherry
|
||||||
|
do
|
||||||
<!--
|
cat job-tmpl.yaml | sed "s/\$ITEM/$i/" > ./jobs/job-$i.yaml
|
||||||
Check if it worked:
|
done
|
||||||
-->
|
```
|
||||||
检查是否工作正常：
|
|
||||||
|
<!--
|
||||||
```shell
|
Check if it worked:
|
||||||
$ ls jobs/
|
-->
|
||||||
job-apple.yaml
|
检查是否工作正常：
|
||||||
job-banana.yaml
|
|
||||||
job-cherry.yaml
|
```shell
|
||||||
```
|
ls jobs/
|
||||||
|
```
|
||||||
<!--
|
|
||||||
Here, we used `sed` to replace the string `$ITEM` with the loop variable.
|
<!--
|
||||||
You could use any type of template language (jinja2, erb) or write a program
|
The output is similar to this:
|
||||||
to generate the Job objects.
|
-->
|
||||||
-->
|
输出类似以下内容：
|
||||||
在这里，我们使用 `sed` 将字符串 `$ITEM` 替换为循环变量。
|
|
||||||
您可以使用任何类型的模板语言(jinja2, erb) 或编写程序来生成作业对象。
|
```
|
||||||
|
job-apple.yaml
|
||||||
<!--
|
job-banana.yaml
|
||||||
Next, create all the jobs with one kubectl command:
|
job-cherry.yaml
|
||||||
-->
|
```
|
||||||
接下来，使用 kubectl 命令创建所有作业：
|
|
||||||
|
<!--
|
||||||
```shell
|
Here, we used `sed` to replace the string `$ITEM` with the loop variable.
|
||||||
$ kubectl create -f ./jobs
|
You could use any type of template language (jinja2, erb) or write a program
|
||||||
job "process-item-apple" created
|
to generate the Job objects.
|
||||||
job "process-item-banana" created
|
-->
|
||||||
job "process-item-cherry" created
|
在这里，我们使用 `sed` 将字符串 `$ITEM` 替换为循环变量。
|
||||||
```
|
您可以使用任何类型的模板语言(jinja2, erb) 或编写程序来生成 Job 对象。
|
||||||
|
|
||||||
<!--
|
<!--
|
||||||
Now, check on the jobs:
|
Next, create all the jobs with one kubectl command:
|
||||||
-->
|
-->
|
||||||
现在，检查这些作业：
|
接下来，使用 kubectl 命令创建所有作业：
|
||||||
|
|
||||||
```shell
|
```shell
|
||||||
$ kubectl get jobs -l jobgroup=jobexample
|
kubectl create -f ./jobs
|
||||||
NAME DESIRED SUCCESSFUL AGE
|
```
|
||||||
process-item-apple 1 1 31s
|
|
||||||
process-item-banana 1 1 31s
|
<!--
|
||||||
process-item-cherry 1 1 31s
|
The output is similar to this:
|
||||||
```
|
-->
|
||||||
|
输出类似以下内容：
|
||||||
<!--
|
|
||||||
Here we use the `-l` option to select all jobs that are part of this
|
```
|
||||||
group of jobs. (There might be other unrelated jobs in the system that we
|
job.batch/process-item-apple created
|
||||||
do not care to see.)
|
job.batch/process-item-banana created
|
||||||
-->
|
job.batch/process-item-cherry created
|
||||||
在这里，我们使用 `-l` 选项选择属于这组作业的所有作业。(系统中可能还有其他不相关的工作，我们不想看到。)
|
```
|
||||||
|
|
||||||
<!--
|
<!--
|
||||||
We can check on the pods as well using the same label selector:
|
Now, check on the jobs:
|
||||||
-->
|
-->
|
||||||
我们可以检查 pod 以及使用同样地标签选择器：
|
现在，检查这些作业：
|
||||||
|
|
||||||
```shell
|
```shell
|
||||||
$ kubectl get pods -l jobgroup=jobexample
|
kubectl get jobs -l jobgroup=jobexample
|
||||||
NAME READY STATUS RESTARTS AGE
|
```
|
||||||
process-item-apple-kixwv 0/1 Completed 0 4m
|
|
||||||
process-item-banana-wrsf7 0/1 Completed 0 4m
|
<!--
|
||||||
process-item-cherry-dnfu9 0/1 Completed 0 4m
|
The output is similar to this:
|
||||||
```
|
-->
|
||||||
|
输出类似以下内容：
|
||||||
<!--
|
|
||||||
There is not a single command to check on the output of all jobs at once,
|
```
|
||||||
but looping over all the pods is pretty easy:
|
NAME COMPLETIONS DURATION AGE
|
||||||
-->
|
process-item-apple 1/1 14s 20s
|
||||||
没有一个命令可以一次检查所有作业的输出，但是循环遍历所有 pod 非常简单：
|
process-item-banana 1/1 12s 20s
|
||||||
|
process-item-cherry 1/1 12s 20s
|
||||||
```shell
|
```
|
||||||
$ for p in $(kubectl get pods -l jobgroup=jobexample -o name)
|
|
||||||
do
|
<!--
|
||||||
kubectl logs $p
|
Here we use the `-l` option to select all jobs that are part of this
|
||||||
done
|
group of jobs. (There might be other unrelated jobs in the system that we
|
||||||
Processing item apple
|
do not care to see.)
|
||||||
Processing item banana
|
-->
|
||||||
Processing item cherry
|
在这里，我们使用 `-l` 选项选择属于这组作业的所有作业。(系统中可能还有其他不相关的工作，我们不想看到。)
|
||||||
```
|
|
||||||
|
<!--
|
||||||
<!--
|
We can check on the pods as well using the same label selector:
|
||||||
## Multiple Template Parameters
|
-->
|
||||||
-->
|
使用同样的标签选择器，我们还可以检查 pods：
|
||||||
|
|
||||||
## 多个模板参数
|
```shell
|
||||||
|
kubectl get pods -l jobgroup=jobexample
|
||||||
<!--
|
```
|
||||||
In the first example, each instance of the template had one parameter, and that parameter was also
|
|
||||||
used as a label. However label keys are limited in [what characters they can
|
<!--
|
||||||
contain](/docs/concepts/overview/working-with-objects/labels/#syntax-and-character-set).
|
The output is similar to this:
|
||||||
-->
|
-->
|
||||||
在第一个示例中，模板的每个实例都有一个参数，该参数也用作标签。
|
输出类似以下内容：
|
||||||
但是标签的键名在[可包含的字符](/docs/concepts/overview/working-with-objects/labels/#syntax-and-character-set)方面有一定的约束。
|
|
||||||
|
```
|
||||||
<!--
|
NAME READY STATUS RESTARTS AGE
|
||||||
This slightly more complex example uses the jinja2 template language to generate our objects.
|
process-item-apple-kixwv 0/1 Completed 0 4m
|
||||||
We will use a one-line python script to convert the template to a file.
|
process-item-banana-wrsf7 0/1 Completed 0 4m
|
||||||
-->
|
process-item-cherry-dnfu9 0/1 Completed 0 4m
|
||||||
这个稍微复杂一点的示例使用 jinja2 板语言来生成我们的对象。
|
```
|
||||||
我们将使用一行 python 脚本将模板转换为文件。
|
|
||||||
|
<!--
|
||||||
<!--
|
We can use this single command to check on the output of all jobs at once:
|
||||||
First, copy and paste the following template of a Job object, into a file called `job.yaml.jinja2`:
|
-->
|
||||||
-->
|
我们可以使用以下操作命令一次性地检查所有作业的输出：
|
||||||
首先，粘贴作业对象的以下模板到一个名为 `job.yaml.jinja2` 的文件中：
|
|
||||||
|
```shell
|
||||||
```liquid
|
kubectl logs -f -l jobgroup=jobexample
|
||||||
{%- set params = [{ "name": "apple", "url": "http://www.orangepippin.com/apples", },
|
```
|
||||||
{ "name": "banana", "url": "https://en.wikipedia.org/wiki/Banana", },
|
|
||||||
{ "name": "raspberry", "url": "https://www.raspberrypi.org/" }]
|
<!--
|
||||||
%}
|
The output is:
|
||||||
{%- for p in params %}
|
-->
|
||||||
{%- set name = p["name"] %}
|
输出内容为：
|
||||||
{%- set url = p["url"] %}
|
|
||||||
apiVersion: batch/v1
|
```
|
||||||
kind: Job
|
Processing item apple
|
||||||
metadata:
|
Processing item banana
|
||||||
name: jobexample-{{ name }}
|
Processing item cherry
|
||||||
labels:
|
```
|
||||||
jobgroup: jobexample
|
|
||||||
spec:
|
<!--
|
||||||
template:
|
## Multiple Template Parameters
|
||||||
metadata:
|
-->
|
||||||
name: jobexample
|
|
||||||
labels:
|
## 多个模板参数
|
||||||
jobgroup: jobexample
|
|
||||||
spec:
|
<!--
|
||||||
containers:
|
In the first example, each instance of the template had one parameter, and that parameter was also
|
||||||
- name: c
|
used as a label. However label keys are limited in [what characters they can
|
||||||
image: busybox
|
contain](/docs/concepts/overview/working-with-objects/labels/#syntax-and-character-set).
|
||||||
command: ["sh", "-c", "echo Processing URL {{ url }} && sleep 5"]
|
-->
|
||||||
restartPolicy: Never
|
在第一个示例中，模板的每个实例都有一个参数，该参数也用作标签。
|
||||||
---
|
但是标签的键名在[可包含的字符](/docs/concepts/overview/working-with-objects/labels/#syntax-and-character-set)方面有一定的约束。
|
||||||
{%- endfor %}
|
|
||||||
|
<!--
|
||||||
```
|
This slightly more complex example uses the jinja2 template language to generate our objects.
|
||||||
|
We will use a one-line python script to convert the template to a file.
|
||||||
<!--
|
-->
|
||||||
The above template defines parameters for each job object using a list of
|
这个稍微复杂一点的示例使用 jinja2 模板语言来生成我们的对象。
|
||||||
python dicts (lines 1-4). Then a for loop emits one job yaml object
|
我们将使用一行 python 脚本将模板转换为文件。
|
||||||
for each set of parameters (remaining lines).
|
|
||||||
We take advantage of the fact that multiple yaml documents can be concatenated
|
<!--
|
||||||
with the `---` separator (second to last line).
|
First, copy and paste the following template of a Job object, into a file called `job.yaml.jinja2`:
|
||||||
.) We can pipe the output directly to kubectl to
|
-->
|
||||||
create the objects.
|
首先，粘贴 Job 对象的以下模板到一个名为 `job.yaml.jinja2` 的文件中：
|
||||||
-->
|
|
||||||
上面的模板使用 python dicts 列表（第1-4行）定义每个作业对象的参数。
|
```liquid
|
||||||
然后 for 循环为每组参数（剩余行）生成一个作业 yaml 对象。
|
{%- set params = [{ "name": "apple", "url": "https://www.orangepippin.com/varieties/apples", },
|
||||||
我们利用了多个 yaml 文档可以与 `---` 分隔符连接的事实（倒数第二行）。
|
{ "name": "banana", "url": "https://en.wikipedia.org/wiki/Banana", },
|
||||||
我们可以将输出直接传递给 kubectl 来创建对象。
|
{ "name": "raspberry", "url": "https://www.raspberrypi.org/" }]
|
||||||
|
%}
|
||||||
<!--
|
{%- for p in params %}
|
||||||
You will need the jinja2 package if you do not already have it: `pip install --user jinja2`.
|
{%- set name = p["name"] %}
|
||||||
Now, use this one-line python program to expand the template:
|
{%- set url = p["url"] %}
|
||||||
-->
|
apiVersion: batch/v1
|
||||||
如果您还没有 jinja2 包则需要安装它: `pip install --user jinja2`。
|
kind: Job
|
||||||
现在，使用这个一行 python 程序来展开模板:
|
metadata:
|
||||||
|
name: jobexample-{{ name }}
|
||||||
```shell
|
labels:
|
||||||
alias render_template='python -c "from jinja2 import Template; import sys; print(Template(sys.stdin.read()).render());"'
|
jobgroup: jobexample
|
||||||
```
|
spec:
|
||||||
|
template:
|
||||||
|
metadata:
|
||||||
<!--
|
name: jobexample
|
||||||
The output can be saved to a file, like this:
|
labels:
|
||||||
-->
|
jobgroup: jobexample
|
||||||
输出可以保存到一个文件，像这样：
|
spec:
|
||||||
|
containers:
|
||||||
```shell
|
- name: c
|
||||||
cat job.yaml.jinja2 | render_template > jobs.yaml
|
image: busybox
|
||||||
```
|
command: ["sh", "-c", "echo Processing URL {{ url }} && sleep 5"]
|
||||||
|
restartPolicy: Never
|
||||||
<!--
|
---
|
||||||
Or sent directly to kubectl, like this:
|
{%- endfor %}
|
||||||
-->
|
|
||||||
或直接发送到 kubectl，如下所示：
|
```
|
||||||
|
|
||||||
```shell
|
<!--
|
||||||
cat job.yaml.jinja2 | render_template | kubectl create -f -
|
The above template defines parameters for each job object using a list of
|
||||||
```
|
python dicts (lines 1-4). Then a for loop emits one job yaml object
|
||||||
|
for each set of parameters (remaining lines).
|
||||||
<!--
|
We take advantage of the fact that multiple yaml documents can be concatenated
|
||||||
## Alternatives
|
with the `---` separator (second to last line).
|
||||||
-->
|
.) We can pipe the output directly to kubectl to
|
||||||
## 替代方案
|
create the objects.
|
||||||
|
-->
|
||||||
<!--
|
上面的模板使用 python 字典列表（第 1-4 行）定义每个作业对象的参数。
|
||||||
If you have a large number of job objects, you may find that:
|
然后使用 for 循环为每组参数（剩余行）生成一个作业 yaml 对象。
|
||||||
-->
|
我们利用了多个 yaml 文档可以与 `---` 分隔符连接的事实（倒数第二行）。
|
||||||
如果您有大量作业对象，您可能会发现：
|
我们可以将输出直接传递给 kubectl 来创建对象。
|
||||||
|
|
||||||
<!--
|
<!--
|
||||||
- Even using labels, managing so many Job objects is cumbersome.
|
You will need the jinja2 package if you do not already have it: `pip install --user jinja2`.
|
||||||
- You exceed resource quota when creating all the Jobs at once,
|
Now, use this one-line python program to expand the template:
|
||||||
and do not want to wait to create them incrementally.
|
-->
|
||||||
- Very large numbers of jobs created at once overload the
|
如果您还没有 jinja2 包则需要安装它: `pip install --user jinja2`。
|
||||||
Kubernetes apiserver, controller, or scheduler.
|
现在，使用这个一行 python 程序来展开模板:
|
||||||
-->
|
|
||||||
|
```shell
|
||||||
- 即使使用标签，管理这么多作业对象也很麻烦。
|
alias render_template='python -c "from jinja2 import Template; import sys; print(Template(sys.stdin.read()).render());"'
|
||||||
- 在一次创建所有作业时，您超过了资源配额，可是您也不希望以递增方式创建作业并等待其完成。
|
```
|
||||||
- 同时创建的大量作业会使 Kubernetes apiserver、控制器或调度程序过载。
|
|
||||||
|
|
||||||
|
<!--
|
||||||
<!--
|
The output can be saved to a file, like this:
|
||||||
In this case, you can consider one of the
|
-->
|
||||||
other [job patterns](/docs/concepts/jobs/run-to-completion-finite-workloads/#job-patterns).
|
输出可以保存到一个文件，像这样：
|
||||||
-->
|
|
||||||
在这种情况下，您可以考虑
|
```shell
|
||||||
其他[工作模式](/docs/concepts/jobs/run-to-completion-finite-workloads/#job-patterns)。
|
cat job.yaml.jinja2 | render_template > jobs.yaml
|
||||||
|
```
|
||||||
{{% /capture %}}
|
|
||||||
|
<!--
|
||||||
|
Or sent directly to kubectl, like this:
|
||||||
|
-->
|
||||||
|
或直接发送到 kubectl，如下所示：
|
||||||
|
|
||||||
|
```shell
|
||||||
|
cat job.yaml.jinja2 | render_template | kubectl apply -f -
|
||||||
|
```
|
||||||
|
|
||||||
|
<!--
|
||||||
|
## Alternatives
|
||||||
|
-->
|
||||||
|
## 替代方案
|
||||||
|
|
||||||
|
<!--
|
||||||
|
If you have a large number of job objects, you may find that:
|
||||||
|
-->
|
||||||
|
如果您有大量作业对象，您可能会发现：
|
||||||
|
|
||||||
|
<!--
|
||||||
|
- Even using labels, managing so many Job objects is cumbersome.
|
||||||
|
- You exceed resource quota when creating all the Jobs at once,
|
||||||
|
and do not want to wait to create them incrementally.
|
||||||
|
- Very large numbers of jobs created at once overload the
|
||||||
|
Kubernetes apiserver, controller, or scheduler.
|
||||||
|
-->
|
||||||
|
|
||||||
|
- 即使使用标签，管理这么多 Job 对象也很麻烦。
|
||||||
|
- 在一次创建所有作业时，您超过了资源配额，可是您也不希望以递增方式创建 Job 并等待其完成。
|
||||||
|
- 同时创建大量作业会使 Kubernetes apiserver、控制器或者调度器负压过大。
|
||||||
|
|
||||||
|
|
||||||
|
<!--
|
||||||
|
In this case, you can consider one of the
|
||||||
|
other [job patterns](/docs/concepts/jobs/run-to-completion-finite-workloads/#job-patterns).
|
||||||
|
-->
|
||||||
|
在这种情况下，您可以考虑其他的[作业模式](/docs/concepts/jobs/run-to-completion-finite-workloads/#job-patterns)。
|
||||||
|
|
||||||
|
{{% /capture %}}
|
||||||
|
|||||||
Reference in New Issue
Block a user