[zh]Resync tasks files[10]

content/zh/docs/tasks/job/coarse-parallel-processing-work-queue.md

@@ -2,7 +2,7 @@
 title: 使用工作队列进行粗粒度并行处理
 min-kubernetes-server-version: v1.8
 content_type: task
-weight: 30
+weight: 20
 ---
 
 <!--
@@ -10,7 +10,7 @@ weight: 30
 title: Coarse Parallel Processing Using a Work Queue
 min-kubernetes-server-version: v1.8
 content_type: task
-weight: 30
+weight: 20
 ---
 -->
 
@@ -28,7 +28,7 @@ Here is an overview of the steps in this example:
 1. **Start a message queue service.**  In this example, we use RabbitMQ, but you could use another
   one.  In practice you would set up a message queue service once and reuse it for many jobs.
 1. **Create a queue, and fill it with messages.**  Each message represents one task to be done.  In
-  this example, a message is just an integer that we will do a lengthy computation on.
+   this example, a message is an integer that we will do a lengthy computation on.
 1. **Start a Job that works on tasks from the queue**.  The Job starts several pods.  Each pod takes
   one task from the message queue, processes it, and repeats until the end of the queue is reached.
 -->
@@ -63,7 +63,7 @@ non-parallel, use of [Job](/docs/concepts/jobs/run-to-completion-finite-workload
 <!--
 ## Starting a message queue service
 
-This example uses RabbitMQ, but it should be easy to adapt to another AMQP-type message service.
+This example uses RabbitMQ, however, you can adapt the example to use another AMQP-type message service.
 
 In practice you could set up a message queue service once in a
 cluster and reuse it for many jobs, as well as for long-running services.
@@ -72,7 +72,7 @@ Start RabbitMQ as follows:
 -->
 ## 启动消息队列服务
 
-本例使用了 RabbitMQ，使用其他 AMQP 类型的消息服务应该比较容易。
+本例使用了 RabbitMQ，但你可以更改该示例，使用其他 AMQP 类型的消息服务。
 
 在实际工作中，在集群中一次性部署某个消息队列服务，之后在很多 Job 中复用，包括需要长期运行的服务。
 
@@ -225,17 +225,17 @@ root@temp-loe07:/#
 
 <!--
 In the last command, the `amqp-consume` tool takes one message (`-c 1`)
-from the queue, and passes that message to the standard input of an arbitrary command.  In this case, the program `cat` is just printing
-out what it gets on the standard input, and the echo is just to add a carriage
+from the queue, and passes that message to the standard input of an arbitrary command.  In this case, the program `cat` prints out the characters read from standard input, and the echo adds a carriage
 return so the example is readable.
 -->
 
-最后一个命令中， `amqp-consume` 工具从队列中取走了一个消息，并把该消息传递给了随机命令的标准输出。在这种情况下，`cat` 只会打印它从标准输入或得的内容，echo 只会添加回车符以便示例可读。
+最后一个命令中， `amqp-consume` 工具从队列中取走了一个消息，并把该消息传递给了随机命令的标准输出。
+在这种情况下，`cat` 会打印它从标准输入中读取的字符，echo 会添加回车符以便示例可读。
 
 <!--
 ## Filling the Queue with tasks
 
-Now lets fill the queue with some "tasks".  In our example, our tasks are just strings to be
+Now let's fill the queue with some "tasks".  In our example, our tasks are strings to be
 printed.
 
 In a practice, the content of the messages might be:

content/zh/docs/tasks/job/fine-parallel-processing-work-queue.md

@@ -2,12 +2,12 @@
 title: 使用工作队列进行精细的并行处理
 content_type: task
 min-kubernetes-server-version: v1.8
-weight: 40
+weight: 30
 ---
 <!--
 title: Fine Parallel Processing Using a Work Queue
 content_type: task
-weight: 40
+weight: 30
 min-kubernetes-server-version: v1.8
 -->
 
@@ -45,10 +45,10 @@ Here is an overview of the steps in this example:
 
 <!--
 1. **Create a queue, and fill it with messages.**  Each message represents one task to be done.  In
-  this example, a message is just an integer that we will do a lengthy computation on.
+   this example, a message is an integer that we will do a lengthy computation on.
 -->
 2. **创建一个队列，然后向其中填充消息。** 每个消息表示一个将要被处理的工作任务。
-   在这个例子中，消息只是一个我们将用于进行长度计算的整数。
+   在这个例子中，消息是一个我们将用于进行长度计算的整数。
 
 <!--
 1. **Start a Job that works on tasks from the queue**.  The Job starts several pods.  Each pod takes
@@ -97,14 +97,14 @@ You could also download the following files directly:
 <!--
 ## Filling the Queue with tasks
 
-Now let's fill the queue with some "tasks".  In our example, our tasks are just strings to be
+Now let's fill the queue with some "tasks".  In our example, our tasks are strings to be
 printed.
 
 Start a temporary interactive pod for running the Redis CLI.
 -->
 ## 使用任务填充队列
 
-现在，让我们往队列里添加一些“任务”。在这个例子中，我们的任务只是一些将被打印出来的字符串。
+现在，让我们往队列里添加一些“任务”。在这个例子中，我们的任务是一些将被打印出来的字符串。
 
 启动一个临时的可交互的 pod 用于运行 Redis 命令行界面。
 

content/zh/docs/tasks/job/parallel-processing-expansion.md

@@ -2,13 +2,13 @@
 title: 使用展开的方式进行并行处理
 content_type: task
 min-kubernetes-server-version: v1.8
-weight: 20
+weight: 50
 ---
 <!--
 title: Parallel Processing using Expansions
 content_type: task
 min-kubernetes-server-version: v1.8
-weight: 20
+weight: 50
 -->
 
 <!-- overview -->
@@ -19,7 +19,7 @@ based on a common template. You can use this approach to process batches of work
 parallel.
 
 For this example there are only three items: _apple_, _banana_, and _cherry_.
-The sample Jobs process each item simply by printing a string then pausing.
+The sample Jobs process each item by printing a string then pausing.
 
 See [using Jobs in real workloads](#using-jobs-in-real-workloads) to learn about how
 this pattern fits more realistic use cases.
@@ -29,7 +29,8 @@ this pattern fits more realistic use cases.
 你可以用这种方法来并行执行批处理任务。
 
 在本任务示例中，只有三个工作条目：_apple_、_banana_ 和 _cherry_。
-示例任务处理每个条目时仅仅是打印一个字符串之后结束。
+示例任务处理每个条目时打印一个字符串之后结束。
+
 参考[在真实负载中使用 Job](#using-jobs-in-real-workloads)了解更适用于真实使用场景的模式。
 
 ## {{% heading "prerequisites" %}}