[GitHub] [flink] TisonKun commented on a change in pull request #9299: [FLINK-13405][docs-zh] Translate "Basic API Concepts" page into Chinese
TisonKun commented on a change in pull request #9299: [FLINK-13405][docs-zh]
Translate "Basic API Concepts" page into Chinese
URL: https://github.com/apache/flink/pull/9299#discussion_r316478746
##
File path: docs/dev/api_concepts.zh.md
##
@@ -24,68 +24,46 @@ specific language governing permissions and limitations
under the License.
-->
-Flink programs are regular programs that implement transformations on
distributed collections
-(e.g., filtering, mapping, updating state, joining, grouping, defining
windows, aggregating).
-Collections are initially created from sources (e.g., by reading from files,
kafka topics, or from local, in-memory
-collections). Results are returned via sinks, which may for example write the
data to
-(distributed) files, or to standard output (for example, the command line
terminal).
-Flink programs run in a variety of contexts, standalone, or embedded in other
programs.
-The execution can happen in a local JVM, or on clusters of many machines.
-
-Depending on the type of data sources, i.e. bounded or unbounded sources, you
would either
-write a batch program or a streaming program where the DataSet API is used for
batch
-and the DataStream API is used for streaming. This guide will introduce the
basic concepts
-that are common to both APIs but please see our
-[Streaming Guide]({{ site.baseurl }}/dev/datastream_api.html) and
-[Batch Guide]({{ site.baseurl }}/dev/batch/index.html) for concrete
information about
-writing programs with each API.
-
-**NOTE:** When showing actual examples of how the APIs can be used we will use
-`StreamingExecutionEnvironment` and the `DataStream` API. The concepts are
exactly the same
-in the `DataSet` API, just replace by `ExecutionEnvironment` and `DataSet`.
+Flink
程序是实现了分布式集合转换（例如过滤、映射、更新状态、join、分组、定义窗口、聚合）的规范化程序。集合初始创建自数据源（例如读取文件、kafka
主题，或本地内存中的集合）。结果通过 sink 返回，例如，它可以将数据写入（分布式）文件，或标准输出（例如命令行终端）。Flink
程序可以在多种环境中运行，独立运行或嵌入到其他程序中。可以在本地 JVM 中执行，也可以在多台机器的集群上执行。
+
+针对有界和无界两种数据源类型，你可以使用 DataSet API 来编写批处理程序或使用 DataStream API
来编写流处理程序。本篇指南将介绍这两种 API 通用的基本概念，使用每种 API 编写程序的具体信息请查阅
+[流处理指南]({{ site.baseurl }}/zh/dev/datastream_api.html) 和
+[批处理指南]({{ site.baseurl }}/zh/dev/batch/index.html)。
+
+**请注意：** 当展示如何使用 API 的实际示例时我们使用 `StreamingExecutionEnvironment` 和 `DataStream
API`。对于批处理，将他们替换为 `ExecutionEnvironment` 和 `DataSet API` 即可，概念是完全相同的。
* This will be replaced by the TOC
{:toc}
-DataSet and DataStream
+DataSet 和 DataStream
--
-Flink has the special classes `DataSet` and `DataStream` to represent data in
a program. You
-can think of them as immutable collections of data that can contain
duplicates. In the case
-of `DataSet` the data is finite while for a `DataStream` the number of
elements can be unbounded.
+Flink 用特有的 `DataSet` 和 `DataStream` 类来表示程序中的数据。你可以将他们视为包含重复项的不可变数据集合。对于
`DataSet`，数据是有限的，而对于 `DataStream`，元素的数量可以是无限的。
-These collections differ from regular Java collections in some key ways.
First, they
-are immutable, meaning that once they are created you cannot add or remove
elements. You can also
-not simply inspect the elements inside.
+这些集合与标准的 Java 集合有一些关键的区别。首先它们是不可变的，也就是说它们一旦被创建你就不能添加或删除元素了。你也不能简单地检查它们内部的元素。
-A collection is initially created by adding a source in a Flink program and
new collections are
-derived from these by transforming them using API methods such as `map`,
`filter` and so on.
+在 Flink 程序中，集合最初通过添加数据源来创建，通过使用 API 的诸如 `map`、`filter` 等方法对数据源进行转换从而派生新的集合。
-Anatomy of a Flink Program
+剖析一个 Flink 程序
--
-Flink programs look like regular programs that transform collections of data.
-Each program consists of the same basic parts:
+Flink 程序看起来像是转换数据集合的规范化程序。每个程序由一些基本的部分组成：
-1. Obtain an `execution environment`,
-2. Load/create the initial data,
-3. Specify transformations on this data,
-4. Specify where to put the results of your computations,
-5. Trigger the program execution
+1. 获取执行环境 `execution environment`，
Review comment:
可以把 \`execution environment\` 用括号括起来或者直接去掉。
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[GitHub] [flink] TisonKun commented on a change in pull request #9299: [FLINK-13405][docs-zh] Translate "Basic API Concepts" page into Chinese
TisonKun commented on a change in pull request #9299: [FLINK-13405][docs-zh]
Translate "Basic API Concepts" page into Chinese
URL: https://github.com/apache/flink/pull/9299#discussion_r316478163
##
File path: docs/dev/api_concepts.zh.md
##
@@ -24,68 +24,46 @@ specific language governing permissions and limitations
under the License.
-->
-Flink programs are regular programs that implement transformations on
distributed collections
-(e.g., filtering, mapping, updating state, joining, grouping, defining
windows, aggregating).
-Collections are initially created from sources (e.g., by reading from files,
kafka topics, or from local, in-memory
-collections). Results are returned via sinks, which may for example write the
data to
-(distributed) files, or to standard output (for example, the command line
terminal).
-Flink programs run in a variety of contexts, standalone, or embedded in other
programs.
-The execution can happen in a local JVM, or on clusters of many machines.
-
-Depending on the type of data sources, i.e. bounded or unbounded sources, you
would either
-write a batch program or a streaming program where the DataSet API is used for
batch
-and the DataStream API is used for streaming. This guide will introduce the
basic concepts
-that are common to both APIs but please see our
-[Streaming Guide]({{ site.baseurl }}/dev/datastream_api.html) and
-[Batch Guide]({{ site.baseurl }}/dev/batch/index.html) for concrete
information about
-writing programs with each API.
-
-**NOTE:** When showing actual examples of how the APIs can be used we will use
-`StreamingExecutionEnvironment` and the `DataStream` API. The concepts are
exactly the same
-in the `DataSet` API, just replace by `ExecutionEnvironment` and `DataSet`.
+Flink
程序是实现了分布式集合转换（例如过滤、映射、更新状态、join、分组、定义窗口、聚合）的规范化程序。集合初始创建自数据源（例如读取文件、kafka
主题，或本地内存中的集合）。结果通过 sink 返回，例如，它可以将数据写入（分布式）文件，或标准输出（例如命令行终端）。Flink
程序可以在多种环境中运行，独立运行或嵌入到其他程序中。可以在本地 JVM 中执行，也可以在多台机器的集群上执行。
+
+针对有界和无界两种数据源类型，你可以使用 DataSet API 来编写批处理程序或使用 DataStream API
来编写流处理程序。本篇指南将介绍这两种 API 通用的基本概念，使用每种 API 编写程序的具体信息请查阅
Review comment:
`使用每种 API 编写程序的具体信息请查阅` 去掉 `每种` 或者说重新写作 `具体使用 API 编写程序的方法请查阅` 或通顺一点。
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[GitHub] [flink] TisonKun commented on a change in pull request #9299: [FLINK-13405][docs-zh] Translate "Basic API Concepts" page into Chinese
TisonKun commented on a change in pull request #9299: [FLINK-13405][docs-zh]
Translate "Basic API Concepts" page into Chinese
URL: https://github.com/apache/flink/pull/9299#discussion_r316477628
##
File path: docs/dev/api_concepts.zh.md
##
@@ -24,68 +24,46 @@ specific language governing permissions and limitations
under the License.
-->
-Flink programs are regular programs that implement transformations on
distributed collections
-(e.g., filtering, mapping, updating state, joining, grouping, defining
windows, aggregating).
-Collections are initially created from sources (e.g., by reading from files,
kafka topics, or from local, in-memory
-collections). Results are returned via sinks, which may for example write the
data to
-(distributed) files, or to standard output (for example, the command line
terminal).
-Flink programs run in a variety of contexts, standalone, or embedded in other
programs.
-The execution can happen in a local JVM, or on clusters of many machines.
-
-Depending on the type of data sources, i.e. bounded or unbounded sources, you
would either
-write a batch program or a streaming program where the DataSet API is used for
batch
-and the DataStream API is used for streaming. This guide will introduce the
basic concepts
-that are common to both APIs but please see our
-[Streaming Guide]({{ site.baseurl }}/dev/datastream_api.html) and
-[Batch Guide]({{ site.baseurl }}/dev/batch/index.html) for concrete
information about
-writing programs with each API.
-
-**NOTE:** When showing actual examples of how the APIs can be used we will use
-`StreamingExecutionEnvironment` and the `DataStream` API. The concepts are
exactly the same
-in the `DataSet` API, just replace by `ExecutionEnvironment` and `DataSet`.
+Flink
程序是实现了分布式集合转换（例如过滤、映射、更新状态、join、分组、定义窗口、聚合）的规范化程序。集合初始创建自数据源（例如读取文件、kafka
主题，或本地内存中的集合）。结果通过 sink 返回，例如，它可以将数据写入（分布式）文件，或标准输出（例如命令行终端）。Flink
程序可以在多种环境中运行，独立运行或嵌入到其他程序中。可以在本地 JVM 中执行，也可以在多台机器的集群上执行。
Review comment:
社区有过一次讨论[1]，建议都不翻译。
[1]
https://lists.apache.org/x/thread.html/8a041adc57c36b2228cdc7394a0442db61a39e82c382e598f8842805@%3Cuser-zh.flink.apache.org%3E
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