[FLINK-21440][doc] translate content.zh/docs/try-flink/table_api.md and correct spelling mistake content/docs/try-flink/table_api.md #14985
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PrivateLi
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Feb 22, 2021
PrivateLi
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- translate Real Time Reporting with the Table API doc to Chinese
- Correct Real Time Reporting with the Table API doc allong with spelling mistake to along with
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Thanks for your contribution @PrivateLi ,left some comment.
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| Apache Flink offers a Table API as a unified, relational API for batch and stream processing, i.e., queries are executed with the same semantics on unbounded, real-time streams or bounded, batch data sets and produce the same results. | ||
| The Table API in Flink is commonly used to ease the definition of data analytics, data pipelining, and ETL applications. | ||
| Apache Flink 提供了 Table API 作为统一的相关 API，用于批处理和流处理，即：对无边界的实时流或有约束的批处理数据集以相同的语义执行查询，并产生相同的结果。Flink 中的 Table API 通常用于简化数据分析，数据管道和ETL应用程序的定义。 |
| Apache Flink 提供了 Table API 作为统一的相关 API，用于批处理和流处理，即：对无边界的实时流或有约束的批处理数据集以相同的语义执行查询，并产生相同的结果。Flink 中的 Table API 通常用于简化数据分析，数据管道和ETL应用程序的定义。 | ||
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| ## What Will You Be Building? | ||
| ## 您要搭建一个什么系统 |
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https://cwiki.apache.org/confluence/display/FLINK/Flink+Translation+Specifications 第6点，用“你” 而不用“您”，下面也一样。
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| If you get stuck, check out the [community support resources](https://flink.apache.org/community.html). | ||
| In particular, Apache Flink's [user mailing list](https://flink.apache.org/community.html#mailing-lists) consistently ranks as one of the most active of any Apache project and a great way to get help quickly. | ||
| 如果遇到困难，可以参考[社区支持资源](https://flink.apache.org/community.html)。 当然也可以在邮件列表提问，Flink 的[用户邮件列表](https://flink.apache.org/community.html#mailing-lists)一直被评为所有Apache项目中最活跃的一个，这也是快速获得帮助的好方法。 |
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| In this tutorial, you will learn how to build a real-time dashboard to track financial transactions by account. | ||
| The pipeline will read data from Kafka and write the results to MySQL visualized via Grafana. | ||
| 在本教程中，您将学习如何构建实时仪表板以按帐户跟踪财务交易。流程将从Kafka读取数据，并将结果写入通过 Grafana 可视化的 MySQL。 |
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将结果写入 MySQL 并通过 Grafana 提供可视化。
---这样是不是通顺一点
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| One of Flink's unique properties is that it provides consistent semantics across batch and streaming. | ||
| This means you can develop and test applications in batch mode on static datasets, and deploy to production as streaming applications. | ||
| Flink 的独特属性之一是，它在批处理和流传输之间提供一致的语义。这意味着您可以在静态数据集上以批处理模式开发和测试应用程序，并作为流应用程序部署到生产中。 |
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Flink 的特色之一是，它在批处理和流处理之间提供一致性的语义。
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| 现在，有了 Job 设置的框架，您就可以添加一些业务逻辑。目的是建立一个报告，显示每个帐户在一天中每个小时的总支出。这意味着时间戳列需要从毫秒舍入到小时粒度。 | ||
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| Flink supports developing relational applications in pure [SQL]({{< ref "docs/dev/table/sql/overview" >}}) or using the [Table API]({{< ref "docs/dev/table/tableApi" >}}). |
| The Table API is a fluent DSL inspired by SQL, that can be written in Python, Java, or Scala and supports strong IDE integration. | ||
| Just like a SQL query, Table programs can select the required fields and group by your keys. | ||
| These features, allong with [built-in functions]({{< ref "docs/dev/table/functions/systemFunctions" >}}) like `floor` and `sum`, you can write this report. | ||
| Flink支持使用纯[SQL]({{< ref "docs/dev/table/sql/overview" >}})或使用[Table API]({{< ref "docs/dev/table/tableApi" >}})。Table API 是受 SQL 启发的流畅 DSL，可以用 Python、Java或 Scala 编写，并支持强大的 IDE 集成。就像 SQL 查询一样，Table 程序可以选择必填字段并按键进行分组。这些特点，结合[内置函数] ({{< ref "docs/dev/table/functions/systemFunctions" >}}) ，如floor和sum，可以编写此报告。 |
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Flink支持使用纯[SQL]({{< ref "docs/dev/table/sql/overview" >}})或使用[Table API]({{< ref "docs/dev/table/tableApi" >}})来开发纯关系型应用。
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利用这些特性，并结合[内置函数] ({{< ref "docs/dev/table/functions/systemFunctions" >}}) ，如 floor 和 sum，就可以编写 report 函数了。
| In a batch context, windows offer a convenient API for grouping records by a timestamp attribute. | ||
| 基于时间的聚合是唯一的，因为与其它属性相反，时间通常在连续流应用程序中向前移动。与用户自定义函数 `floor` 不同，窗口函数是[内部函数](https://en.wikipedia.org/wiki/Intrinsic_function)，它允许运行时应用额外的优化。在批处理环境中，窗口函数提供了一种用于按 timestamp 属性对记录进行分组方便的API。 | ||
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| Running the test with this implementation will also pass. |
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| Now with the skeleton of a Job set-up, you are ready to add some business logic. | ||
| The goal is to build a report that shows the total spend for each account across each hour of the day. | ||
| This means the timestamp column needs be be rounded down from millisecond to hour granularity. |
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这里有个typo，应该是 ‘to be’ 吧，改下英文原文。
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update the pull request based on feedback |
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