This is an automated email from the ASF dual-hosted git repository. tison pushed a commit to branch doc-portal in repository https://gitbox.apache.org/repos/asf/incubator-streampark-website.git
commit 8b937b4f84a0c56d505c10c62efdc054b7a50356 Author: tison <[email protected]> AuthorDate: Thu Apr 25 09:11:57 2024 +0800 Revise Document portal Signed-off-by: tison <[email protected]> --- docs/intro.md | 24 +++++++++---------- .../current/intro.md | 27 ++++++++++------------ package.json | 3 ++- 3 files changed, 25 insertions(+), 29 deletions(-) diff --git a/docs/intro.md b/docs/intro.md index 70c8135d..d5d5bad8 100644 --- a/docs/intro.md +++ b/docs/intro.md @@ -6,23 +6,22 @@ sidebar_position: 1 # Apache StreamPark™ -make stream processing easier!!! - -> An amazing framework makes stream processing easier. +Make stream processing easier! ## 🚀 What is Apache StreamPark™ `Apache StreamPark` is an easy-to-use stream processing application development framework and one-stop stream processing operation platform, Aimed at ease building and managing streaming applications, StreamPark provides scaffolding for writing streaming process logics with Apache Flink and Apache Spark. -StreamPark also provides a professional task management including task development, scheduling, interactive query, deployment, operation, maintenance, etc. - +StreamPark also provides a professional task management including task development, scheduling, interactive query, deployment, operation, maintenance, etc. ## Why Apache StreamPark™ -Apache Flink and Apache Spark are widely used as the next generation of big data streaming computing engines. Based on a bench of excellent experiences combined with best practices, we extracted the task deployment and runtime parameters into the configuration files. In this way, an easy-to-use RuntimeContext with out-of-the-box connectors would bring easier and more efficient task development experience. It reduces the learning cost and development barriers, hence developers can focus [...] +Apache Flink and Apache Spark are widely used as the next generation of big data streaming computing engines. Based on a bench of excellent experiences combined with best practices, we extracted the task deployment and runtime parameters into the configuration files. In this way, an easy-to-use `RuntimeContext` with out-of-the-box connectors would bring easier and more efficient task development experience. It reduces the learning cost and development barriers, hence developers can focus [...] + On the other hand, It can be challenge for enterprises to use Flink & Spark if there is no professional management platform for Flink & Spark tasks during the deployment phase. StreamPark provides such a professional task management platform, including task development, scheduling, interactive query, deployment, operation, maintenance, etc. ## 🎉 Features + * Apache Flink & Apache Spark application development scaffold * Support multiple versions of Flink & Spark * Wide range of out-of-the-box connectors @@ -39,16 +38,15 @@ The overall architecture of Apache StreamPark is shown in the following figure. ### 1️⃣ streampark-core The positioning of `streampark-core` is a framework uesd while developing, it focuses on coding development, regulates configuration files, and develops in the convention over configuration guide. -streampark-core provides a development-time RunTime Content and a series of out-of-the-box Connectors. Cumbersome operations are simplified by extending `DataStream-related` methods and integrating DataStream and `Flink sql` api . -development efficiency and development experience will be highly improved because users can focus on the business. + +`streampark-core` provides a development-time RunTime Content and a series of out-of-the-box Connectors. Cumbersome operations are simplified by extending DataStream-related methods and integrating DataStream and Flink SQL API. Development efficiency and development experience will be highly improved because users can focus on the business. ### 2️⃣ streampark-console -`streampark-console` is a comprehensive real-time `low code` data platform that can manage `Flink` tasks more convenient. +`streampark-console` is a comprehensive real-time Low Code data platform that can manage Flink tasks more convenient. It integrates the experience of many best practices and integrates many functions such as project compilation, release, -parameter configuration, startup, `savepoint`, `flame graph`, `Flink SQL`, monitoring, etc., -which greatly simplifies the daily operation of Flink tasks and maintenance. The ultimate goal is to create a one-stop big data platform, -which can provide a solution that integrates flow and batch, and integrates lake and warehouse. +parameter configuration, startup, savepoint, flame graph, Flink SQL, monitoring, etc., which greatly simplifies the daily operation of Flink tasks and maintenance. The ultimate goal is to create a one-stop big data platform, which can provide a solution that integrates flow and batch, and integrates lake and warehouse. + This platform uses technologies including but not limited to: * [Apache Flink](http://flink.apache.org) @@ -65,4 +63,4 @@ This platform uses technologies including but not limited to: * [Monaco Editor](https://microsoft.github.io/monaco-editor/) * ... -Thanks for the respect given by the above excellent open source projects and many unmentioned excellent open source projects +Thanks for the respect given by the above excellent open source projects and many unmentioned excellent open source projects! diff --git a/i18n/zh-CN/docusaurus-plugin-content-docs/current/intro.md b/i18n/zh-CN/docusaurus-plugin-content-docs/current/intro.md index a94fbd35..c57230fe 100644 --- a/i18n/zh-CN/docusaurus-plugin-content-docs/current/intro.md +++ b/i18n/zh-CN/docusaurus-plugin-content-docs/current/intro.md @@ -6,41 +6,38 @@ sidebar_position: 1 # Apache StreamPark™ -make stream processing easier!!! - -> 一个神奇的框架,让流处理更简单 +一个神奇的框架，让流处理更简单！ ## 🚀 什么是 Apache StreamPark™ -实时即未来,在实时处理流域 `Apache Spark` 和 `Apache Flink` 是一个伟大的进步,尤其是 `Apache Flink` 被普遍认为是下一代大数据流计算引擎, 我们在使用 `Flink` & `Spark` 时发现从编程模型, 启动配置到运维管理都有很多可以抽象共用的地方, 我们将一些好的经验固化下来并结合业内的最佳实践, 通过不断努力诞生了今天的框架 —— `StreamPark`, 项目的初衷是 —— 让流处理更简单, -使用 `StreamPark` 开发流处理作业, 可以极大降低学习成本和开发门槛, 让开发者只用关心最核心的业务,`StreamPark` 规范了项目的配置,鼓励函数式编程,定义了最佳的编程方式,提供了一系列开箱即用的`Connectors`,标准化了配置、开发、测试、部署、监控、运维的整个过程, 提供了`scala`和`java`两套 Api, 并且提供了一个一站式的流处理作业开发管理平台, 从流处理作业开发到上线全生命周期都 -做了支持, 是一个一站式的流处理计算平台. +实时即未来,在实时处理流域 Apache Spark 和 Apache Flink 是一个伟大的进步，尤其是 Flink 被普遍认为是下一代大数据流计算引擎。 +在使用 Flink 和 Spark 时，我们发现从编程模型, 启动配置到运维管理都有很多可以抽象共用的地方。于是，我们将一些好的经验固化下来并结合业内的最佳实践, 通过不断努力诞生了今天的框架：Apache StreamPark。项目的初衷是：让流处理更简单！ +使用 StreamPark 开发流处理作业, 可以极大降低学习成本和开发门槛, 让开发者只用关心最核心的业务，StreamPark 规范了项目的配置、鼓励函数式编程、定义了最佳的编程方式，提供了一系列开箱即用的连接器（Connector），标准化了配置、开发、测试、部署、监控、运维的整个过程，提供了 Scala 和 Java 两套接口，并且提供了一个一站式的流处理作业开发管理平台，从流处理作业开发到上线全生命周期都做了支持，是一个一站式的流处理计算平台。 ## 🎉 Features -* Apache Flink & Apache Spark 应用程序开发脚手架 -* 支持多个版本的 Flink & Spark -* 一系列开箱即用的connectors +* Flink 和 Spark 应用程序开发脚手架 +* 支持多个版本的 Flink 和 Spark +* 一系列开箱即用的连接器 * 一站式流处理运营平台 -* 支持catalog、olap、streaming-warehouse等 +* 支持 Catalog / OLAP / Streaming Warehouse 等场景 * ... ## 🏳🌈 组成部分 -`Apache StreamPark` 核心由`streampark-core` 和 `streampark-console` 组成 +Apache StreamPark 核心由 `streampark-core` 和 `streampark-console` 组成：  ### 1️⃣ streampark-core -`streampark-core` 定位是一个开发时框架,关注编码开发,规范了配置文件,按照约定优于配置的方式进行开发,提供了一个开发时 `RunTime Content`和一系列开箱即用的`Connector`,扩展了`DataStream`相关的方法,融合了`DataStream`和`Flink sql` api,简化繁琐的操作,聚焦业务本身,提高开发效率和开发体验 +`streampark-core` 定位是一个开发时框架，关注编码开发，规范了配置文件，按照约定优于配置的方式进行开发，提供了一个开发环境的 `RuntimeContext` 和一系列开箱即用的连接器，扩展了 `DataStream` 相关的方法，融合了 `DataStream` 和 `Flink SQL` API，简化繁琐的操作、聚焦业务本身，提高开发效率和开发体验。 ### 2️⃣ streampark-console -`streampark-console` 是一个综合实时数据平台,低代码(`Low Code`)平台,可以较好的管理`Flink`任务,集成了项目编译、发布、参数配置、启动、`savepoint`,火焰图(`flame graph`),`Flink SQL`, -监控等诸多功能于一体, 大大简化了 `Flink` 任务的日常操作和维护,融合了诸多最佳实践。旧时王谢堂前燕,飞入寻常百姓家,让大公司有能力研发使用的项目,现在人人可以使用, 其最终目标是打造成一个实时数仓,流批一体的一站式大数据解决方案,该平台使用但不仅限以下技术: +`streampark-console` 是一个综合实时数据平台、低代码平台，可以较好的管理 Flink 任务，集成了项目编译、发布、参数配置、启动、保存点、火焰图、Flink SQL 和 监控等诸多功能于一体，大大简化了 Flink 任务的日常操作和维护，融合了诸多最佳实践。旧时王谢堂前燕，飞入寻常百姓家。让大公司有能力研发使用的项目，现在人人可以使用，其最终目标是打造成一个实时数仓，流批一体的一站式大数据解决方案，该平台使用了（但不仅限）以下技术： * [Apache Flink](http://flink.apache.org) * [Apache Spark](http://spark.apache.org) @@ -56,4 +53,4 @@ make stream processing easier!!! * [Monaco Editor](https://microsoft.github.io/monaco-editor/) * ... -感谢以上优秀的开源项目和很多未提到的优秀开源项目,给予最大的 respect. +感谢以上优秀的开源项目和很多未提到的优秀开源项目，给予最大的 respect！ diff --git a/package.json b/package.json index 54d1094e..5ad69fb5 100644 --- a/package.json +++ b/package.json @@ -54,5 +54,6 @@ "last 1 firefox version", "last 1 safari version" ] - } + }, + "packageManager": "[email protected]+sha256.64c0b63e5fa0e21f354b5eff7c9a1b486f32046bfc3283670569e3c6a9cad102" }
