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Posted to issues@streampark.apache.org by "cottage14 (via GitHub)" <gi...@apache.org> on 2024/04/25 17:40:32 UTC
[PR] Update intro.md text changes to improve readability [incubator-streampark-website]
cottage14 opened a new pull request, #352:
URL: https://github.com/apache/incubator-streampark-website/pull/352
line 11: corrected grammar and some noun-verb alignments
line 15: if you have 'including' at the start of a list, you do not need 'etc.' at the end.
line 17: a question requires a ? at the end
line 21: removed repetition
lines 30 and 63: removed empty bullet point
line 33: changed 'three parts' to 'two parts'
lines 41 and 64: rewrote sentences
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Re: [PR] Update intro.md text changes to improve readability [incubator-streampark-website]
Posted by "cottage14 (via GitHub)" <gi...@apache.org>.
cottage14 commented on PR #352:
URL: https://github.com/apache/incubator-streampark-website/pull/352#issuecomment-2077936485
Always happy to help. I will try to work my way through the rest of the doc
pages to see what I can see.
a
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Re: [PR] Update intro.md text changes to improve readability [incubator-streampark-website]
Posted by "tisonkun (via GitHub)" <gi...@apache.org>.
tisonkun commented on PR #352:
URL: https://github.com/apache/incubator-streampark-website/pull/352#issuecomment-2077896992
Thanks for your contribution! It's exciting to have a professional editor help with this content.
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Re: [PR] Update intro.md text changes to improve readability [incubator-streampark-website]
Posted by "tisonkun (via GitHub)" <gi...@apache.org>.
tisonkun commented on code in PR #352:
URL: https://github.com/apache/incubator-streampark-website/pull/352#discussion_r1579894384
##########
docs/intro.md:
##########
@@ -10,44 +10,43 @@ 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.
+`Apache StreamPark` is an easy-to-use stream processing application development framework and one-stop stream processing operation platform. Aimed to make it easy to build and manage streaming applications, StreamPark provides scaffolding for writing streaming process logic 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 module including task development, scheduling, interactive queries, deployment, operations, and maintenance.
-## Why Apache StreamPark™
+## 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 on the business logic.
+Apache Flink and Apache Spark are widely used as the next generation of big data streaming computing engines. Based on a foundation 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 can bring an easier and more efficient task development experience. It reduces the learning cost and development barriers, so developers can focus on the business logic.
-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.
+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 as described above.
## 🎉 Features
* Apache Flink & Apache Spark application development scaffold
-* Support multiple versions of Flink & Spark
+* Supports multiple versions of Flink & Spark
* Wide range of out-of-the-box connectors
* One-stop stream processing operation platform
-* Support catalog、olap、streaming-warehouse etc.
-* ...
+* Supports catalog、olap、streaming-warehouse, etc.
Review Comment:
```suggestion
* Supports catalog, OLAP, streaming warehouse, etc.
```
##########
docs/intro.md:
##########
@@ -10,44 +10,43 @@ 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.
+`Apache StreamPark` is an easy-to-use stream processing application development framework and one-stop stream processing operation platform. Aimed to make it easy to build and manage streaming applications, StreamPark provides scaffolding for writing streaming process logic 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 module including task development, scheduling, interactive queries, deployment, operations, and maintenance.
-## Why Apache StreamPark™
+## 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 on the business logic.
+Apache Flink and Apache Spark are widely used as the next generation of big data streaming computing engines. Based on a foundation 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 can bring an easier and more efficient task development experience. It reduces the learning cost and development barriers, so developers can focus on the business logic.
-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.
+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 as described above.
## 🎉 Features
* Apache Flink & Apache Spark application development scaffold
-* Support multiple versions of Flink & Spark
+* Supports multiple versions of Flink & Spark
* Wide range of out-of-the-box connectors
* One-stop stream processing operation platform
-* Support catalog、olap、streaming-warehouse etc.
-* ...
+* Supports catalog、olap、streaming-warehouse, etc.
## 🏳🌈 Architecture of Apache StreamPark™
-The overall architecture of Apache StreamPark is shown in the following figure. Apache StreamPark consists of three parts, they are streampark-core and streampark-console.
+The overall architecture of Apache StreamPark is shown in the following figure. Apache StreamPark has two parts, `streampark-core` and `streampark-console`.
### 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` is a framework uesd during development. It supports on coding development, regulates configuration files, and follows the 'convention over configuration' guide.
Review Comment:
```suggestion
`streampark-core` is a framework used during development. It supports coding development, regulates configuration files, and follows the 'convention over configuration' principle.
```
##########
docs/intro.md:
##########
@@ -10,44 +10,43 @@ 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.
+`Apache StreamPark` is an easy-to-use stream processing application development framework and one-stop stream processing operation platform. Aimed to make it easy to build and manage streaming applications, StreamPark provides scaffolding for writing streaming process logic with Apache Flink and Apache Spark.
Review Comment:
```suggestion
Apache StreamPark is an easy-to-use stream processing application development framework and one-stop stream processing operation platform. Aimed to make it easy to build and manage streaming applications, StreamPark provides scaffolding for writing streaming process logic with Apache Flink and Apache Spark.
```
##########
docs/intro.md:
##########
@@ -10,44 +10,43 @@ 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.
+`Apache StreamPark` is an easy-to-use stream processing application development framework and one-stop stream processing operation platform. Aimed to make it easy to build and manage streaming applications, StreamPark provides scaffolding for writing streaming process logic 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 module including task development, scheduling, interactive queries, deployment, operations, and maintenance.
-## Why Apache StreamPark™
+## 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 on the business logic.
+Apache Flink and Apache Spark are widely used as the next generation of big data streaming computing engines. Based on a foundation 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 can bring an easier and more efficient task development experience. It reduces the learning cost and development barriers, so developers can focus on the business logic.
-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.
+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 as described above.
## 🎉 Features
* Apache Flink & Apache Spark application development scaffold
-* Support multiple versions of Flink & Spark
+* Supports multiple versions of Flink & Spark
* Wide range of out-of-the-box connectors
* One-stop stream processing operation platform
-* Support catalog、olap、streaming-warehouse etc.
-* ...
+* Supports catalog、olap、streaming-warehouse, etc.
## 🏳🌈 Architecture of Apache StreamPark™
-The overall architecture of Apache StreamPark is shown in the following figure. Apache StreamPark consists of three parts, they are streampark-core and streampark-console.
+The overall architecture of Apache StreamPark is shown in the following figure. Apache StreamPark has two parts, `streampark-core` and `streampark-console`.
### 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` is a framework uesd during development. It supports on coding development, regulates configuration files, and follows 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 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 the Flink SQL API. This improves development efficiency and developer experience, because users can focus on the business logic.
Review Comment:
```suggestion
`streampark-core` provides 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 the Flink SQL API. This improves development efficiency and developer experience, because users can focus on the business logic.
```
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Re: [PR] Update intro.md text changes to improve readability [incubator-streampark-website]
Posted by "tisonkun (via GitHub)" <gi...@apache.org>.
tisonkun merged PR #352:
URL: https://github.com/apache/incubator-streampark-website/pull/352
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