[GitHub] [flink-web] carp84 commented on a diff in pull request #577: [FLINK-29668] Remove Gelly

[GitBox <gi...@apache.org>]

carp84 commented on code in PR #577:
URL: https://github.com/apache/flink-web/pull/577#discussion_r999227117


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usecases.md:
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@@ -67,7 +67,7 @@ Another aspect is a simpler application architecture. A batch analytics pipeline
 
 ### How does Flink support data analytics applications?
 
-Flink provides very good support for continuous streaming as well as batch analytics. Specifically, it features an ANSI-compliant SQL interface with unified semantics for batch and streaming queries. SQL queries compute the same result regardless whether they are run on a static data set of recorded events or on a real-time event stream. Rich support for user-defined functions ensures that custom code can be executed in SQL queries. If even more custom logic is required, Flink's DataStream API or DataSet API provide more low-level control. Moreover, Flink's Gelly library provides algorithms and building blocks for large-scale and high-performance graph analytics on batch data sets.
+Flink provides very good support for continuous streaming as well as batch analytics. Specifically, it features an ANSI-compliant SQL interface with unified semantics for batch and streaming queries. SQL queries compute the same result regardless whether they are run on a static data set of recorded events or on a real-time event stream. Rich support for user-defined functions ensures that custom code can be executed in SQL queries. If even more custom logic is required, Flink's DataStream API or DataSet API provide more low-level control. 

Review Comment:
   Maybe also worth mentioning graph processing here like below?
   
   Moreover, Flink could provide algorithms and building blocks for large-scale and high-performance graph processing, which used to be supported by the Gelly library. However, along with the evolution of Flink (especially the deprecation of the old dataset API), Gelly has been dropped and will be replaced by new implementations based on the new iterations framework via [Flink ML](https://nightlies.apache.org/flink/flink-ml-docs-stable/docs/development/iteration/).
   
   And the Chinese version:
   
   此外，Flink 具备为大规模高性能图分析提供算法和构建支持的能力。Flink中的Gelly模块曾经提供过这种能力，但随着Flink的演进（尤其是dataset API的废弃）Gelly已经被移除，图处理能力将由基于[Flink-ML中提供的新迭代框架](https://nightlies.apache.org/flink/flink-ml-docs-stable/docs/development/iteration/)的全新实现提供，敬请期待。



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