[GitHub] [flink-web] MarkSfik commented on a diff in pull request #618: Announcement blogpost for the 1.17 release

["MarkSfik (via GitHub)" <gi...@apache.org>]

MarkSfik commented on code in PR #618:
URL: https://github.com/apache/flink-web/pull/618#discussion_r1138772302


##########
docs/content/posts/2023-03-09-release-1.17.0.md:
##########
@@ -0,0 +1,485 @@
+---
+authors:
+- LeonardXu:
+  name: "Leonard Xu"
+  twitter: Leonardxbj
+date: "2023-03-09T08:00:00Z" #FIXME: Change to the actual release date, also the date in the filename, and the directory name of linked images
+subtitle: ""
+title: Announcing the Release of Apache Flink 1.17
+aliases:
+- /news/2023/03/09/release-1.17.0.html #FIXME: Change to the actual release date
+---
+
+The Apache Flink PMC is pleased to announce Apache Flink release 1.17.0. Apache
+Flink is the leading stream processing standard, and the concept of unified
+stream and batch data processing is being successfully adopted in more and more
+companies. Thanks to our excellent community and contributors, Apache Flink
+continues to grow as a technology and remains one of the most active projects in
+the Apache Software Foundation. Flink 1.17 had 173 contributors enthusiastically
+participating and saw the completion of 7 FLIPs and 600+ issues, bringing many
+exciting new features and improvements to the community.
+
+
+# Towards Streaming Warehouses
+
+In order to achieve greater efficiency in the realm of [streaming
+warehouse](https://www.alibabacloud.com/blog/more-than-computing-a-new-era-led-by-the-warehouse-architecture-of-apache-flink_598821),
+Flink 1.17 contains substantial improvements to both the performance of batch
+processing and the semantics of streaming processing. These improvements
+represent a significant stride towards the creation of a more efficient and
+streamlined data warehouse, capable of processing large quantities of data in
+real-time.
+
+For batch processing, this release includes several new features and
+improvements:
+
+* **Streaming Warehouse API:**
+  [FLIP-282](https://cwiki.apache.org/confluence/pages/viewpage.action?pageId=235838061)
+  introduces the new Delete and Update API in Flink SQL which works in(only) batch
+  mode. External storage systems like Flink Table Store can implement row-level
+  updates via this new API. The ALTER TABLE syntax is enhanced by including the
+  ability to ADD/MODIFY/DROP columns, primary keys, and watermarks, making it
+  easier for users to maintain their table schema.
+* **Batch Execution Improvements:** Execution of batch workloads has been
+  significantly improved in Flink 1.17 in terms of performance, stability and
+  usability. Performance wise, a 26% TPC-DS improvement on 10T dataset is achieved
+  with strategy and operator optimizations, such as new join reordering and adaptive
+  local hash aggregation, Hive aggregate functions improvements, and the hybrid
+  shuffle mode enhancements. Stability wise, speculative execution now supports
+  all operators, and the Adaptive Batch Scheduler is more robust against data
+  skew. Usability wise, the tuning effort required for batch workloads has been
+  reduced. The Adaptive Batch Scheduler is now the default scheduler in batch mode.
+  The hybrid shuffle is compatible with speculative execution and the Adaptive 
+  Batch Scheduler, next to various configuration simplifications.
+* **SQL Client/Gateway:** Apache Flink 1.17 introduces the "gateway mode" for
+  SQL Client, allowing users to submit SQL queries to a SQL Gateway for enhanced
+  functionality. Users can use SQL statements to manage job lifecycles,
+  including displaying job information and stopping running jobs.  This provides
+  a powerful tool for managing Flink jobs.
+
+For stream processing, the following features and improvements are realized:
+
+* **Streaming SQL Semantics:** Non-deterministic operations may bring incorrect
+  results or exceptions which is a challenging topic in streaming SQL. Incorrect
+  optimization plans and functional issues have been fixed, and the experimental
+  feature of [PLAN_ADVICE](https://nightlies.apache.org/flink/flink-docs-release-1.17/docs/dev/table/sql/explain/#explaindetails)
+  is introduced to inform of potential correctness risks and optimization
+  suggestions to SQL users.
+* **Checkpoint Improvements:** The generic incremental checkpoint improvements
+  enhance the speed and stability of the checkpoint procedure, and the unaligned
+  checkpoint has improved  stability under backpressure and is production-ready

Review Comment:
   ```suggestion
     checkpoint has improved stability under backpressure and is production-ready
   ```



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