ruanhang1993 commented on code in PR #27235: URL: https://github.com/apache/flink/pull/27235#discussion_r2579797369
########## docs/content.zh/release-notes/flink-2.2.md: ########## @@ -0,0 +1,224 @@ +--- +title: "Release Notes - Flink 2.2" +--- + +<!-- +Licensed to the Apache Software Foundation (ASF) under one +or more contributor license agreements. See the NOTICE file +distributed with this work for additional information +regarding copyright ownership. The ASF licenses this file +to you under the Apache License, Version 2.0 (the +"License"); you may not use this file except in compliance +with the License. You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, +software distributed under the License is distributed on an +"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +KIND, either express or implied. See the License for the +specific language governing permissions and limitations +under the License. +--> + +# Release notes - Flink 2.2 + +These release notes discuss important aspects, such as configuration, behavior or dependencies, +that changed between Flink 2.1 and Flink 2.2. Please read these notes carefully if you are +planning to upgrade your Flink version to 2.2. + +### Table SQL / API + +#### Support VECTOR_SEARCH in Flink SQL + +##### [FLINK-38422](https://issues.apache.org/jira/browse/FLINK-38422) + +Apache Flink has supported leveraging LLM capabilities through the `ML_PREDICT` function in Flink SQL +since version 2.1, enabling users to perform semantic analysis in a simple and efficient way. This +integration has been technically validated in scenarios such as log classification and real-time +question-answering systems. However, the current architecture allows Flink to only use embedding +models to convert unstructured data (e.g., text, images) into high-dimensional vector features, +which are then persisted to downstream storage systems. It lacks real-time online querying and +similarity analysis capabilities for vector spaces. The VECTOR_SEARCH function is provided in Flink +2.2 to enable users to perform streaming vector similarity searches and real-time context retrieval +directly within Flink. + +See more details about the capabilities and usages of +Flink's [Vector Search](https://nightlies.apache.org/flink/flink-docs-release-2.2/docs/dev/table/sql/queries/vector-search/). + +#### Realtime AI Function + +##### [FLINK-38104](https://issues.apache.org/jira/browse/FLINK-38104) + +Apache Flink has supported leveraging LLM capabilities through the `ML_PREDICT` function in Flink SQL +since version 2.1. In Flink 2.2, the Table API also supports model inference operations that allow +you to integrate machine learning models directly into your data processing pipelines. Review Comment: Fixed. -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
