lsyldliu commented on code in PR #800:
URL: https://github.com/apache/flink-web/pull/800#discussion_r2232656277
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docs/content/posts/2025-07-31-release-2.1.0.md:
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+---
+authors:
+ - reswqa:
+ name: "Ron Liu"
+ twitter: "Ron999"
+
+date: "2025-07-31T08:00:00Z"
+subtitle: ""
+title: Ushers in a New Era of Unified Real-Time Data + AI with Comprehensive
Upgrades
+aliases:
+ - /news/2025/07/31/release-2.1.0.html
+---
+
+The Apache Flink PMC is proud to announce the release of Apache Flink 2.1.0.
This marks a significant milestone
+in the evolution of the real-time data processing engine into a unified Data +
AI platform. This release brings
+together 116 global contributors, implements 15 FLIPs (Flink Improvement
Proposals), and resolves over 220 issues,
+with a strong focus on deepening the integration of real-time AI and
intelligent stream processing:
+
+1. **Breakthroughs in Real-Time AI**:
+ - Introduces AI Model DDL, enabling flexible management of AI models
through Flink SQL and the Table API.
+
+ - Extends the `ML_PREDICT` Table-Valued Function (TVF), empowering
real-time invocation of AI models within Flink SQL,
+ laying the foundation for building end-to-end real-time AI workflows.
+
+2. **Enhanced Real-Time Data Processing**:
+ - Adds the `VARIANT` data type for efficient handling of semi-structured
data like JSON. Combined with the `PARSE_JSON` function
+ and lakehouse formats (e.g., Apache Paimon), it enables dynamic schema
data analysis.
+
+ - Significantly optimizes streaming joins with the innovative introduction
of `DeltaJoin` and `MultiJoin` strategies,
+ eliminating state bottlenecks and improving resource utilization and job
stability.
+
+Flink 2.1.0 seamlessly integrates real-time data processing with AI models,
empowering enterprises to advance from
+real-time analytics to real-time intelligent decision-making, meeting the
evolving demands of modern data applications.
+We extend our gratitude to all contributors for their invaluable support!
+
+Let's dive into the highlights.
+
+# Flink SQL Improvements
+
+## Model DDLs
+Since Flink 2.0, we have introduced dedicated syntax for AI models, enabling
users to define models
+as easily as creating catalog objects and invoke them like standard functions
or table functions in SQL statements.
+In Flink 2.1, we have also added Model DDLs Table API support, enabling users
to define and manage AI models programmatically
+via the Table API in both Java and Python. This provides a flexible,
code-driven alternative to SQL for model management and
+integration within Flink applications.
+
+Example:
+- Defining a Model via Flink SQL
+```sql
+CREATE MODEL my_model
+INPUT (f0 STRING)
+OUTPUT (label STRING)
+WITH (
+ 'task' = 'classification',
+ 'type' = 'remote',
+ 'provider' = 'openai',
+ 'openai.endpoint' = 'remote',
+ 'openai.api_key' = 'abcdefg',
+);
+```
+
+- Defining a Model via Table API (Java)
+```java
+tEnv.createModel(
+ "MyModel",
+ ModelDescriptor.forProvider("OPENAI")
+ .inputSchema(Schema.newBuilder()
+ .column("f0", DataTypes.STRING())
+ .build())
+ .outputSchema(Schema.newBuilder()
+ .column("label", DataTypes.STRING())
+ .build())
+ .option("task", "classification")
+ .option("type", "remote")
+ .option("provider", "openai")
+ .option("openai.endpoint", "remote")
+ .option("openai.api_key", "abcdefg")
+ .build(),
+ true);
+```
+
+**More Information**
+* [FLINK-37548](https://issues.apache.org/jira/browse/FLINK-37548)
+*
[FLIP-437](https://cwiki.apache.org/confluence/display/FLINK/FLIP-437%3A+Support+ML+Models+in+Flink+SQL)
+*
[FLIP-507](https://cwiki.apache.org/confluence/display/FLINK/FLIP-507%3A+Add+Model+DDL+methods+in+TABLE+API)
+
+## Realtime AI Function
+
+Based on the AI model DDL, In Flink 2.1, we expanded the `ML_PREDICT`
table-valued function (TVF) to perform realtime model inference in SQL queries,
applying machine learning models to data streams seamlessly.
+The implementation supports both Flink builtin model providers (OpenAI) and
interfaces for users to define custom model providers, accelerating Flink's
evolution from a real-time
+data processing engine to a unified realtime AI platform. Looking ahead, we
plan to introduce more AI functions such as `ML_EVALUATE`, `VECTOR_SEARCH` to
unlock end-to-end experience
+for real-time data processing, model training, and inference.
+
+Take the following SQL statements as an example:
+```sql
+-- Declare a AI model
+CREATE MODEL `my_model`
+INPUT (text STRING)
+OUTPUT (response STRING)
+WITH(
+ 'provider' = 'openai',
+ 'endpoint' = 'https://api.openai.com/v1/llm/v1/chat',
+ 'api-key' = 'abcdefg',
+ 'system-prompt' = 'translate to Chinese',
+ 'model' = 'gpt-4o'
+);
+
+-- Basic usage
+SELECT * FROM ML_PREDICT(
+ TABLE input_table,
+ MODEL my_model,
+ DESCRIPTOR(text)
+);
+
+-- With configuration options
+SELECT * FROM ML_PREDICT(
+ TABLE input_table,
+ MODEL my_model,
+ DESCRIPTOR(text)
+ MAP['async', 'true', 'timeout', '100s']
+);
+
+-- Using named parameters
+SELECT * FROM ML_PREDICT(
+ INPUT => TABLE input_table,
+ MODEL => MODEL my_model,
+ ARGS => DESCRIPTOR(text),
+ CONFIG => MAP['async', 'true']
+);
+```
+
+**More Information**
+* [FLINK-34992](https://issues.apache.org/jira/browse/FLINK-34992)
+* [FLINK-37777](https://issues.apache.org/jira/browse/FLINK-37777)
+*
[FLIP-437](https://cwiki.apache.org/confluence/display/FLINK/FLIP-437%3A+Support+ML+Models+in+Flink+SQL)
+*
[FLIP-525](https://cwiki.apache.org/confluence/display/FLINK/FLIP-525%3A+Model+ML_PREDICT%2C+ML_EVALUATE+Implementation+Design)
+* [Model
Inference](https://nightlies.apache.org/flink/flink-docs-release-2.1/docs/dev/table/sql/queries/model-inference/)
+
+## Variant Type
Review Comment:
@twalthr Thanks for providing the details.
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