[FLINK-38661][docs] Add 2.2.0 release note (#27235)

Author: ruanhang1993

docs/content.zh/_index.md

@@ -86,7 +86,8 @@ under the License.
 For some reason Hugo will only allow linking to the 
 release notes if there is a leading '/' and file extension.
 -->
-请参阅 [Flink 2.1]({{< ref "/release-notes/flink-2.1.md" >}})，
+请参阅 [Flink 2.2]({{< ref "/release-notes/flink-2.2.md" >}})，
+[Flink 2.1]({{< ref "/release-notes/flink-2.1.md" >}})，
 [Flink 2.0]({{< ref "/release-notes/flink-2.0.md" >}})，
 [Flink 1.20]({{< ref "/release-notes/flink-1.20.md" >}})，
 [Flink 1.19]({{< ref "/release-notes/flink-1.19.md" >}})，

docs/content.zh/release-notes/flink-2.2.md

@@ -0,0 +1,226 @@
+---
+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.
+
+See more details about the capabilities and usages of
+Flink's [Model Inference](https://nightlies.apache.org/flink/flink-docs-release-2.2/docs/dev/table/tableapi/#model-inference).
+
+#### Materialized Table
+
+##### [FLINK-38532](https://issues.apache.org/jira/browse/FLINK-38532), [FLINK-38311](https://issues.apache.org/jira/browse/FLINK-38311)
+
+By specifying data freshness and query when creating [Materialized Table](https://nightlies.apache.org/flink/flink-docs-release-2.2/docs/dev/table/materialized-table/overview/),
+the engine automatically derives the schema for the materialized table and creates corresponding
+data refresh pipeline to achieve the specified freshness.
+
+From Flink 2.2, the FRESHNESS clause is not a mandatory part of the CREATE MATERIALIZED TABLE and
+CREATE OR ALTER MATERIALIZED TABLE DDL statements. Flink 2.2 introduces a new MaterializedTableEnricher
+interface. This provides a formal extension point for customizable default logic, allowing advanced
+users and vendors to implement "smart" default behaviors (e.g., inferring freshness from upstream tables).
+
+Besides this, users can use `DISTRIBUTED BY` or`DISTRIBUTED INTO` to support bucketing concept
+for Materialized tables. Users can use `SHOW MATERIALIZED TABLES` to show all Materialized tables.
+
+#### SinkUpsertMaterializer V2
+
+##### [FLINK-38459](https://issues.apache.org/jira/browse/FLINK-38459)
+
+SinkUpsertMaterializer is an operator in Flink that reconciles out of order changelog events before
+sending them to an upsert sink. Performance of this operator degrades exponentially in some cases.
+Flink 2.2 introduces a new implementation that is optimized for such cases.
+
+#### Delta Join
+
+##### [FLINK-38495](https://issues.apache.org/jira/browse/FLINK-38495), [FLINK-38511](https://issues.apache.org/jira/browse/FLINK-38511), [FLINK-38556](https://issues.apache.org/jira/browse/FLINK-38556)
+
+In 2.1, Apache Flink has introduced a new delta join operator to mitigate the challenges caused by
+big state in regular joins. It replaces the large state maintained by regular joins with a
+bidirectional lookup-based join that directly reuses data from the source tables.
+
+Flink 2.2 enhances support for converting more SQL patterns into delta joins. Delta joins now
+support consuming CDC sources without DELETE operations, and allow projection and filter operations
+after the source. Additionally, delta joins include support for caching, which helps reduce requests
+to external storage.
+
+See more details about the capabilities and usages of Flink's
+[Delta Joins](https://nightlies.apache.org/flink/flink-docs-release-2.2/docs/dev/table/tuning/#delta-joins).
+
+#### SQL Types
+
+##### [FLINK-20539](https://issues.apache.org/jira/browse/FLINK-20539), [FLINK-38181](https://issues.apache.org/jira/browse/FLINK-38181)
+
+Before Flink 2.2, row types defined in SQL e.g. `SELECT CAST(f AS ROW&lt;i NOT NULL&gt;)` did ignore
+the `NOT NULL` constraint. This was more aligned with the SQL standard but caused many type
+inconsistencies and cryptic error message when working on nested data. For example, it prevented
+using rows in computed columns or join keys. The new behavior takes the nullability into consideration.
+The config option `table.legacy-nested-row-nullability` allows to restore the old behavior if required,
+but it is recommended to update existing queries that ignored constraints before.
+
+Casting to TIME type now considers the correct precision (0-3). Casting incorrect strings to time
+(e.g. where the hour component is higher than 24) leads to a runtime exception now. Casting between
+BINARY and VARBINARY should now correctly consider the target length.
+
+#### Use UniqueKeys instead of Upsertkeys for state management
+
+##### [FLINK-38209](https://issues.apache.org/jira/browse/FLINK-38209)
+
+This is considerable optimization and an breaking change for the StreamingMultiJoinOperator.
+As noted in the release notes, the operator was launched in an experimental state for Flink 2.1
+since we're working on relevant optimizations that could be breaking changes.
+
+### Runtime
+
+#### Balanced Tasks Scheduling
+
+##### [FLINK-31757](https://issues.apache.org/jira/browse/FLINK-31757)
+
+Introducing a balanced tasks scheduling strategy to achieve task load balancing for TMs and reducing
+job bottlenecks.
+
+See more details about the capabilities and usages of
+Flink's [Balanced Tasks Scheduling](https://nightlies.apache.org/flink/flink-docs-release-2.2/docs/deployment/tasks-scheduling/balanced_tasks_scheduling/).
+
+#### Enhanced Job History Retention Policies for HistoryServer
+
+##### [FLINK-38229](https://issues.apache.org/jira/browse/FLINK-38229)
+
+Before Flink 2.2, HistoryServer supports only a quantity-based job archive retention policy and
+is insufficient for scenarios, requiring time-based retention or combined rules. Users can use
+the new configuration `historyserver.archive.retained-ttl` combining with `historyserver.archive.retained-jobs`
+to fulfill more scenario requirements.
+
+#### Metrics
+
+##### [FLINK-38158](https://issues.apache.org/jira/browse/FLINK-38158), [FLINK-38353](https://issues.apache.org/jira/browse/FLINK-38353)
+
+Since 2.2.0 users can now assign custom metric variables for each operator/transformation used in the
+Job. Those variables are later converted to tags/labels by the metric reporters, allowing users to
+tab/label specific operator's metrics. For example, you can use this to name and differentiate sources.
+
+Users can now control the level of details of checkpoint spans via [traces.checkpoint.span-detail-level](https://nightlies.apache.org/flink/flink-docs-release-2.2/docs/deployment/config/#traces-checkpoint-span-detail-level).
+Highest levels report tree of spans for each task and subtask. Reported custom spans can now contain
+children spans. See more details in [Traces](https://nightlies.apache.org/flink/flink-docs-release-2.2/docs/ops/traces/).
+
+#### Introduce Event Reporting
+
+##### [FLINK-37426](https://issues.apache.org/jira/browse/FLINK-37426)
+
+Since 2.1.0 users are able to report custom events using the EventReporters. Since 2.2.0 Flink reports
+some built-in/system events.
+
+### Connectors
+
+#### Introduce RateLimiter for Source
+
+##### [FLINK-38497](https://issues.apache.org/jira/browse/FLINK-38497)
+
+Flink jobs frequently exchange data with external systems, which consumes their network bandwidth
+and CPU. When these resources are scarce, pulling data too aggressively can disrupt other workloads.
+In Flink 2.2, we introduce a RateLimiter interface to provide request rate limiting for Scan Sources
+and connector developers can integrate with rate limiting frameworks to implement their own read
+restriction strategies. This feature is currently only available in the DataStream API.
+
+#### Balanced splits assignment
+
+##### [FLINK-38564](https://issues.apache.org/jira/browse/FLINK-38564)
+
+SplitEnumerator is responsible for assigning splits, but it lacks visibility into the actual runtime
+status or distribution of these splits. This makes it impossible for SplitEnumerator to guarantee
+that the sharding is evenly distributed, and data skew is very likely to occur. From Flink 2.2,
+SplitEnumerator has the information of the splits distribution and provides the ability to evenly
+assign splits at runtime.
+
+### Python
+
+#### Support async function in Python DataStream API
+
+##### [FLINK-38190](https://issues.apache.org/jira/browse/FLINK-38190)
+
+In Flink 2.2, we have added support of async function in Python DataStream API. This enables Python
+users to efficiently query external services in their Flink jobs, e.g. large-sized LLM which is
+typically deployed in a standalone GPU cluster, etc.
+
+Furthermore, we have provided comprehensive support to ensure the stability of external service
+access. On one hand, we support limiting the number of concurrent requests sent to the external
+service to avoid overwhelming it. On the other hand, we have also added retry support to tolerate
+temporary unavailability which maybe caused by network jitter or other transient issues.
+
+### Dependency upgrades
+
+#### Upgrade commons-lang3 to version 3.18.0
+
+##### [FLINK-38193](https://issues.apache.org/jira/browse/FLINK-38193)
+
+Upgrade org.apache.commons:commons-lang3 from 3.12.0 to 3.18.0 to mitigate CVE-2025-48924.
+
+#### Upgrade protobuf-java from 3.x to 4.32.1 with compatibility patch for parquet-protobuf
+
+##### [FLINK-38547](https://issues.apache.org/jira/browse/FLINK-38547)
+
+Flink now uses protobuf-java 4.32.1 (corresponding to Protocol Buffers version 32), upgrading from
+protobuf-java 3.21.7 (Protocol Buffers version 21). This major upgrade enables:
+
+- **Protobuf Editions Support**: Full support for the new `edition = "2023"` and `edition = "2024"`
+  syntax introduced in Protocol Buffers v27+. Editions provide a unified approach that combines
+  proto2 and proto3 functionality with fine-grained feature control.
+- **Improved Proto3 Field Presence**: Better handling of optional fields in proto3 without the
+  limitations of older protobuf versions, eliminating the need to set `protobuf.read-default-values`
+  to `true` for field presence checking.
+- **Enhanced Performance**: Leverages performance improvements and bug fixes from 11 Protocol
+  Buffers releases (versions 22-32).
+- **Modern Protobuf Features**: Access to newer protobuf capabilities including Edition 2024
+  features and improved runtime behavior.
+
+Users with existing proto2 and proto3 `.proto` files will continue to work without changes.

docs/content/_index.md

@@ -87,6 +87,7 @@ For some reason Hugo will only allow linking to the
 release notes if there is a leading '/' and file extension.
 -->
 See the release notes for
+[Flink 2.2]({{< ref "/release-notes/flink-2.2.md" >}}),
 [Flink 2.1]({{< ref "/release-notes/flink-2.1.md" >}}),
 [Flink 2.0]({{< ref "/release-notes/flink-2.0.md" >}}),
 [Flink 1.20]({{< ref "/release-notes/flink-1.20.md" >}}),