This is an automated email from the ASF dual-hosted git repository.
ron pushed a commit to branch release-2.1
in repository https://gitbox.apache.org/repos/asf/flink.git
The following commit(s) were added to refs/heads/release-2.1 by this push:
new 16ffc02bf3e [FLINK-38017][release] Add release note for release 2.1
(#26778)
16ffc02bf3e is described below
commit 16ffc02bf3ec92a4426677cf3cf29c0f7d4ee00b
Author: Ron <ron9....@gmail.com>
AuthorDate: Sat Jul 19 10:24:32 2025 +0800
[FLINK-38017][release] Add release note for release 2.1 (#26778)
(cherry picked from commit 7309fe832cb303c9adf6bfb441790e3d293908fe)
---
docs/content.zh/_index.md | 3 +-
docs/content.zh/release-notes/flink-2.1.md | 185 +++++++++++++++++++++++++++++
docs/content/_index.md | 1 +
docs/content/release-notes/flink-2.1.md | 185 +++++++++++++++++++++++++++++
4 files changed, 373 insertions(+), 1 deletion(-)
diff --git a/docs/content.zh/_index.md b/docs/content.zh/_index.md
index 14693f69724..b2fa4429de6 100644
--- a/docs/content.zh/_index.md
+++ b/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 2.0]({{< ref "/release-notes/flink-2.0.md" >}})，
+请参阅 [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" >}})，
[Flink 1.18]({{< ref "/release-notes/flink-1.18.md" >}})，
diff --git a/docs/content.zh/release-notes/flink-2.1.md
b/docs/content.zh/release-notes/flink-2.1.md
new file mode 100644
index 00000000000..b5e1b4f2f80
--- /dev/null
+++ b/docs/content.zh/release-notes/flink-2.1.md
@@ -0,0 +1,185 @@
+---
+title: "Release Notes - Flink 2.1"
+---
+
+<!--
+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 2.1
+
+These release notes discuss important aspects, such as configuration, behavior
or dependencies,
+that changed between Flink 2.0 and Flink 2.1. Please read these notes
carefully if you are
+planning to upgrade your Flink version to 2.1.
+
+### Table SQL / API
+
+#### Model DDLs using Table API
+
+##### [FLINK-37548](https://issues.apache.org/jira/browse/FLINK-37548)
+
+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 also added Model DDLs Table API support,
allowing users to define
+and manage AI models programmatically through the Table API in both Java and
Python.
+
+#### Realtime AI Function
+
+##### [FLINK-34992](https://issues.apache.org/jira/browse/FLINK-34992),
[FLINK-37777](https://issues.apache.org/jira/browse/FLINK-37777)
+
+Based on the AI model DDL, we also 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 to unlock end-to-end experience for real-time data processing, model
training, and
+inference.
+
+See more details about the capabilities and usages of
+Flink's [Model
Inference](https://nightlies.apache.org/flink/flink-docs-release-2.1/docs/dev/table/sql/queries/model-inference/).
+
+#### Variant Type
+
+##### [FLINK-37922](https://issues.apache.org/jira/browse/FLINK-37922)
+
+Variant is a new data type for semi-structured data(e.g. JSON), it supports
storing any
+semi-structured data, including ARRAY, MAP(with STRING keys), and scalar
types—while preserving
+field type information in a JSON-like structure. Unlike ROW and STRUCTURED
types, VARIANT provides
+superior flexibility for handling deeply nested and evolving schemas.
+
+Users can use `PARSE_JSON` or`TRY_PARSE_JSON` to convert JSON-formatted
VARCHAR data to VARIANT. In
+addition, table formats like Apache Paimon now support the VARIANT type, this
enable
+users to efficiently process semi-structured data in lakehouse using Flink SQL.
+
+#### Structured Type Enhancements
+
+##### [FLINK-37861](https://issues.apache.org/jira/browse/FLINK-37861)
+
+Enabling declare user-defined objects via STRUCTURED TYPE directly in `CREATE
TABLE` DDL
+statements, resolving critical type equivalence issues and significantly
improving API usability.
+
+#### Delta Join
+
+##### [FLINK-37836](https://issues.apache.org/jira/browse/FLINK-37836)
+
+Introduced a new DeltaJoin operator in stream processing jobs, along with
optimizations for simple
+streaming join pipeline. Compared to traditional streaming join, delta join
requires significantly
+less state, effectively mitigating issues related to large state, including
resource bottlenecks,
+slow checkpointing, and lengthy job recovery times. This feature is enabled by
default. More details
+can be found
+at [Delta
Join](https://cwiki.apache.org/confluence/display/FLINK/FLIP-486%3A+Introduce+A+New+DeltaJoin)
+
+#### Multiple Regular Joins
+
+##### [FLINK-37859](https://issues.apache.org/jira/browse/FLINK-37859)
+
+Streaming Flink jobs with multiple cascaded streaming joins often experience
operational
+instability and performance degradation due to large state sizes. This release
introduces a
+multi-join operator (`StreamingMultiJoinOperator`) that drastically reduces
state size
+by eliminating intermediate results. The operator achieves this by processing
joins across all input
+streams simultaneously within a single operator instance, storing only raw
input records instead of
+propagated join output.
+
+This "zero intermediate state" approach primarily targets state reduction,
offering substantial
+benefits in resource consumption and operational stability. This feature is
now available for
+pipelines with multiple INNER/LEFT joins that share at least one common join
key, enable with
+`SET 'table.optimizer.multi-join.enabled' = 'true'`.
+
+#### Async Lookup Join Enhancements
+
+##### [FLINK-37874](https://issues.apache.org/jira/browse/FLINK-37874)
+
+Support handling records in order based on upsert key (the unique key in the
input stream deduced by
+planner) while allowing parallel processing of different keys to achieve
better throughput when
+processing changelog data stream.
+
+#### Sink Reuse
+
+##### [FLINK-37227](https://issues.apache.org/jira/browse/FLINK-37227)
+
+Within a single Flink job, when writing multiple `INSERT INTO` statements
updating identical
+columns (different columns will be supported in next release) of a target
table, the planner will
+optimize the execution plan and merge the sink nodes to achieve reuse. This
will be a great
+usability improvement for users using partial-update features with data lake
storages like Apache
+Paimon.
+
+#### Support Smile Format for Compiled Plan Serialization
+
+##### [FLINK-37341](https://issues.apache.org/jira/browse/FLINK-37341)
+
+This release adds smile binary format support for compiled plans, providing a
memory-efficient
+alternative to JSON for serialization/deserialization. By default JSON is
used, in order to use
+smile format need to call `CompiledPlan#asSmileBytes` and
`PlanReference#fromSmileBytes` method.
+
+### Runtime
+
+#### Add Pluggable Batching for Async Sink
+
+##### [FLINK-37298](https://issues.apache.org/jira/browse/FLINK-37298)
+
+Introducing a pluggable batching mechanism for async sink that allows users to
define custom
+batching write strategies tailored to specific requirements.
+
+#### Split-level Watermark Metrics
+
+##### [FLINK-37410](https://issues.apache.org/jira/browse/FLINK-37410)
+
+We adds some split level watermark metrics, covering watermark progress and
per-split state gauges
+to enhance the watermark observability:
+
+- `currentWatermark`: the last watermark this split has received.
+- `activeTimeMsPerSecond`: the time this split is active per second.
+- `pausedTimeMsPerSecond`: the time this split is paused due to watermark
alignment per second.
+- `idleTimeMsPerSecond`: the time this split is marked idle by idleness
detection per second.
+- `accumulatedActiveTimeMs`: accumulated time this split was active since
registered.
+- `accumulatedPausedTimeMs`: accumulated time this split was paused since
registered.
+- `accumulatedIdleTimeMs`: accumulated time this split was idle since
registered.
+
+### Connectors
+
+#### Introduce SQL Connector for Keyed State
+
+##### [FLINK-36929](https://issues.apache.org/jira/browse/FLINK-36929)
+
+In this release, we introduce a new connector for keyed state. This connector
allows
+users to query keyed state directly from checkpoint or savepoint using Flink
SQL, making it easier
+to inspect, debug, and validate the state of Flink jobs without custom
tooling. This feature is
+especially useful for analyzing long-running jobs and validating state
migrations.
+
+### Python
+
+#### Adds support of Python 3.12 and removes support of Python 3.8
+
+##### [FLINK-37823](https://issues.apache.org/jira/browse/FLINK-37823),
[FLINK-37776](https://issues.apache.org/jira/browse/FLINK-37776)
+
+PyFlink 2.1 will support Python 3.12 and remove the support for Python 3.8.
+
+### Dependency upgrades
+
+#### Upgrade flink-shaded version to 20.0
+
+##### [FLINK-37376](https://issues.apache.org/jira/browse/FLINK-37376)
+
+Bump flink-shaded version to 20.0 to support Smile format.
+
+#### Upgrade Parquet version to 1.15.3
+
+##### [FLINK-37760](https://issues.apache.org/jira/browse/FLINK-37760)
+
+Bump parquet version to 1.15.3 to resolve parquet-avro module
+vulnerability found in
[CVE-2025-30065](https://nvd.nist.gov/vuln/detail/CVE-2025-30065).
\ No newline at end of file
diff --git a/docs/content/_index.md b/docs/content/_index.md
index 05d5380b269..9051660db58 100644
--- a/docs/content/_index.md
+++ b/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 2.1]({{< 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" >}}),
diff --git a/docs/content/release-notes/flink-2.1.md
b/docs/content/release-notes/flink-2.1.md
new file mode 100644
index 00000000000..b5e1b4f2f80
--- /dev/null
+++ b/docs/content/release-notes/flink-2.1.md
@@ -0,0 +1,185 @@
+---
+title: "Release Notes - Flink 2.1"
+---
+
+<!--
+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 2.1
+
+These release notes discuss important aspects, such as configuration, behavior
or dependencies,
+that changed between Flink 2.0 and Flink 2.1. Please read these notes
carefully if you are
+planning to upgrade your Flink version to 2.1.
+
+### Table SQL / API
+
+#### Model DDLs using Table API
+
+##### [FLINK-37548](https://issues.apache.org/jira/browse/FLINK-37548)
+
+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 also added Model DDLs Table API support,
allowing users to define
+and manage AI models programmatically through the Table API in both Java and
Python.
+
+#### Realtime AI Function
+
+##### [FLINK-34992](https://issues.apache.org/jira/browse/FLINK-34992),
[FLINK-37777](https://issues.apache.org/jira/browse/FLINK-37777)
+
+Based on the AI model DDL, we also 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 to unlock end-to-end experience for real-time data processing, model
training, and
+inference.
+
+See more details about the capabilities and usages of
+Flink's [Model
Inference](https://nightlies.apache.org/flink/flink-docs-release-2.1/docs/dev/table/sql/queries/model-inference/).
+
+#### Variant Type
+
+##### [FLINK-37922](https://issues.apache.org/jira/browse/FLINK-37922)
+
+Variant is a new data type for semi-structured data(e.g. JSON), it supports
storing any
+semi-structured data, including ARRAY, MAP(with STRING keys), and scalar
types—while preserving
+field type information in a JSON-like structure. Unlike ROW and STRUCTURED
types, VARIANT provides
+superior flexibility for handling deeply nested and evolving schemas.
+
+Users can use `PARSE_JSON` or`TRY_PARSE_JSON` to convert JSON-formatted
VARCHAR data to VARIANT. In
+addition, table formats like Apache Paimon now support the VARIANT type, this
enable
+users to efficiently process semi-structured data in lakehouse using Flink SQL.
+
+#### Structured Type Enhancements
+
+##### [FLINK-37861](https://issues.apache.org/jira/browse/FLINK-37861)
+
+Enabling declare user-defined objects via STRUCTURED TYPE directly in `CREATE
TABLE` DDL
+statements, resolving critical type equivalence issues and significantly
improving API usability.
+
+#### Delta Join
+
+##### [FLINK-37836](https://issues.apache.org/jira/browse/FLINK-37836)
+
+Introduced a new DeltaJoin operator in stream processing jobs, along with
optimizations for simple
+streaming join pipeline. Compared to traditional streaming join, delta join
requires significantly
+less state, effectively mitigating issues related to large state, including
resource bottlenecks,
+slow checkpointing, and lengthy job recovery times. This feature is enabled by
default. More details
+can be found
+at [Delta
Join](https://cwiki.apache.org/confluence/display/FLINK/FLIP-486%3A+Introduce+A+New+DeltaJoin)
+
+#### Multiple Regular Joins
+
+##### [FLINK-37859](https://issues.apache.org/jira/browse/FLINK-37859)
+
+Streaming Flink jobs with multiple cascaded streaming joins often experience
operational
+instability and performance degradation due to large state sizes. This release
introduces a
+multi-join operator (`StreamingMultiJoinOperator`) that drastically reduces
state size
+by eliminating intermediate results. The operator achieves this by processing
joins across all input
+streams simultaneously within a single operator instance, storing only raw
input records instead of
+propagated join output.
+
+This "zero intermediate state" approach primarily targets state reduction,
offering substantial
+benefits in resource consumption and operational stability. This feature is
now available for
+pipelines with multiple INNER/LEFT joins that share at least one common join
key, enable with
+`SET 'table.optimizer.multi-join.enabled' = 'true'`.
+
+#### Async Lookup Join Enhancements
+
+##### [FLINK-37874](https://issues.apache.org/jira/browse/FLINK-37874)
+
+Support handling records in order based on upsert key (the unique key in the
input stream deduced by
+planner) while allowing parallel processing of different keys to achieve
better throughput when
+processing changelog data stream.
+
+#### Sink Reuse
+
+##### [FLINK-37227](https://issues.apache.org/jira/browse/FLINK-37227)
+
+Within a single Flink job, when writing multiple `INSERT INTO` statements
updating identical
+columns (different columns will be supported in next release) of a target
table, the planner will
+optimize the execution plan and merge the sink nodes to achieve reuse. This
will be a great
+usability improvement for users using partial-update features with data lake
storages like Apache
+Paimon.
+
+#### Support Smile Format for Compiled Plan Serialization
+
+##### [FLINK-37341](https://issues.apache.org/jira/browse/FLINK-37341)
+
+This release adds smile binary format support for compiled plans, providing a
memory-efficient
+alternative to JSON for serialization/deserialization. By default JSON is
used, in order to use
+smile format need to call `CompiledPlan#asSmileBytes` and
`PlanReference#fromSmileBytes` method.
+
+### Runtime
+
+#### Add Pluggable Batching for Async Sink
+
+##### [FLINK-37298](https://issues.apache.org/jira/browse/FLINK-37298)
+
+Introducing a pluggable batching mechanism for async sink that allows users to
define custom
+batching write strategies tailored to specific requirements.
+
+#### Split-level Watermark Metrics
+
+##### [FLINK-37410](https://issues.apache.org/jira/browse/FLINK-37410)
+
+We adds some split level watermark metrics, covering watermark progress and
per-split state gauges
+to enhance the watermark observability:
+
+- `currentWatermark`: the last watermark this split has received.
+- `activeTimeMsPerSecond`: the time this split is active per second.
+- `pausedTimeMsPerSecond`: the time this split is paused due to watermark
alignment per second.
+- `idleTimeMsPerSecond`: the time this split is marked idle by idleness
detection per second.
+- `accumulatedActiveTimeMs`: accumulated time this split was active since
registered.
+- `accumulatedPausedTimeMs`: accumulated time this split was paused since
registered.
+- `accumulatedIdleTimeMs`: accumulated time this split was idle since
registered.
+
+### Connectors
+
+#### Introduce SQL Connector for Keyed State
+
+##### [FLINK-36929](https://issues.apache.org/jira/browse/FLINK-36929)
+
+In this release, we introduce a new connector for keyed state. This connector
allows
+users to query keyed state directly from checkpoint or savepoint using Flink
SQL, making it easier
+to inspect, debug, and validate the state of Flink jobs without custom
tooling. This feature is
+especially useful for analyzing long-running jobs and validating state
migrations.
+
+### Python
+
+#### Adds support of Python 3.12 and removes support of Python 3.8
+
+##### [FLINK-37823](https://issues.apache.org/jira/browse/FLINK-37823),
[FLINK-37776](https://issues.apache.org/jira/browse/FLINK-37776)
+
+PyFlink 2.1 will support Python 3.12 and remove the support for Python 3.8.
+
+### Dependency upgrades
+
+#### Upgrade flink-shaded version to 20.0
+
+##### [FLINK-37376](https://issues.apache.org/jira/browse/FLINK-37376)
+
+Bump flink-shaded version to 20.0 to support Smile format.
+
+#### Upgrade Parquet version to 1.15.3
+
+##### [FLINK-37760](https://issues.apache.org/jira/browse/FLINK-37760)
+
+Bump parquet version to 1.15.3 to resolve parquet-avro module
+vulnerability found in
[CVE-2025-30065](https://nvd.nist.gov/vuln/detail/CVE-2025-30065).
\ No newline at end of file
