This is an automated email from the ASF dual-hosted git repository.
renqs pushed a commit to branch release-1.17
in repository https://gitbox.apache.org/repos/asf/flink.git
The following commit(s) were added to refs/heads/release-1.17 by this push:
new 2a38aab5171 [FLINK-31157][release] Add release note for version 1.17
2a38aab5171 is described below
commit 2a38aab51715b7b4be6d9293eb7574bc908dc2e4
Author: Qingsheng Ren <[email protected]>
AuthorDate: Thu Mar 23 14:26:03 2023 +0800
[FLINK-31157][release] Add release note for version 1.17
---
docs/content.zh/_index.md | 12 +-
docs/content.zh/release-notes/flink-1.17.md | 213 ++++++++++++++++++++++++++++
docs/content/_index.md | 13 +-
docs/content/release-notes/flink-1.17.md | 213 ++++++++++++++++++++++++++++
4 files changed, 449 insertions(+), 2 deletions(-)
diff --git a/docs/content.zh/_index.md b/docs/content.zh/_index.md
index 48a6ae7d6ec..6ce0a0ab091 100644
--- a/docs/content.zh/_index.md
+++ b/docs/content.zh/_index.md
@@ -85,7 +85,17 @@ 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 1.16]({{< ref "/release-notes/flink-1.16.md" >}}), [Flink 1.15]({{<
ref "/release-notes/flink-1.15.md" >}}), [Flink 1.14]({{< ref
"/release-notes/flink-1.14.md" >}}), [Flink 1.13]({{< ref
"/release-notes/flink-1.13.md" >}}), [Flink 1.12]({{< ref
"/release-notes/flink-1.12.md" >}})，[Flink 1.11]({{< ref
"/release-notes/flink-1.11.md" >}})，[Flink 1.10]({{< ref
"/release-notes/flink-1.10.md" >}})，[Flink 1.9]({{< ref
"/release-notes/flink-1.9.md" >}})，[Flink 1.8]({{< ref "/release- [...]
+请参阅 [Flink 1.17]({{< ref "/release-notes/flink-1.17.md" >}})，
+[Flink 1.16]({{< ref "/release-notes/flink-1.16.md" >}})，
+[Flink 1.15]({{< ref "/release-notes/flink-1.15.md" >}})，
+[Flink 1.14]({{< ref "/release-notes/flink-1.14.md" >}})，
+[Flink 1.13]({{< ref "/release-notes/flink-1.13.md" >}})，
+[Flink 1.12]({{< ref "/release-notes/flink-1.12.md" >}})，
+[Flink 1.11]({{< ref "/release-notes/flink-1.11.md" >}})，
+[Flink 1.10]({{< ref "/release-notes/flink-1.10.md" >}})，
+[Flink 1.9]({{< ref "/release-notes/flink-1.9.md" >}})，
+[Flink 1.8]({{< ref "/release-notes/flink-1.8.md" >}})，或者
+[Flink 1.7]({{< ref "/release-notes/flink-1.7.md" >}}) 的发行说明。
{{< /columns >}}
diff --git a/docs/content.zh/release-notes/flink-1.17.md
b/docs/content.zh/release-notes/flink-1.17.md
new file mode 100644
index 00000000000..5b3f3437cd5
--- /dev/null
+++ b/docs/content.zh/release-notes/flink-1.17.md
@@ -0,0 +1,213 @@
+---
+title: "Release Notes - Flink 1.17"
+---
+<!--
+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 1.17
+
+These release notes discuss important aspects, such as configuration, behavior
or dependencies,
+that changed between Flink 1.16 and Flink 1.17. Please read these notes
carefully if you are
+planning to upgrade your Flink version to 1.17.
+
+
+### Clusters & Deployment
+
+#### Only one Zookeeper version is bundled in `flink-dist`
+##### [FLINK-30237](https://issues.apache.org/jira/browse/FLINK-30237)
+The Flink distribution no longer bundles 2 different Zookeeper client jars
(one in lib, one in lib/opt
+respectively). Instead, only 1 client will be bundled within the flink-dist
jar. This has no
+effect on the supported Zookeeper server versions.
+
+
+### Table API & SQL
+
+#### Incompatible plan change of event time temporal join on an upsert source
+##### [FLINK-29849](https://issues.apache.org/jira/browse/FLINK-29849)
+A correctness issue when do event time temporal join with a versioned table
backed by an upsert
+source was resolved. When the right input of the join is an upsert source, it
no longer generates
+a ChangelogNormalize node for it. This is an incompatible plan change compared
to 1.16.0.
+
+#### Incompatible plan change of filter after temporal join
+##### [FLINK-28988](https://issues.apache.org/jira/browse/FLINK-28988)
+After the patch is applied, the filter will no longer be pushed down into both
inputs of the event time
+temporal join. Note this may cause incompatible plan changes compared to
1.16.0, e.g., when left
+input is an upsert source (use upsert-kafka connector), the query plan will
remove the
+ChangelogNormalize node which appeared in 1.16.0.
+
+### Connectors & Libraries
+
+#### Remove cassandra connector from master branch
+##### [FLINK-30312](https://issues.apache.org/jira/browse/FLINK-30312)
+The Cassandra connector has been externalized and is no longer released as
part of the main Flink
+release. Downloads can be found at https://flink.apache.org/downloads.html and
the
+source code at https://github.com/apache/flink-connector-cassandra.
+
+#### Remove Pulsar connector from master branch
+##### [FLINK-30397](https://issues.apache.org/jira/browse/FLINK-30397)
+The Pulsar connector has been externalized and is no longer bundled and
released as part of the
+main Flink release. Downloads can be found at
https://flink.apache.org/downloads.html and the
+source code at https://github.com/apache/flink-connector-pulsar.
+
+#### Remove HCatalog
+##### [FLINK-29669](https://issues.apache.org/jira/browse/FLINK-29669)
+The HCatalog connector has been removed from Flink. You can use the Hive
connector as a replacement.
+
+#### Remove Gelly
+##### [FLINK-29668](https://issues.apache.org/jira/browse/FLINK-29668)
+Gelly has been removed from Flink. Current users of Gelly should not upgrade
to Flink 1.17 but
+stay on an older version. If you're looking for iterations support, you could
investigate
+[Flink ML
Iteration](https://nightlies.apache.org/flink/flink-ml-docs-stable/docs/development/iteration/)
+as a potential successor.
+
+#### Support watermark alignment of source splits
+##### [FLINK-28853](https://issues.apache.org/jira/browse/FLINK-28853)
+Since Flink 1.17, source connectors have to implement watermark alignment of
source split in order
+to use the watermark alignment feature. The required methods to implement are:
+`SourceReader#pauseOrResumeSplits` and `SplitReader#pauseOrResumeSplits`.
+
+If you are migrating from
+Flink <= 1.16.x, and you are using watermark alignment, but at the same time
you are not able to
+upgrade/modify your connector, you can disable per split alignment via setting
+`pipeline.watermark-alignment.allow-unaligned-source-splits` to true. Note
that by doing so,
+watermark alignment will be working properly only when your number of splits
equals to the
+parallelism of the source operator.
+
+#### Remove deprecated MiniClusterResource
+##### [FLINK-29548](https://issues.apache.org/jira/browse/FLINK-29548)
+The deprecated `MiniClusterResource` in `flink-test-utils` has been removed.
The
+`MiniClusterWithClientResource` is a drop-in replacement.
+
+#### Kinesis connector doesn't shade jackson dependency
+##### [FLINK-14896](https://issues.apache.org/jira/browse/FLINK-14896)
+Kinesis connector now shades and relocates transitive Jackson dependencies of
`flink-connector-kinesis`. If your Flink job
+was transitively relying on the these, you may need to include additional
Jackson dependencies into
+your project.
+
+### Runtime & Coordination
+
+#### Speculative execution take input data amount into account when detecting
slow tasks
+##### [FLINK-30707](https://issues.apache.org/jira/browse/FLINK-30707)
+The slow task detecting is improved for speculative execution. Previously, it
only considered the
+execution time of tasks when deciding which tasks are slow. It now takes the
input data volume of
+tasks into account. Tasks which have a longer execution time but consumes more
data may not be
+considered as slow. This improvement helps to eliminate the negative impacts
of data skew on slow
+task detecting.
+
+#### Use adaptive batch scheduler as default scheduler for batch jobs
+##### [FLINK-30682](https://issues.apache.org/jira/browse/FLINK-30682)
+Adaptive batch scheduler is now used for batch jobs by default. It will
automatically decide the
+parallelism of operators. The keys and values of related configuration items
are improved for ease
+of use. More details can be found in the
+[document](https://nightlies.apache.org/flink/flink-docs-release-1.17/docs/deployment/elastic_scaling/#adaptive-batch-scheduler).
+
+#### Simplify network memory configurations for TaskManager
+##### [FLINK-30469](https://issues.apache.org/jira/browse/FLINK-30469)
+The default value of `taskmanager.memory.network.max` has changed from `1g` to
`Long#MAX_VALUE`,
+to reduce the number of config options the user needs to tune when trying to
increase the network
+memory size. This may affect the performance when this option is not
explicitly configured, due to
+potential changes of network memory size, heap and managed memory size when
the total memory
+size is fixed. To go back to the previous behavior, the user can explicitly
configure this option to
+the previous default value of `1g`.
+
+A threshold is introduced for controlling the number of required buffers among
all buffers needed
+for reading data from upstream tasks. Reducing the number of required buffers
helps reduce the
+chance of failures due to insufficient network buffers, at the price of
potential performance
+impact. By default, the number of required buffers is only reduced for batch
workloads, while stay
+unchanged for streaming workloads. This can be tuned via
+`taskmanager.network.memory.read-buffer.required-per-gate.max`. See the
description of the config
+option for more details.
+
+### Metric Reporters
+
+#### Only support reporter factories for instantiation
+##### [FLINK-24235](https://issues.apache.org/jira/browse/FLINK-24235)
+Configuring reporters by their class is no longer supported. Reporter
implementations must provide
+a MetricReporterFactory, and all configurations must be migrated to such a
factory.
+
+#### `UseLogicalIdentifier` makes datadog consider metric as custom
+##### [FLINK-30383](https://issues.apache.org/jira/browse/FLINK-30383)
+The Datadog reporter now adds a "flink." prefix to metric identifiers if
"useLogicalIdentifier" is
+enabled. This is required for these metrics to be recognized as Flink metrics,
not custom ones.
+
+#### Use separate Prometheus CollectorRegistries
+##### [FLINK-30020](https://issues.apache.org/jira/browse/FLINK-30020)
+The PrometheusReporters now use a separate CollectorRegistry for each reporter
instance instead of
+the singleton default registry. This generally shouldn't impact setups, but it
may break code that
+indirectly interacts with the reporter via the singleton instance (e.g., a
test trying to assert
+what metrics are reported).
+
+### Checkpoints
+
+#### Drop TypeSerializerConfigSnapshot and savepoint support from Flink
versions < 1.8.0
+##### [FLINK-29807](https://issues.apache.org/jira/browse/FLINK-29807)
+Savepoints using `TypeSerializerConfigSnapshot` are no longer supported. That
means that all savepoints
+from Flink < 1.8.0 are no longer supported. Furthermore, savepoints from Flink
< 1.17.0 created
+with custom serializer using deprecated since Flink 1.8.0 class
`TypeSerializerConfigSnapshot` are
+also no longer supported.
+
+If you are only using built-in serializers (Pojo, Kryo, Avro,
+Tuple, ...), and your savepoint is from Flink >= 1.8.0, you don't have to do
anything.
+
+If you are only using built-in serializers (Pojo, Kryo, Avro, Tuple, ...), and
your savepoint is
+from Flink < 1.8.0, please first upgrade your job to 1.8.x <= Flink <= 1.16.x,
before upgrading in
+a second step to Flink >= 1.17.x.
+
+If previously you were using a custom serializer that depends on
`TypeSerializerConfigSnapshot`,
+please upgrade your serializer to `TypeSerializerSnapshot` while still using
1.8.x <= Flink <= 1.16.x,
+take a savepoint and restore from that savepoint in Flink >= 1.7.0.
+
+### Python
+
+#### Remove duplicated operators in the StreamGraph for Python DataStream API
jobs
+##### [FLINK-31272](https://issues.apache.org/jira/browse/FLINK-31272)
+This duplicated operator issue has been addressed since 1.15.4, 1.16.2 and
1.17.0. For jobs which
+are not affected by this issue, there are no backward compatibility issues.
However, for jobs which
+are affected, it may not be possible to restore from savepoints generated from
versions
+1.15.0 ~ 1.15.3 and 1.16.0 ~ 1.16.1.
+
+#### Adds support of Python 3.10 and removes support of Python 3.6
+##### [FLINK-29421](https://issues.apache.org/jira/browse/FLINK-29421)
+PyFlink 1.17 will support Python 3.10 and remove the support of Python 3.6.
+
+### Dependency upgrades
+
+#### Upgrade FRocksDB to 6.20.3-ververica-2.0
+##### [FLINK-30836](https://issues.apache.org/jira/browse/FLINK-30836)
+Upgrade FRocksDB to 6.20.3-ververica-2.0.
+
+#### Upgrade the minimal supported hadoop version to 2.10.2
+##### [FLINK-29710](https://issues.apache.org/jira/browse/FLINK-29710)
+The minimum Hadoop version supported by Apache Flink has been updated to
version 2.10.2. For Hadoop
+3, the minimum Hadoop version that is now supported is version 3.2.3.
+
+#### Upgrade Calcite version to 1.29.0
+##### [FLINK-20873](https://issues.apache.org/jira/browse/FLINK-20873)
+##### [FLINK-21239](https://issues.apache.org/jira/browse/FLINK-21239)
+##### [FLINK-29932](https://issues.apache.org/jira/browse/FLINK-29932)
+Calcite upgrade brings optimizations that change logical plans for some
queries involving `Sarg` and
+queries with `count` of non-distinct values. Please note that the execution
plan changes for
+certain SQL queries after the upgrade, so savepoints are not backward
compatible in these cases.
+
+#### Update dependency versions for PyFlink
+##### [FLINK-29421](https://issues.apache.org/jira/browse/FLINK-29421)
+For support of Python 3.10, PyFlink updates some dependencies:
+- apache-beam: 2.43.0
+- pemja: 0.3.0
+- cloudpickle: 2.2.0
diff --git a/docs/content/_index.md b/docs/content/_index.md
index ee2d4545484..30e64fe67fb 100644
--- a/docs/content/_index.md
+++ b/docs/content/_index.md
@@ -85,7 +85,18 @@ Release notes cover important changes between Flink
versions. Please read them c
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 1.16]({{< ref "/release-notes/flink-1.16.md"
>}}), [Flink 1.15]({{< ref "/release-notes/flink-1.15.md" >}}), [Flink
1.14]({{< ref "/release-notes/flink-1.14.md" >}}), [Flink 1.13]({{< ref
"/release-notes/flink-1.13.md" >}}), [Flink 1.12]({{< ref
"/release-notes/flink-1.12.md" >}}), [Flink 1.11]({{< ref
"/release-notes/flink-1.11.md" >}}), [Flink 1.10]({{< ref
"/release-notes/flink-1.10.md" >}}), [Flink 1.9]({{< ref
"/release-notes/flink-1.9.md" >}}), [Fli [...]
+See the release notes for
+[Flink 1.17]({{< ref "/release-notes/flink-1.17.md" >}}),
+[Flink 1.16]({{< ref "/release-notes/flink-1.16.md" >}}),
+[Flink 1.15]({{< ref "/release-notes/flink-1.15.md" >}}),
+[Flink 1.14]({{< ref "/release-notes/flink-1.14.md" >}}),
+[Flink 1.13]({{< ref "/release-notes/flink-1.13.md" >}}),
+[Flink 1.12]({{< ref "/release-notes/flink-1.12.md" >}}),
+[Flink 1.11]({{< ref "/release-notes/flink-1.11.md" >}}),
+[Flink 1.10]({{< ref "/release-notes/flink-1.10.md" >}}),
+[Flink 1.9]({{< ref "/release-notes/flink-1.9.md" >}}),
+[Flink 1.8]({{< ref "/release-notes/flink-1.8.md" >}}), or
+[Flink 1.7]({{< ref "/release-notes/flink-1.7.md" >}}).
{{< /columns >}}
diff --git a/docs/content/release-notes/flink-1.17.md
b/docs/content/release-notes/flink-1.17.md
new file mode 100644
index 00000000000..5b3f3437cd5
--- /dev/null
+++ b/docs/content/release-notes/flink-1.17.md
@@ -0,0 +1,213 @@
+---
+title: "Release Notes - Flink 1.17"
+---
+<!--
+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 1.17
+
+These release notes discuss important aspects, such as configuration, behavior
or dependencies,
+that changed between Flink 1.16 and Flink 1.17. Please read these notes
carefully if you are
+planning to upgrade your Flink version to 1.17.
+
+
+### Clusters & Deployment
+
+#### Only one Zookeeper version is bundled in `flink-dist`
+##### [FLINK-30237](https://issues.apache.org/jira/browse/FLINK-30237)
+The Flink distribution no longer bundles 2 different Zookeeper client jars
(one in lib, one in lib/opt
+respectively). Instead, only 1 client will be bundled within the flink-dist
jar. This has no
+effect on the supported Zookeeper server versions.
+
+
+### Table API & SQL
+
+#### Incompatible plan change of event time temporal join on an upsert source
+##### [FLINK-29849](https://issues.apache.org/jira/browse/FLINK-29849)
+A correctness issue when do event time temporal join with a versioned table
backed by an upsert
+source was resolved. When the right input of the join is an upsert source, it
no longer generates
+a ChangelogNormalize node for it. This is an incompatible plan change compared
to 1.16.0.
+
+#### Incompatible plan change of filter after temporal join
+##### [FLINK-28988](https://issues.apache.org/jira/browse/FLINK-28988)
+After the patch is applied, the filter will no longer be pushed down into both
inputs of the event time
+temporal join. Note this may cause incompatible plan changes compared to
1.16.0, e.g., when left
+input is an upsert source (use upsert-kafka connector), the query plan will
remove the
+ChangelogNormalize node which appeared in 1.16.0.
+
+### Connectors & Libraries
+
+#### Remove cassandra connector from master branch
+##### [FLINK-30312](https://issues.apache.org/jira/browse/FLINK-30312)
+The Cassandra connector has been externalized and is no longer released as
part of the main Flink
+release. Downloads can be found at https://flink.apache.org/downloads.html and
the
+source code at https://github.com/apache/flink-connector-cassandra.
+
+#### Remove Pulsar connector from master branch
+##### [FLINK-30397](https://issues.apache.org/jira/browse/FLINK-30397)
+The Pulsar connector has been externalized and is no longer bundled and
released as part of the
+main Flink release. Downloads can be found at
https://flink.apache.org/downloads.html and the
+source code at https://github.com/apache/flink-connector-pulsar.
+
+#### Remove HCatalog
+##### [FLINK-29669](https://issues.apache.org/jira/browse/FLINK-29669)
+The HCatalog connector has been removed from Flink. You can use the Hive
connector as a replacement.
+
+#### Remove Gelly
+##### [FLINK-29668](https://issues.apache.org/jira/browse/FLINK-29668)
+Gelly has been removed from Flink. Current users of Gelly should not upgrade
to Flink 1.17 but
+stay on an older version. If you're looking for iterations support, you could
investigate
+[Flink ML
Iteration](https://nightlies.apache.org/flink/flink-ml-docs-stable/docs/development/iteration/)
+as a potential successor.
+
+#### Support watermark alignment of source splits
+##### [FLINK-28853](https://issues.apache.org/jira/browse/FLINK-28853)
+Since Flink 1.17, source connectors have to implement watermark alignment of
source split in order
+to use the watermark alignment feature. The required methods to implement are:
+`SourceReader#pauseOrResumeSplits` and `SplitReader#pauseOrResumeSplits`.
+
+If you are migrating from
+Flink <= 1.16.x, and you are using watermark alignment, but at the same time
you are not able to
+upgrade/modify your connector, you can disable per split alignment via setting
+`pipeline.watermark-alignment.allow-unaligned-source-splits` to true. Note
that by doing so,
+watermark alignment will be working properly only when your number of splits
equals to the
+parallelism of the source operator.
+
+#### Remove deprecated MiniClusterResource
+##### [FLINK-29548](https://issues.apache.org/jira/browse/FLINK-29548)
+The deprecated `MiniClusterResource` in `flink-test-utils` has been removed.
The
+`MiniClusterWithClientResource` is a drop-in replacement.
+
+#### Kinesis connector doesn't shade jackson dependency
+##### [FLINK-14896](https://issues.apache.org/jira/browse/FLINK-14896)
+Kinesis connector now shades and relocates transitive Jackson dependencies of
`flink-connector-kinesis`. If your Flink job
+was transitively relying on the these, you may need to include additional
Jackson dependencies into
+your project.
+
+### Runtime & Coordination
+
+#### Speculative execution take input data amount into account when detecting
slow tasks
+##### [FLINK-30707](https://issues.apache.org/jira/browse/FLINK-30707)
+The slow task detecting is improved for speculative execution. Previously, it
only considered the
+execution time of tasks when deciding which tasks are slow. It now takes the
input data volume of
+tasks into account. Tasks which have a longer execution time but consumes more
data may not be
+considered as slow. This improvement helps to eliminate the negative impacts
of data skew on slow
+task detecting.
+
+#### Use adaptive batch scheduler as default scheduler for batch jobs
+##### [FLINK-30682](https://issues.apache.org/jira/browse/FLINK-30682)
+Adaptive batch scheduler is now used for batch jobs by default. It will
automatically decide the
+parallelism of operators. The keys and values of related configuration items
are improved for ease
+of use. More details can be found in the
+[document](https://nightlies.apache.org/flink/flink-docs-release-1.17/docs/deployment/elastic_scaling/#adaptive-batch-scheduler).
+
+#### Simplify network memory configurations for TaskManager
+##### [FLINK-30469](https://issues.apache.org/jira/browse/FLINK-30469)
+The default value of `taskmanager.memory.network.max` has changed from `1g` to
`Long#MAX_VALUE`,
+to reduce the number of config options the user needs to tune when trying to
increase the network
+memory size. This may affect the performance when this option is not
explicitly configured, due to
+potential changes of network memory size, heap and managed memory size when
the total memory
+size is fixed. To go back to the previous behavior, the user can explicitly
configure this option to
+the previous default value of `1g`.
+
+A threshold is introduced for controlling the number of required buffers among
all buffers needed
+for reading data from upstream tasks. Reducing the number of required buffers
helps reduce the
+chance of failures due to insufficient network buffers, at the price of
potential performance
+impact. By default, the number of required buffers is only reduced for batch
workloads, while stay
+unchanged for streaming workloads. This can be tuned via
+`taskmanager.network.memory.read-buffer.required-per-gate.max`. See the
description of the config
+option for more details.
+
+### Metric Reporters
+
+#### Only support reporter factories for instantiation
+##### [FLINK-24235](https://issues.apache.org/jira/browse/FLINK-24235)
+Configuring reporters by their class is no longer supported. Reporter
implementations must provide
+a MetricReporterFactory, and all configurations must be migrated to such a
factory.
+
+#### `UseLogicalIdentifier` makes datadog consider metric as custom
+##### [FLINK-30383](https://issues.apache.org/jira/browse/FLINK-30383)
+The Datadog reporter now adds a "flink." prefix to metric identifiers if
"useLogicalIdentifier" is
+enabled. This is required for these metrics to be recognized as Flink metrics,
not custom ones.
+
+#### Use separate Prometheus CollectorRegistries
+##### [FLINK-30020](https://issues.apache.org/jira/browse/FLINK-30020)
+The PrometheusReporters now use a separate CollectorRegistry for each reporter
instance instead of
+the singleton default registry. This generally shouldn't impact setups, but it
may break code that
+indirectly interacts with the reporter via the singleton instance (e.g., a
test trying to assert
+what metrics are reported).
+
+### Checkpoints
+
+#### Drop TypeSerializerConfigSnapshot and savepoint support from Flink
versions < 1.8.0
+##### [FLINK-29807](https://issues.apache.org/jira/browse/FLINK-29807)
+Savepoints using `TypeSerializerConfigSnapshot` are no longer supported. That
means that all savepoints
+from Flink < 1.8.0 are no longer supported. Furthermore, savepoints from Flink
< 1.17.0 created
+with custom serializer using deprecated since Flink 1.8.0 class
`TypeSerializerConfigSnapshot` are
+also no longer supported.
+
+If you are only using built-in serializers (Pojo, Kryo, Avro,
+Tuple, ...), and your savepoint is from Flink >= 1.8.0, you don't have to do
anything.
+
+If you are only using built-in serializers (Pojo, Kryo, Avro, Tuple, ...), and
your savepoint is
+from Flink < 1.8.0, please first upgrade your job to 1.8.x <= Flink <= 1.16.x,
before upgrading in
+a second step to Flink >= 1.17.x.
+
+If previously you were using a custom serializer that depends on
`TypeSerializerConfigSnapshot`,
+please upgrade your serializer to `TypeSerializerSnapshot` while still using
1.8.x <= Flink <= 1.16.x,
+take a savepoint and restore from that savepoint in Flink >= 1.7.0.
+
+### Python
+
+#### Remove duplicated operators in the StreamGraph for Python DataStream API
jobs
+##### [FLINK-31272](https://issues.apache.org/jira/browse/FLINK-31272)
+This duplicated operator issue has been addressed since 1.15.4, 1.16.2 and
1.17.0. For jobs which
+are not affected by this issue, there are no backward compatibility issues.
However, for jobs which
+are affected, it may not be possible to restore from savepoints generated from
versions
+1.15.0 ~ 1.15.3 and 1.16.0 ~ 1.16.1.
+
+#### Adds support of Python 3.10 and removes support of Python 3.6
+##### [FLINK-29421](https://issues.apache.org/jira/browse/FLINK-29421)
+PyFlink 1.17 will support Python 3.10 and remove the support of Python 3.6.
+
+### Dependency upgrades
+
+#### Upgrade FRocksDB to 6.20.3-ververica-2.0
+##### [FLINK-30836](https://issues.apache.org/jira/browse/FLINK-30836)
+Upgrade FRocksDB to 6.20.3-ververica-2.0.
+
+#### Upgrade the minimal supported hadoop version to 2.10.2
+##### [FLINK-29710](https://issues.apache.org/jira/browse/FLINK-29710)
+The minimum Hadoop version supported by Apache Flink has been updated to
version 2.10.2. For Hadoop
+3, the minimum Hadoop version that is now supported is version 3.2.3.
+
+#### Upgrade Calcite version to 1.29.0
+##### [FLINK-20873](https://issues.apache.org/jira/browse/FLINK-20873)
+##### [FLINK-21239](https://issues.apache.org/jira/browse/FLINK-21239)
+##### [FLINK-29932](https://issues.apache.org/jira/browse/FLINK-29932)
+Calcite upgrade brings optimizations that change logical plans for some
queries involving `Sarg` and
+queries with `count` of non-distinct values. Please note that the execution
plan changes for
+certain SQL queries after the upgrade, so savepoints are not backward
compatible in these cases.
+
+#### Update dependency versions for PyFlink
+##### [FLINK-29421](https://issues.apache.org/jira/browse/FLINK-29421)
+For support of Python 3.10, PyFlink updates some dependencies:
+- apache-beam: 2.43.0
+- pemja: 0.3.0
+- cloudpickle: 2.2.0
