azagrebin commented on a change in pull request #12699: URL: https://github.com/apache/flink/pull/12699#discussion_r442690348
########## File path: docs/release-notes/flink-1.11.md ########## @@ -0,0 +1,246 @@ +--- +title: "Release Notes - Flink 1.11" +--- +<!-- +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. +--> + + +These release notes discuss important aspects, such as configuration, behavior, +or dependencies, that changed between Flink 1.10 and Flink 1.11. Please read +these notes carefully if you are planning to upgrade your Flink version to 1.11. + +* This will be replaced by the TOC +{:toc} + +### Clusters & Deployment +#### Removal of `LegacyScheduler` ([FLINK-15629](https://issues.apache.org/jira/browse/FLINK-15629)) +Flink no longer supports the legacy scheduler. +Hence, setting `jobmanager.scheduler: legacy` will no longer work and fail with an `IllegalArgumentException`. +The only valid option for `jobmanager.scheduler` is the default value `ng`. + +#### Bind user code class loader to lifetime of a slot ([FLINK-16408](https://issues.apache.org/jira/browse/FLINK-16408)) +The user code class loader is being reused by the `TaskExecutor` as long as there is at least a single slot allocated for the respective job. +This changes Flink's recovery behaviour slightly so that it will not reload static fields. +The benefit is that this change drastically reduces pressure on the JVM's metaspace. + +#### Replaced `slave` file name with `workers` ([FLINK-18307](https://issues.apache.org/jira/browse/FLINK-18307)) +For Standalone Setups, the file with the worker nodes is no longer called `slaves` but `workers`. +Previous setups that use the `start-cluster.sh` and `stop-cluster.sh` scripts simply need to rename that file. + +### Memory Management Review comment: ```suggestion ### Memory Management #### New Flink Master Memory Model ##### Overview With [FLIP-116](https://cwiki.apache.org/confluence/display/FLINK/FLIP-116%3A+Unified+Memory+Configuration+for+Job+Managers), a new memory model has been introduced for the Flink Master. New configuration options have been introduced to control the memory consumption of the Flink Master process. This affects all types of deployments: standalone, YARN, Mesos, and the new active Kubernetes integration. Please, check the user documentation for [more details](https://ci.apache.org/projects/flink/flink-docs-master/ops/memory/mem_setup_master.html). If you try to reuse your previous Flink configuration without any adjustments, the new memory model can result in differently computed memory parameters for the JVM and, thus, performance changes or even failures. See also [the migration guide](https://ci.apache.org/projects/flink/flink-docs-master/ops/memory/mem_migration.html#migrate-job-manager-memory-configuration). ##### Deprecation and breaking changes The following options are deprecated: * `jobmanager.heap.size` * `jobmanager.heap.mb` If these deprecated options are still used, they will be interpreted as one of the following new options in order to maintain backwards compatibility: * [JVM Heap](https://ci.apache.org/projects/flink/flink-docs-master/ops/memory/mem_setup_master.html#configure-jvm-heap) ([`jobmanager.memory.heap.size`](https://ci.apache.org/projects/flink/flink-docs-master/ops/config.html#jobmanager-memory-heap-size)) for standalone and Mesos deployments * [Total Process Memory](https://ci.apache.org/projects/flink/flink-docs-master/ops/memory/mem_setup_master.html#configure-total-memory) ([`jobmanager.memory.process.size`](https://ci.apache.org/projects/flink/flink-docs-master/ops/config.html#jobmanager-memory-process-size)) for containerized deployments (Kubernetes and Yarn) The following options have been removed and have no effect anymore: * `containerized.heap-cutoff-ratio` * `containerized.heap-cutoff-min` There is [no container cut-off](https://ci.apache.org/projects/flink/flink-docs-master/ops/memory/mem_migration.html#container-cut-off-memory) anymore. ##### JVM arguments The `direct` and `metaspace` memory of the Flink Master's JVM process are now limited by configurable values: * [`jobmanager.memory.off-heap.size`](https://ci.apache.org/projects/flink/flink-docs-master/ops/config.html#jobmanager-memory-off-heap-size) * [`jobmanager.memory.jvm-metaspace.size`](https://ci.apache.org/projects/flink/flink-docs-master/ops/config.html#jobmanager-memory-jvm-metaspace-size) See also [JVM Parameters](https://ci.apache.org/projects/flink/flink-docs-master/ops/memory/mem_setup.html#jvm-parameters). <span class="label label-warning">Attention</span> These new limits can produce the respective `OutOfMemoryError` exceptions if they are not configured properly or there is a respective memory leak. See also [the troubleshooting guide](https://ci.apache.org/projects/flink/flink-docs-master/ops/memory/mem_trouble.html#outofmemoryerror-direct-buffer-memory). ``` ---------------------------------------------------------------- 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. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
