snuyanzin commented on code in PR #597: URL: https://github.com/apache/flink-web/pull/597#discussion_r1114158664
########## docs/content/roadmap.md: ########## @@ -0,0 +1,203 @@ +--- +title: Roadmap +bookCollapseSection: false +weight: 15 +menu_weight: 3 +--- +<!-- +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. +--> + +# Roadmap + +**Preamble:** This roadmap means to provide user and contributors with a high-level summary of ongoing efforts, +grouped by the major threads to which the efforts belong. With so much that is happening in Flink, we +hope that this helps with understanding the direction of the project. +The roadmap contains both efforts in early stages as well as nearly completed +efforts, so that users may get a better impression of the overall status and direction of those developments. + +More details and various smaller changes can be found in the +[FLIPs](https://cwiki.apache.org/confluence/display/FLINK/Flink+Improvement+Proposals) + +The roadmap is continuously updated. New features and efforts should be added to the roadmap once +there is consensus that they will happen and what they will roughly look like for the user. + +**Last Update:** 2022-11-14 + +## Feature Radar + +The feature radar is meant to give users guidance regarding feature maturity, as well as which features +are approaching end-of-life. For questions, please contact the developer mailing list: +[[email protected]](mailto:[email protected]) + +<div class="row front-graphic"> + {{< img src="/img/flink_feature_radar_3.svg" width="700px" >}} +</div> + +#### Feature Stages + +- **MVP:** Have a look, consider whether this can help you in the future. +- **Beta:** You can benefit from this, but you should carefully evaluate the feature. +- **Ready and Evolving:** Ready to use in production, but be aware you may need to make some adjustments to your application and setup in the future, when you upgrade Flink. +- **Stable:** Unrestricted use in production +- **Reaching End-of-Life:** Stable, still feel free to use, but think about alternatives. Not a good match for new long-lived projects. +- **Deprecated:** Start looking for alternatives now + +### Unified Analytics: Where Batch and Streaming come Together; SQL and beyond. + +Flink is a streaming data system in its core, that executes "batch as a special case of streaming". +Efficient execution of batch jobs is powerful in its own right; but even more so, batch processing +capabilities (efficient processing of bounded streams) open the way for a seamless unification of +batch and streaming applications. + +Unified streaming/batch up-levels the streaming data paradigm: It gives users consistent semantics across +their real-time and lag-time applications. Furthermore, streaming applications often need to be complemented +by batch (bounded stream) processing, for example when reprocessing data after bugs or data quality issues, +or when bootstrapping new applications. A unified API and system make this much easier. + +### A unified SQL Platform + +The community has been building Flink to a powerful basis for a unified (batch and streaming) SQL analytics +platform, and is continuing to do so. + +SQL has very strong cross-batch-streaming semantics, allowing users to use the same queries for ad-hoc analytics +and as continuous queries. Flink already contains an efficient unified query engine, and a wide set of +integrations. With user feedback, those are continuously improved. + +**Going Beyond a SQL Stream/Batch Processing Engine** + +- To extend the capability of a pure stream processor and make Flink ready for future use cases, + [FLIP-188](https://cwiki.apache.org/confluence/display/FLINK/FLIP-188%3A+Introduce+Built-in+Dynamic+Table+Storage) + has been announced adding built in dynamic table storage. +- The experience of updating Flink SQL based jobs has been rather cumbersome as it could have + lead to new job graphs making restoring from savepoints/checkpoints impossible. + [FLIP-190](https://cwiki.apache.org/confluence/pages/viewpage.action?pageId=191336489&src=contextnavpagetreemode) + that already has been shipped as MVP is targeting this. + + +**Platform Infrastructure** + +- After [FLIP-163](https://cwiki.apache.org/confluence/display/FLINK/FLIP-163%3A+SQL+Client+Improvements) + the community is working again on a set of SQL Client usability improvements + ([FLIP-189](https://cwiki.apache.org/confluence/display/FLINK/FLIP-189%3A+SQL+Client+Usability+Improvements)) + which is aiming at improving the user experience, when using the SQL client. + +**Support for Common Languages, Formats, Catalogs** + +- With [FLIP-216](https://cwiki.apache.org/confluence/display/FLINK/FLIP-216%3A++Introduce+pluggable+dialect+and++decouple+Hive+connector) + there's now the initiative to introduce pluggable dialects on the example of the Hive connector. + Including so many dependencies to make dialects work has lead to an overhead for contributors + and users. + +Flink has a broad SQL coverage for batch (full TPC-DS support) and a state-of-the-art set of supported +operations in streaming. There is continuous effort to add more functions and cover more SQL operations. + +### Deep Batch / Streaming Unification for the DataStream API + +The *DataStream API* is Flink's *physical* API, for use cases where users need very explicit control over data +types, streams, state, and time. This API is evolving to support efficient batch execution on bounded data. + +DataStream API executes the same dataflow shape in batch as in streaming, keeping the same operators. +That way users keep the same level of control over the dataflow, and our goal is to mix and switch between +batch/streaming execution in the future to make it a seamless experience. + +**Unified Sources and Sinks** + +- The first APIs and implementations of sources were specific to either streaming programs in the DataStream API + ([SourceFunction](https://github.com/apache/flink/blob/master/flink-streaming-java/src/main/java/org/apache/flink/streaming/api/functions/source/SourceFunction.java)), + or to batch programs in the DataSet API ([InputFormat](https://github.com/apache/flink/blob/master/flink-core/src/main/java/org/apache/flink/api/common/io/InputFormat.java)). + + In this effort, we are creating sources that work across batch and streaming execution. The aim is to give + users a consistent experience across both modes, and to allow them to easily switch between streaming and batch + execution for their unbounded and bounded streaming applications. + The interface for this New Source API is done and available, and we are working on migrating more source connectors + to this new model, see [FLIP-27](https://cwiki.apache.org/confluence/display/FLINK/FLIP-27%3A+Refactor+Source+Interface). + +- Similar to the sources, the original sink APIs are also specific to streaming + ([SinkFunction](https://github.com/apache/flink/blob/master/flink-streaming-java/src/main/java/org/apache/flink/streaming/api/functions/sink/SinkFunction.java)) + and batch ([OutputFormat](https://github.com/apache/flink/blob/master/flink-core/src/main/java/org/apache/flink/api/common/io/OutputFormat.java)) + APIs and execution. + + We have introduced a new API for sinks that consistently handles result writing and committing (*Transactions*) + across batch and streaming. The first iteration of the API exists, and we are porting sinks and refining the + API in the process. See [FLIP-143](https://cwiki.apache.org/confluence/display/FLINK/FLIP-143%3A+Unified+Sink+API). + +### Applications vs. Clusters; "Flink as a Library" + +The goal of these efforts is to make it feel natural to deploy (long running streaming) Flink applications. +Instead of starting a cluster and submitting a job to that cluster, these efforts support deploying a streaming +job as a self contained application. + +For example as a simple Kubernetes deployment; deployed and scaled like a regular application without extra workflows. + +- There is currently a Kubernetes Operator being developed by the community. See + [FLIP-212](https://cwiki.apache.org/confluence/display/FLINK/FLIP-212%3A+Introduce+Flink+Kubernetes+Operator). + +### Performance + +Continuous work to keep improving performance and recovery speed. + +### Faster Checkpoints and Recovery + +The community is continuously working on improving checkpointing and recovery speed. +Checkpoints and recovery are stable and have been a reliable workhorse for years. We are still +trying to make it faster, more predictable, and to remove some confusions and inflexibility in some areas. + +- [FLIP-183](https://cwiki.apache.org/confluence/display/FLINK/FLIP-183%3A+Dynamic+buffer+size+adjustment) + is targeting size of checkpoints by debloating the buffers. A first beta is already available. +- With [FLIP-151](https://cwiki.apache.org/confluence/display/FLINK/FLIP-151%3A+Incremental+snapshots+for+heap-based+state+backend) + there is an ongoing effort to implement a heap based state backend. + +### Apache Flink as part of an ever evolving data ecosystem + +There is almost no use case in which Apache Flink is used on its own. It has established itself +as part of many data related reference architectures. In fact you'll find the squirrel logo covering +several aspects. + +The community has added a lot of connectors and formats. With the already mentionend Review Comment: ```suggestion The community has added a lot of connectors and formats. With the already mentioned ``` -- 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. 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