knaufk commented on a change in pull request #11092: [FLINK-15999] Extract “Concepts” material from API/Library sections and start proper concepts section URL: https://github.com/apache/flink/pull/11092#discussion_r379560406
########## File path: docs/concepts/stateful-stream-processing.md ########## @@ -0,0 +1,412 @@ +--- +title: Stateful Stream Processing +nav-id: stateful-stream-processing +nav-pos: 2 +nav-title: Stateful Stream Processing +nav-parent_id: concepts +--- +<!-- +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. +--> + +While many operations in a dataflow simply look at one individual *event at a +time* (for example an event parser), some operations remember information +across multiple events (for example window operators). These operations are +called **stateful**. + +Stateful functions and operators store data across the processing of individual +elements/events, making state a critical building block for any type of more +elaborate operation. + +For example: + + - When an application searches for certain event patterns, the state will + store the sequence of events encountered so far. + - When aggregating events per minute/hour/day, the state holds the pending + aggregates. + - When training a machine learning model over a stream of data points, the + state holds the current version of the model parameters. + - When historic data needs to be managed, the state allows efficient access + to events that occurred in the past. + +Flink needs to be aware of the state in order to make state fault tolerant +using [checkpoints]({{ site.baseurl}}{% link dev/stream/state/checkpointing.md +%}) and to allow [savepoints]({{ site.baseurl }}{%link ops/state/savepoints.md +%}) of streaming applications. + +Knowledge about the state also allows for rescaling Flink applications, meaning +that Flink takes care of redistributing state across parallel instances. + +The [queryable state]({{ site.baseurl }}{% link +dev/stream/state/queryable_state.md %}) feature of Flink allows you to access +state from outside of Flink during runtime. + +When working with state, it might also be useful to read about [Flink's state +backends]({{ site.baseurl }}{% link ops/state/state_backends.md %}). Flink +provides different state backends that specify how and where state is stored. +State can be located on Java's heap or off-heap. Depending on your state +backend, Flink can also *manage* the state for the application, meaning Flink +deals with the memory management (possibly spilling to disk if necessary) to +allow applications to hold very large state. State backends can be configured +without changing your application logic. + +* This will be replaced by the TOC +{:toc} + +## What is State? + +`TODO: expand this section` + +There are different types of state in Flink, the most-used type of state is +*Keyed State*. For special cases you can use *Operator State* and *Broadcast +State*. *Broadcast State* is a special type of *Operator State*. + +{% top %} + +## State in Stream & Batch Processing Review comment: As far as I remember, this was supposed to be about the conceptual differences between state handling in batch and stream processing. I don't remember exactly, what we talked about here. The only thing I can think of right now is, that the data structures in which state is stored need to be different in batch and stream processing for it to be efficient. I guess one could also say something about boundedness and expiry of state? @StephanEwen what did we have in mind here? ---------------------------------------------------------------- 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 With regards, Apache Git Services
