knaufk commented on a change in pull request #8607: [FLINK-12652] [documentation] add first version of a glossary URL: https://github.com/apache/flink/pull/8607#discussion_r290188342
########## File path: docs/concepts/glossary.md ########## @@ -0,0 +1,140 @@ +--- +title: Glossary +nav-pos: 3 +nav-title: Glossary +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. +--> + +#### Flink Application Cluster + +A Flink Application Cluster is a dedicated [Flink Cluster](./glossary#flink-cluster) that only +executes a single [Flink Job](./glossary#flink-job). The lifetime of the +[Flink Cluster](./glossary#flink-cluster) is bound to the lifetime of the Flink Job. Formerly +Flink Application Clusters were also known as Flink Clusters in *job mode*. + +#### Flink Cluster + +The distributed system consisting of (typically) one Flink Master process and one or more Flink +Taskmanagers processes. + +#### Event + +An event is a statement of fact about a change of the state of the domain modelled by the +application. Events can be input and/or output of a stream or batch processing application. +Events are special types of [records](./glossary#Record) + +#### ExecutionGraph + +see [Physical Graph](./glossary#physical-graph) + +#### Function + +Functions, or user-defined functions (UDFs), are implemented by the user and encapsulate the +application logic of a Flink program. Most Functions are wrapped by a corresponding +[Operator](./glossary#operator). + +#### Instance + +The term *instance* is used to describe a specific instance of a specific type (usually +[Operator](./glossary#operator) or [Function](./glossary#function)) during runtime. As Apache Flink +is mostly written in Java, this corresponds to the definition of *Instance* or *Object* in Java. +In the context of Apache Flink, the term *parallel instance* is also frequently used to emphasizes +that multiple instances of the same [Operator](./glossary#operator) or +[Function](./glossary#function) type are running in parallel. + +#### Flink Job + +A Flink Job is the runtime representation of a Flink program. A Flink Job can be either submitted +to a long running [Flink Session Cluster](./glossary#flink-session-cluster) or it can be started as a +self-contained [Flink Application Cluster](./glossary#flink-application-cluster). + +#### JobGraph + +see [Logical Graph](./glossary#logical-graph) + +#### Logical Graph + +A logical graph is a directed graph describing the high-level logic of a stream processing program. +The nodes are [Operators](./glossary#operator) and the edges indicate input/output-relationships or +data streams or data sets. + +#### Managed State + +Managed State describes application state, which has been registered with the framework. For +Managed State Apache Flink will take care about persistence and rescaling among other things. + +#### Operator + +Node of a [Logical Graph](./glossary#logical-graph). An Operator performs a certain operation, +which is usually executed by a [Function](./glossary#function). Sources and Sinks are special +Operators for data ingestion and data egress. + +#### Partition + +A partition is an independent subset of the overall data stream or data set. A data stream or +data set is divided into partitions by assigning each [record](./glossary#Record) to one or more +partitions. Partitions of data streams or data sets are consumed by [Tasks](./glossary#task) during +runtime. + +#### Physical Graph + +A physical graph is the result of translating a [Logical Graph](./glossary#logical-graph) for +execution in a distributed runtime. The nodes are [Tasks](./glossary#task) and the edges indicate +input/output-relationships or partitions of data streams or data sets. + +#### Record + +Records are the constituent elements of a data set or data stream. +[Operators](./glossary#operator) and [Functions](./glossary#Function) receive records as input +and emit records as output. + +#### Flink Session Cluster + +A long-running [Flink Cluster](./glossary#flink-cluster), which accepts multiple +[Flink Jobs](./glossary#flink-job) for execution. The lifetime of this Flink Cluster is not bound +to the lifetime of any Flink Job. Formerly, a Flink Session Cluster was also known as a Flink Cluster in +*session mode*. + +#### State Backend + +For stream processing programs the State Backend determines how state is stored on each Taskmanager +(Java Heap of Taskmanager or RocksDB) as well as where it is written upon a checkpoint (Java Heap of Flink Master or +Filesystem). + +#### Sub-Task + +A Sub-Task is a [Task](./glossary#task) responsible for processing a +[partition](./glossary#partition) of the data stream. The term "Sub-Task" emphasizes that there are +multiple parallel Tasks for the same [Operator](./glossary#operator). + +#### Task + +Node of a [Physical Graph](./glossary#physical-graph). A task is the basic unit of work, which is +executed by Flink's runtime. Tasks usually encapsulate one or more [Operators](./glossary#operator). + +#### Transformation + +A transformation is applied on one or more data streams or data sets and results in one or more +output new data streams or data sets. A transformation might change a data stream or data set on a +per-record basis, but but might also only change its partitioning or perform an aggregation. In +contrast to operations, transformations operate on streams or data sets, while operations operate +on [records](./glossary#Record). Review comment: For me, an operation would be the action that an operator performs. The idea is that transformations are applied on streams, while operations are applied on individual records. ---------------------------------------------------------------- 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: [email protected] With regards, Apache Git Services
