[flink] update README
Project: http://git-wip-us.apache.org/repos/asf/incubator-beam/repo Commit: http://git-wip-us.apache.org/repos/asf/incubator-beam/commit/ceb2c87f Tree: http://git-wip-us.apache.org/repos/asf/incubator-beam/tree/ceb2c87f Diff: http://git-wip-us.apache.org/repos/asf/incubator-beam/diff/ceb2c87f Branch: refs/heads/master Commit: ceb2c87f8f749cb4db0582b9f1abc15c4da752fd Parents: 28fcfd7 Author: Maximilian Michels <[email protected]> Authored: Wed Mar 2 23:51:38 2016 +0100 Committer: Davor Bonaci <[email protected]> Committed: Fri Mar 4 10:04:23 2016 -0800 ---------------------------------------------------------------------- runners/flink/README.md | 60 ++++++++++++++++++++++---------------------- 1 file changed, 30 insertions(+), 30 deletions(-) ---------------------------------------------------------------------- http://git-wip-us.apache.org/repos/asf/incubator-beam/blob/ceb2c87f/runners/flink/README.md ---------------------------------------------------------------------- diff --git a/runners/flink/README.md b/runners/flink/README.md index 499ed6d..0fee6f0 100644 --- a/runners/flink/README.md +++ b/runners/flink/README.md @@ -1,17 +1,17 @@ -Flink-Dataflow --------------- +Flink Beam Runner (Flink-Runner) +------------------------------- -Flink-Dataflow is a Runner for Google Dataflow (aka Apache Beam) which enables you to -run Dataflow programs with Flink. It integrates seamlessly with the Dataflow -API, allowing you to execute Dataflow programs in streaming or batch mode. +Flink-Runner is a Runner for Apache Beam which enables you to +run Beam dataflows with Flink. It integrates seamlessly with the Beam +API, allowing you to execute Apache Beam programs in streaming or batch mode. ## Streaming -### Full Dataflow Windowing and Triggering Semantics +### Full Beam Windowing and Triggering Semantics -The Flink Dataflow Runner supports *Event Time* allowing you to analyze data with respect to its +The Flink Beam Runner supports *Event Time* allowing you to analyze data with respect to its associated timestamp. It handles out-or-order and late-arriving elements. You may leverage the full -power of the Dataflow windowing semantics like *time-based*, *sliding*, *tumbling*, or *count* +power of the Beam windowing semantics like *time-based*, *sliding*, *tumbling*, or *count* windows. You may build *session* windows which allow you to keep track of events associated with each other. @@ -27,7 +27,7 @@ and sinks or use the provided support for Apache Kafka. ### Seamless integration -To execute a Dataflow program in streaming mode, just enable streaming in the `PipelineOptions`: +To execute a Beam program in streaming mode, just enable streaming in the `PipelineOptions`: options.setStreaming(true); @@ -52,7 +52,7 @@ and sinks. ## Features -The Flink Dataflow Runner maintains as much compatibility with the Dataflow API as possible. We +The Flink Beam Runner maintains as much compatibility with the Beam API as possible. We support transformations on data like: - Grouping @@ -66,25 +66,25 @@ support transformations on data like: # Getting Started -To get started using Flink-Dataflow, we first need to install the latest version. +To get started using the Flink Runner, we first need to install the latest version. -## Install Flink-Dataflow ## +## Install Flink-Runner ## -To retrieve the latest version of Flink-Dataflow, run the following command +To retrieve the latest version of Flink-Runner, run the following command - git clone https://github.com/dataArtisans/flink-dataflow + git clone https://github.com/apache/incubator-beam -Then switch to the newly created directory and run Maven to build the Dataflow runner: +Then switch to the newly created directory and run Maven to build the Beam runner: - cd flink-dataflow + cd incubator-beam mvn clean install -DskipTests -Flink-Dataflow is now installed in your local maven repository. +Flink-Runner is now installed in your local maven repository. ## Executing an example Next, let's run the classic WordCount example. It's semantically identically to -the example provided with Google Dataflow. Only this time, we chose the +the example provided with ApacheBeam. Only this time, we chose the `FlinkPipelineRunner` to execute the WordCount on top of Flink. Here's an excerpt from the WordCount class file: @@ -113,15 +113,15 @@ Then let's run the included WordCount locally on your machine: mvn exec:exec -Dinput=kinglear.txt -Doutput=wordcounts.txt -Congratulations, you have run your first Google Dataflow program on top of Apache Flink! +Congratulations, you have run your first ApacheBeam program on top of Apache Flink! -# Running Dataflow programs on a Flink cluster +# Running Beam programs on a Flink cluster -You can run your Dataflow program on an Apache Flink cluster. Please start off by creating a new +You can run your Beam program on an Apache Flink cluster. Please start off by creating a new Maven project. - mvn archetype:generate -DgroupId=com.mycompany.dataflow -DartifactId=dataflow-test \ + mvn archetype:generate -DgroupId=com.mycompany.beam -DartifactId=beam-test \ -DarchetypeArtifactId=maven-archetype-quickstart -DinteractiveMode=false The contents of the root `pom.xml` should be slightly changed aftewards (explanation below): @@ -133,14 +133,14 @@ The contents of the root `pom.xml` should be slightly changed aftewards (explana xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd";> <modelVersion>4.0.0</modelVersion> - <groupId>com.mycompany.dataflow</groupId> - <artifactId>dataflow-test</artifactId> + <groupId>com.mycompany.beam</groupId> + <artifactId>beam-test</artifactId> <version>1.0</version> <dependencies> <dependency> - <groupId>com.dataartisans</groupId> - <artifactId>flink-dataflow</artifactId> + <groupId>org.apache.beam</groupId> + <artifactId>flink-runner</artifactId> <version>0.2</version> </dependency> </dependencies> @@ -182,13 +182,13 @@ The contents of the root `pom.xml` should be slightly changed aftewards (explana The following changes have been made: -1. The Flink Dataflow Runner was added as a dependency. +1. The Flink Beam Runner was added as a dependency. 2. The Maven Shade plugin was added to build a fat jar. -A fat jar is necessary if you want to submit your Dataflow code to a Flink cluster. The fat jar -includes your program code but also Dataflow code which is necessary during runtime. Note that this -step is necessary because the Dataflow Runner is not part of Flink. +A fat jar is necessary if you want to submit your Beam code to a Flink cluster. The fat jar +includes your program code but also Beam code which is necessary during runtime. Note that this +step is necessary because the Beam Runner is not part of Flink. You can then build the jar using `mvn clean package`. Please submit the fat jar in the `target` folder to the Flink cluster using the command-line utility like so:
