This is an automated email from the ASF dual-hosted git repository. riemer pushed a commit to branch SP-769 in repository https://gitbox.apache.org/repos/asf/streampipes-website.git
commit 631954d4b6690c8d32f5408ae8cda816e04dbb5f Author: Dominik Riemer <[email protected]> AuthorDate: Sun Dec 4 13:05:47 2022 +0100 Update tutorials (apache/streampipes#769) --- documentation/docs/06_extend-cli.md | 2 +- .../docs/06_extend-tutorial-data-processors.md | 25 +++++++++------------- .../docs/06_extend-tutorial-data-sinks.md | 8 +++---- .../docs/06_extend-tutorial-data-sources.md | 23 ++++++-------------- 4 files changed, 21 insertions(+), 37 deletions(-) diff --git a/documentation/docs/06_extend-cli.md b/documentation/docs/06_extend-cli.md index 0caec85b..09cf34d7 100644 --- a/documentation/docs/06_extend-cli.md +++ b/documentation/docs/06_extend-cli.md @@ -11,7 +11,7 @@ The StreamPipes command-line interface (CLI) is focused on developers in order t The main difference between the standard Docker/K8s installation is an improved communication between services running as containers and services running locally for development. -The CLI can be found in the [main repository](https://github.com/apache/streampipes/tree/master/installer/cli) or in the ``compose/cli`` folder of the downloaded source code. +The CLI can be found in the [main repository](https://github.com/apache/streampipes/tree/master/installer/cli) or in the ``installer/cli`` folder of the downloaded source code. ## TL;DR diff --git a/documentation/docs/06_extend-tutorial-data-processors.md b/documentation/docs/06_extend-tutorial-data-processors.md index 525b5592..408159b8 100644 --- a/documentation/docs/06_extend-tutorial-data-processors.md +++ b/documentation/docs/06_extend-tutorial-data-processors.md @@ -4,13 +4,13 @@ title: Tutorial: Data Processors sidebar_label: Tutorial: Data Processors --- -In this tutorial, we will add a new data processor using the standalone wrapper. +In this tutorial, we will add a new data processor. -From an architectural point of view, we will create a self-contained service that includes the description of the data processor and a an implementation. +From an architectural point of view, we will create a self-contained service that includes the description of the data processor and an implementation. ## Objective -We are going to create a new data processor that realized a simple geofencing algorithm - we detect vehicles that enter a specified radius around a user-defined location. +We are going to create a new data processor that realizes a simple geofencing algorithm - we detect vehicles that enter a specified radius around a user-defined location. This pipeline element will be a generic element that works with any event stream that provides geospatial coordinates in form of a latitude/longitude pair. The algorithm outputs every location event once the position has entered the geofence. @@ -32,7 +32,7 @@ Enter the following command in a command line of your choice (Apache Maven needs ``` mvn archetype:generate \ -DarchetypeGroupId=org.apache.streampipes -DarchetypeArtifactId=streampipes-archetype-extensions-jvm \ --DarchetypeVersion=0.69.0 -DgroupId=my.groupId \ +-DarchetypeVersion=0.70.0 -DgroupId=my.groupId \ -DartifactId=my-example -DclassNamePrefix=MyExample -DpackageName=mypackagename ``` @@ -76,7 +76,7 @@ public class GeofencingProcessor extends StreamPipesDataProcessor { @Override public DataProcessorDescription declareModel() { - return ProcessingElementBuilder.create("org.streampipes.tutorial-geofencing") + return ProcessingElementBuilder.create("org.apache.streampipes.tutorial-geofencing") .category(DataProcessorType.ENRICH) .withAssets(Assets.DOCUMENTATION, Assets.ICON) .build(); @@ -108,7 +108,7 @@ Similar to data sources, the SDK provides a builder class to generate the descri Delete the content within the ``declareModel`` method and add the following lines to the `declareModel` method: ```java -return ProcessingElementBuilder.create("org.streampipes.tutorial.geofencing", "Geofencing", "A simple geofencing data processor") +return ProcessingElementBuilder.create("org.apache.streampipes.tutorial.geofencing", "Geofencing", "A simple geofencing data processor") ``` This creates a new data processor with the ID, title and description assigned to the element builder. @@ -202,7 +202,7 @@ The radius value can be extracted as follows: int radius = parameters.extractor().singleValueParameter("radius", Float.class); ``` -Great! That's all we need to describe a data processor for usage in StreamPipes. Your controller class should look as follows: +Great! That's all we need to describe a data processor for usage in StreamPipes. Your processor class should look as follows: ```java package org.apache.streampipes.pe.example; @@ -281,7 +281,7 @@ public class GeofencingProcessor extends StreamPipesDataProcessor { Everything we need to do now is to add an implementation. -Open the class `GeofencingProcessor.java` and add the following piece of code to the onEvent method, which realizes the Geofencing functionality: +Add the following piece of code to the onEvent method, which realizes the Geofencing functionality: ```java @@ -343,14 +343,9 @@ Now we are ready to start our service! Configure your IDE to provide an environment variable called ``SP_DEBUG`` with value ``true`` when starting the project. -Execute the main method in the class `Init` we've just created, open a web browser and navigate to http://localhost:8090 (or the port you have assigned). - -You should see something as follows: - -<img src="/docs/img/tutorial-processors/pe-overview-flink.PNG" alt="Pipeline Element Container Overview"> - +Execute the main method in the class `Init` we've just created. -The services automatically registers itself in StreamPipes. +The service automatically registers itself in StreamPipes. To install the just created element, open the StreamPipes UI and follow the manual provided in the [user guide](03_use-install-pipeline-elements.md). ## Read more diff --git a/documentation/docs/06_extend-tutorial-data-sinks.md b/documentation/docs/06_extend-tutorial-data-sinks.md index c0a664cb..f2d14e72 100644 --- a/documentation/docs/06_extend-tutorial-data-sinks.md +++ b/documentation/docs/06_extend-tutorial-data-sinks.md @@ -23,7 +23,7 @@ Enter the following command in a command line of your choice (Apache Maven needs ``` mvn archetype:generate -DarchetypeGroupId=org.apache.streampipes \ --DarchetypeArtifactId=streampipes-archetype-extensions-jvm -DarchetypeVersion=0.68.0 \ +-DarchetypeArtifactId=streampipes-archetype-extensions-jvm -DarchetypeVersion=0.70.0 \ -DgroupId=org.streampipes.tutorial -DartifactId=sink-tutorial -DclassNamePrefix=Rest -DpackageName=mypackage ``` @@ -63,7 +63,7 @@ public class RestSink extends StreamPipesDataSink { @Override public DataSinkDescription declareModel() { - return DataSinkBuilder.create("org.streampipes.tutorial.pe.sink.rest") + return DataSinkBuilder.create("org.apache.streampipes.tutorial.pe.sink.rest") .category(DataSinkType.NOTIFICATION) .withAssets(Assets.DOCUMENTATION, Assets.ICON) .withLocales(Locales.EN) @@ -219,9 +219,7 @@ Now we are ready to start our service! Configure your IDE to provide an environment variable called ``SP_DEBUG`` with value ``true`` when starting the project. -Execute the main method in the class `Init` we've just created, open a web browser and navigate to http://localhost:8090 (or the port you have assigned). - -The services automatically registers itself in StreamPipes. +Execute the main method in the class `Init` we've just created. The service automatically registers itself in StreamPipes. To install the created element, open the StreamPipes UI and follow the manual provided in the [user guide](03_use-install-pipeline-elements.md). diff --git a/documentation/docs/06_extend-tutorial-data-sources.md b/documentation/docs/06_extend-tutorial-data-sources.md index 45a5f56a..eadd8e87 100644 --- a/documentation/docs/06_extend-tutorial-data-sources.md +++ b/documentation/docs/06_extend-tutorial-data-sources.md @@ -32,7 +32,7 @@ Enter the following command in a command line of your choice (Apache Maven needs ``` mvn archetype:generate \ -DarchetypeGroupId=org.apache.streampipes -DarchetypeArtifactId=streampipes-archetype-extensions-jvm \ --DarchetypeVersion=0.69.0 -DgroupId=my.groupId \ +-DarchetypeVersion=0.70.0 -DgroupId=my.groupId \ -DartifactId=my-source -DclassNamePrefix=MySource -DpackageName=mypackagename ``` @@ -75,7 +75,7 @@ In contrast, the class `AbstractAlreadyExistingStream` indicates that we only wa Next, we will add the definition of the data stream. Add the following code inside of the `declareModel` method: ```java -return DataStreamBuilder.create("org.streampipes.tutorial.vehicle.position", "Vehicle Position", "An event stream " + +return DataStreamBuilder.create("org.apache.streampipes.tutorial.vehicle.position", "Vehicle Position", "An event stream " + "that produces current vehicle positions") ``` @@ -104,11 +104,10 @@ In order to complete the minimum required specification of an event stream, we n This can be achieved by extending the builder with the respective properties: ```java .format(Formats.jsonFormat()) -.protocol(Protocols.kafka("localhost", 9094, "TOPIC_SHOULD_BE_CHANGED")) +.protocol(Protocols.kafka("localhost", 9094, "org.apache.streampipes.tutoria.vehicle")) .build(); ``` -Set ``org.streampipes.tutorial.vehicle`` as your new topic by replacing the term ``TOPIC_SHOULD_BE_CHANGED`. In this example, we defined that the data stream consists of events in a JSON format and that Kafka is used as a message broker to transmit events. The last build() method call triggers the construction of the data stream definition. @@ -129,7 +128,7 @@ Let's assume our stream should produce some random values that are sent to Strea for (;;) { JsonObject jsonObject = new JsonObject(); jsonObject.addProperty("timestamp", System.currentTimeMillis()); - jsonObject.addProperty("plateNumber", "KA-FZ 1"); + jsonObject.addProperty("plateNumber", "KA-SP 1"); jsonObject.addProperty("latitude", random.nextDouble()); jsonObject.addProperty("longitude", random.nextDouble()); @@ -191,19 +190,9 @@ In some cases, the detected hostname is not resolvable from within a container ( Now we are ready to start our first container! -Execute the main method in the class `Init`, open a web browser and navigate to http://localhost:8090, or change the port according to the value of the ``SP_PORT`` variable in the env file. - Configure your IDE to provide an environment variable called ``SP_DEBUG`` with value ``true`` when starting the project. -You should see something as follows: - -<img src="/docs/img/tutorial-sources/pe-overview.PNG" alt="Pipeline Element Container Overview"> - -Click on the link of the data source to see the generated description of the pipeline element. - -<img src="/docs/img/tutorial-sources/pe-rdf.PNG" alt="Pipeline Element description"> - -The container automatically registers itself in StreamPipes. +The service automatically registers itself in StreamPipes. To install the just created element, open the StreamPipes UI and install the source over the ``Install Pipeline Elements`` section. @@ -211,3 +200,5 @@ To install the just created element, open the StreamPipes UI and install the sou Congratulations! You've just created your first pipeline element for StreamPipes. There are many more things to explore and data sources can be defined in much more detail. +Also consider that in some cases, you would like to create a configurable adapter, +where a data source can be configured by users in the UI when connecting data.
