A simple pipeline that processes events from a wind turbine farm.
The same as sensor-data-scala, but implemented using the Java DSL.
An aggregation of user call record data (metadata of phone calls).
A simple pipeline that generates events from energy devices.
A simple pipeline that generates events from energy devices. This pipeline will fail based on a pre-defined probability percentage. Its purpose is to demonstrate the failure recovery features of Pipelines and Spark.
An event-based e-commerce streaming platform. Events are generated based on user events such as purchases and merchant actions such as the addition of products and their stock numbers.
| Application | Akka Streams (Scala) | Akka Streams (Java) | Spark | Testkit | Ingress | Egress | Auto Data Generation |
|---|---|---|---|---|---|---|---|
sensor-data-scala |
Yes | No | No | No | HTTP | stdout (logs) | Yes (Client Lua Script) |
sensor-data-java |
No | Yes | No | No | HTTP | stdout (logs) | Yes (Client Lua Script) |
call-record-aggregator |
Yes | Yes | Yes | Yes | HTTP | stdout (logs) | Yes |
spark-sensors |
No | No | Yes | No | HTTP | stdout (logs) | Yes |
spark-resilience-test |
Yes | No | No | Yes | HTTP | stdout (logs) | Yes |
warez |
Yes | No | Yes | Yes | HTTP | ElasticSearch, HTTP API | No |
Consult the Pipelines Documentation for instructions on building, deploying and running Pipelines applications.
NOTE
Before building any examples remember to update the Docker registry in the target-env.sbt file.