glothos / koober Goto Github PK

An uber data pipeline sample app. Play Framework, Akka Streams, Kafka, Flink, Spark Streaming, and Cassandra.

Start Kafka:

./sbt kafkaServer/run

Web App:

1. Obtain an API key from mapbox.com
2. Start the Play web app: MAPBOX_ACCESS_TOKEN=YOUR-MAPBOX-API-KEY ./sbt webapp/run

Try it out:

1. Open the driver UI: http://localhost:9000/driver
2. Open the rider UI: http://localhost:9000/rider
3. In the Rider UI, click on the map to position the rider
4. In the Driver UI, click on the rider to initiate a pickup

Start Flink:

1. ./sbt flinkClient/run
2. Initiate a few pickups and see the average pickup wait time change (in the stdout console for the Flink process)

Start Cassandra:

./sbt cassandraServer/run

Start the Spark Streaming process:

1. ./sbt kafkaToCassandra/run
2. Watch all of the ride data be micro-batched from Kafka to Cassandra

Setup PredictionIO Pipeline:

1. Setup PIO

2. Set the PIO Access Key:

    export PIO_ACCESS_KEY=<YOUR PIO ACCESS KEY>
   

3. Start the PIO Pipeline:

    ./sbt pioClient/run
   

Copy demo data into Kafka or PIO:

For fake data, run:

./sbt "demoData/run <kafka|pio> fake <number of records> <number of months> <number of clusters>"

For New York data, run:

./sbt "demoData/run <kafka|pio> ny <number of months> <sample rate>"

Start the Demand Dashboard

PREDICTIONIO_URL=http://asdf.com MAPBOX_ACCESS_TOKEN=YOUR_MAPBOX_TOKEN ./sbt demandDashboard/run