Kryo serialization should not be used for long term storage as upgrading the library could end in binary representation incompatibilities.
First you need to start cassandra locally and create both the keyspace and the column families using src/main/cql/01_key_space.cql and src/main/cql/02_column_family.cql.
Then you need to create the folder data somewhere in your filesystem, i.e. your home folder. Inside the data you should create three folders named revenue, trends and unique.
Modify the config files src/main/resources/revenue.conf, src/main/resources/trends.conf and src/main/resources/unique.conf to replace <path> in the property producer.folder with the path to your data folder.
To run the unique users job, load sbt and execute the command:
runMain com.mindcandy.data.jobs.unique.UniqueJobLauncher unique.conf
In a different shell, copy the file <repo>/fast-gt-perfect/data/unique/data.json to the unique folder inside your data folder; Spark should detect the file and process it.
You can stop the Spark job by pressing the RETURN key at any moment.
To run the revenue job, load sbt and execute the command:
runMain com.mindcandy.data.jobs.revenue.RevenueJobLauncher revenue.conf
In a different shell, copy the file <repo>/fast-gt-perfect/data/revenue/data.json to the revenue folder inside your data folder; Spark should detect the file and process it.
You can stop the Spark job by pressing the RETURN key at any moment.
To run the trending job, load sbt and execute the command:
runMain com.mindcandy.data.jobs.trends.TrendsJobLauncher trends.conf
In a different shell, copy the file <repo>/fast-gt-perfect/data/trends/data.json to the trends folder inside your data folder; Spark should detect the file and process it.
You can stop the Spark job by pressing the RETURN key at any moment.