This tools will run a synthetic workload against Apache Cassandra with the intention of stressing the system. It can maintain multiple views of data either manually (in app) or via Materialized Views (in server)

Imagine we run a music service that allows users to create playlists. The core table for our service is:

CREATE TABLE user_playlists
(
  user_name           text,
  playlist_name       text,
  song_id             text,
  added_time          bigint,
  artist_name         text,
  genre               text,
  last_played         bigint,
  PRIMARY KEY (user_name, playlist_name, song_id) 
);

Now with this information we can create add, update, delete playlists in our system. But we want to answer other questions using this data like:

Which users like the same song? Which users like the same artist? Which users like the same genre? What was the recently played tracks for a given user?

So our system maintains other views on this data (defined in the schema)

   # Load the schema into your C* cluster
   cqlsh < bench_schema.cql
   
   # compile 
   mvn compile
   
   # run with server based materialized view mode
   mvn exec:java -Dexec.args=""

   # To with in app based manual view mode
   mvn exec:java -Dexec.args="--manual" 

   # To see all options
   mvn exec:java -Dexec.args="--help"
   

After running, there will be a detailed csv files under ./reports/view and ./reports/manual

by @tjake