MATERIALIZED VIEW BENCHMARK
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)
How to use?
# 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