Owl commonly benchmarks on large daily datasets. In this case a 43 million row table with 12 columns completes in under 6 mins (5:30). The best balance for this dataset was 3 executors each with 10G of ram.
./owlcheck \-u user -p password \-c jdbc:mysql://owldatalake.chzid9w0hpyi.us-east-1.rds.amazonaws.com:3306 \-q "select * from silo.account_large where acc_upd_ts > '2018-02-01 05:0:00'" \-rd 2019-02-02 \-ds account_large \-dc acc_upd_ts \-corroff \-histoff \-driver com.mysql.cj.jdbc.Driver \-lib "/home/ec2-user/owl/drivers/mysql/" \-master yarn \-deploymode client \-numexecutors 3 \-executormemory 10g \-histoff -corroff -loglevel DEBUG -readonly
note: not all Owl features were turned on during this run. On large datasets it is worth it to consider limiting the columns, owl-features, or lookbacks if they are not of interest.