mrpowers / mrpowers-benchmarks Goto Github PK

Move the developer focused stuff to a separate file.

Focus the README more on users interested in results. Not folks that want to clone the repo and run the commands themselves.

The h2o data creation R scripts work for small datasets, but aren't scalable. Here are the results on my machine:

Rscript groupby-datagen.R 1e7 1e2 0 0 # 7 seconds
Rscript groupby-datagen.R 1e8 1e1 5 1 # 3.5 minutes
Rscript groupby-datagen.R 1e9 1e1 5 1 # errors out, presumably due to a memory error

@ghuls created a sed script that should be more portable and easier to parallelize than the Rscript. I'm assuming we can parallelize the sed script to generate multiple CSV files in parallel, so this will scale. e.g. have groupby-datagen.R 1e9 1e1 5 1 output 50 1GB files instead of a single 50GB file.

@ghuls - can you create a PR and with your sed code? Any suggestions how to parallelize it? I can probably figure out how to parallelize it with Dask if that's the best option. Thanks!

https://www.queryverse.org/benchmarks/

from library import * is not good practice. It makes it hard to know what functions or classes come from that module.

I'd recommend choosing an alias, and doing something like this:

import dask_h2o_groupby_queries as ho_queries

or some other alias and then doing:

ho_queries.benchmark()

This way it's clear where the benchmark function comes from