Lubomír Bulej

It seems to me that this is not really a responsibility of a benchmark to say to which release it belongs. Let me think loudly... To me, a release is...

OK, I assume it's not critical for first release because we have no obsolete benchmarks yet. We'll come up with something (and I would lean towards configuration file or annotations...

I was under the impression that the number of executors influenced the default number of partitions created by default when creating RDDs directly from files on disk. It was also...

> ... seeing how our Spark instance is hardcoded to run locally ( > > https://github.com/renaissance-benchmarks/renaissance/blob/510b3b9e8f01dc397f35b64a7b5f8a943b75d012/benchmarks/apache-spark/src/main/scala/org/renaissance/apache/spark/SparkUtil.scala#L61 > ) I'm not sure what we're trying to do with the worker instance...

The thing with controlling the number of executor instances appears to originate from #145 and #147 and at that time, it seemed to work for @farquet. Looking at the [allowed...

#274 removes the configuration of executor instances (along with the benchmark parameter) as well as explicit input data partitioning (for now). I was wondering whether it would make sense to...

I have updated the PR and the measurement bundle (plugins work now). For testing, I added `als-ml` benchmark, which uses `ml.ALS` instead of `mllib.ALS`. Both do a conversion to RDD,...

Well, being able to plug the detailed description into a generated document should get us extra points :-)

Just to keep track of progress, #135 introduces the `@Description` annotation which should be used for this purpose. Note that the one-line summary should go to `@Summary`.

This brings to mind another thing -- do we want to checksum benchmark outputs so that we can detect if they break?