Re: Dealing with expensive jenkins + Dataflow jobs

2019-02-18 Thread Łukasz Gajowy
Thanks for your suggestions. It's always good to reach the dev list! You're right that we should focus more on what are we trying to test rather than providing huge loads. To stay transparent for everyone: "what is it we're trying to test?" I talked with some testing experts from the Dataflow te

Re: Dealing with expensive jenkins + Dataflow jobs

2019-01-23 Thread Alan Myrvold
Agreeing with Robert about "what is it we're trying to test?". Would a smaller performance test find the same issues, faster and more reliably? We have seen issues with the apache-beam-testing project exceeding quota during dataflow jobs, resulting in spurious failures during precommits and postco

Re: Dealing with expensive jenkins + Dataflow jobs

2019-01-23 Thread Robert Bradshaw
I like the idea of creating separate project(s) for load tests so as to not compete with other tests and the standard development cycle. As for how many workers is too many, I would take the track "what is it we're trying to test?" Unless your stress-testing the shuffle itself, much of what Beam d

Re: Dealing with expensive jenkins + Dataflow jobs

2019-01-23 Thread Łukasz Gajowy
Hi, pinging this thread (maybe some folks missed it). What do you think about those concerns/ideas? Łukasz pon., 14 sty 2019 o 17:11 Łukasz Gajowy napisał(a): > Hi all, > > one problem we need to solve while working with load tests we currently > develop is that we don't really know how much G

Dealing with expensive jenkins + Dataflow jobs

2019-01-14 Thread Łukasz Gajowy
Hi all, one problem we need to solve while working with load tests we currently develop is that we don't really know how much GCP/Jenkins resources can we occupy. We did some initial testing with beam_Java_LoadTests_GroupByKey_Dataflow_Small[1] and it seems that for: - 1 000 000 000 (~ 23 GB) syn