See #204.
This graph isn't huge (around 2MB for 50-60k jobs), but it's larger than the other graphs by some factor due to the amount of data being rendered. But it also isn't large enough that we can make huge savings by exporting to a PNG.
It would be worth exploring converting the ConcurrencyLineGraph to use e.g. pandas or scipy to quantize/smooth the input data to reduce the size of the generated graph, as for regular runs, most changes in concurrency are just noise (a job finishing and then something new immediately being scheduled).
See #204.
This graph isn't huge (around 2MB for 50-60k jobs), but it's larger than the other graphs by some factor due to the amount of data being rendered. But it also isn't large enough that we can make huge savings by exporting to a PNG.
It would be worth exploring converting the
ConcurrencyLineGraphto use e.g.pandasorscipyto quantize/smooth the input data to reduce the size of the generated graph, as for regular runs, most changes in concurrency are just noise (a job finishing and then something new immediately being scheduled).