- split the 'sortby' select field into two fields
- sort by average
- legend shows plotted and total values in the date range
- removed InlineDataSeries, because it was not used anymore
In logarithmic plots it is not easy to spot which event are longer than
60 seconds. A thin grey line help with this.
Also: fixed the marker lines (zoom area) which broke when y-ranges were
introduced. The lines were not drawn correctly, when the y-axis offset
was greater than 0.
Gnuplot supports differen coordinate systems. 'graph' is relative to the
area within the axes, 0,0 is bottom left and 1,1 is top right. And
'first' is based on the values of the x1 axis.
By using "graph 0.25,0" we say that the starting point is 25% of the
x-axis and 0% of the y-axis without having to compute the exact values.
Sometimes it is useful to specify the certain y-axis range. For example
when you are only interested in the values that take longer than a
threshold. Or when you want to exclude some outliers. When you want to
compare plots in a gallery, it is very handy when all plots have the
same data-area.
Eventually we want to only support what is now called aggregate, but
not have to implement different plot types. So instead of supporting
percentile plots for dashboards I removed them. You can still get
percentile plots together with the scatter plot.
Scaling big plots to small thumbnails results in bad images that barely
show any details.
We solve this by calling gnuplot a second time to generate the
thumbnails. They don't have any labels and are rendered in the required
size, so that not scaling is necessary.
Thumbnails have to be requested explicitly, because it can be expensive
to compute them.
Counting the available values is quite expensive and there are only a
few corner cases where this makes sense. One of them is when the query
is for a method that is not project specific and therefore no project
values can be found.
The last improvement of memory usage introduced a performance
regression. The ingestion performance dropped by 50%-80%, because
for every inserted entry the Tags were created inefficient.
For each entry we executed two calls to System.nanoTime().
The resulting numbers aren't very reliable and calling nanoTime
that often (160k - 300k per second) is quite expensive.
