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.
Plotting can take a long time and use a lot of resources.
Multiple plot requests can cause the machine to run OOM.
We are now allowing plots for 500k files again. This is mainly to
prevent unwanted plots of everything.
This is done in preparation for the proposal API.
In order to compute proposals we need to consume the
API of the DataStore, but the code does not need to
be in the DataStore.
Extracting the API allows us to separate these concerns.
LuDB has a few disadvantages.
1. Most notably disk space. H2 wastes a lot of valuable disk space.
For my test data set with 44 million entries it is 14 MB
(sometimes a lot more; depends on H2 internal cleanup). With
data-store it is 15 KB.
Overall I could reduce the disk space from 231 MB to 200 MB (13.4 %
in this example). That is an average of 4.6 bytes per entry.
2. Speed:
a) Liquibase is slow. The first time it takes approx. three seconds
b) Query and insertion. with data-store we can insert entries
up to 1.6 times faster.
Data-store uses a few tricks to save disk space:
1. We encode the tags into the file names.
2. To keep them short we translate the key/value of the tag into
shorter numbers. For example "foo" -> 12 and "bar" to 47. So the
tag "foo"/"bar" would be 12/47.
We then translate this number into a numeral system of base 62
(a-zA-Z0-9), so it can be used for file names and it is shorter.
That way we only have to store the mapping of string to int.
3. We do that in a simple tab separated file.
