For starters, the blog post was informative and should get some creative juices flowing for applications in others' stacks -- piqued my interests in hacking core utilities. However...
The graphs never show a 30K token mark, which is what the heap-allocation counter showed for their [programming language] classifier.
It's not clear to me that much RSS was saved. Maybe 20Mb? So, the next question is how many classifiers are running, where such a "hit" actually matters. Again, there is no 30K mark on the runtime graphs, but let's assume the generation to the graphs' left are linear. It looks like we're saving a half-second and removing most of the jitter, but it's not made clear how the removal of GC chunking has any effect on processing outside of the classifier. I just can't imagine how a couple of these classifiers can't keep up with the push rate of files to Github -- the classification improvements are neither low-hanging or part of the BigO in Github's stack. The process seems very able to run asynchronous at push time and un-deferred, if unrun, on page view. Unless they're seeing more than 1 million pageviews/sec (per classifier; just run more? one 20Mb service per httpd server?), because I can't really imagine hitting more than 10x their tokens (300K tokens), which is still only ~50Mb; the RSS graph, again, has a weird scale to suggest they might grow their tokens by 67x.
Comments
For starters, the blog post was informative and should get some creative juices flowing for applications in others' stacks -- piqued my interests in hacking core utilities. However...
The graphs never show a 30K token mark, which is what the heap-allocation counter showed for their [programming language] classifier.
It's not clear to me that much RSS was saved. Maybe 20Mb? So, the next question is how many classifiers are running, where such a "hit" actually matters. Again, there is no 30K mark on the runtime graphs, but let's assume the generation to the graphs' left are linear. It looks like we're saving a half-second and removing most of the jitter, but it's not made clear how the removal of GC chunking has any effect on processing outside of the classifier. I just can't imagine how a couple of these classifiers can't keep up with the push rate of files to Github -- the classification improvements are neither low-hanging or part of the BigO in Github's stack. The process seems very able to run asynchronous at push time and un-deferred, if unrun, on page view. Unless they're seeing more than 1 million pageviews/sec (per classifier; just run more? one 20Mb service per httpd server?), because I can't really imagine hitting more than 10x their tokens (300K tokens), which is still only ~50Mb; the RSS graph, again, has a weird scale to suggest they might grow their tokens by 67x.
They said in the article that they want to expand the classification data so my guess is they will be going well beyond 30k tokens.