I was looking for information around how OpenCensus metrics handles the problem of "coordinated omission".
As far as I saw Micrometer from http://micrometer.io uses the LatencyUtils http://latencyutils.github.io/LatencyUtils/ by Gil Tene to solve this issue, but I couldn't find anything like that for OpenCensus.
If anyone could point me in the right direction that would be helpful.
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I want to input the past couple of years of my high school soccer team's stat books into a spreadsheet so I can run my own analysis on it using Python in Google Colab or a Jupyter Notebook. The problem I have right now is that I don't know what the best way of aggregating it in Excel is. I have a record of basic stats such as lineups, shots, saves, goals, assists, etc. for each individual game (standard box score stuff you'd expect from a high school team who uses a JV player to keep stats). But what would be the best way to input all of this in a way that will make it easy for me to analyze? Obviously I can't make a separate Excel tab for each individual game (there are hundreds of games), and I don't think logging them all into the same tab would be the best thing to do either, but I don't what I should do in order to solve this problem. This seems like a simple problem, and I'm probably missing a really obvious solution, but if anyone could give me some advice, I'd be very grateful. Does anyone have any experience doing anything similar? Thanks for taking the time to help.
I haven't tried anything yet because I wanted to figure out a good method before I put a bunch of time into this.
I've been tracing my code and comparing notes between my own code and some sample code
I'm working from this sample code: http://mbostock.github.io/d3/talk/20111116/bundle.html
My source example is here: http://www.nogumallowed.com/test5.php
My problem is the path lines. They work, they connect, but I love in the source how the lines have more seemingly random curves to them. I can'y figure out how to recreate that. Mine all flow incredibly well, but look rather plain in comparison.
Can anyone offer any insights? I've been coming back to this for a few days, and haven't figured it out yet. The documentation hasn't tipped me in the right direction yet either.
I'm just scratching the surface of "comfortable with D3", but there's still A LOT for me to learn on it before I give myself a D3 Jedi.
It doesn't look like your clustering code (if you have any) is working very well. The subjects should be clustered together into related groups, but it doesn't appear like yours are. For instance, your node "John Sly" is connected to almost very other node except the few on either side of it. It seems to me that those nine or so highly connected nodes should be distributed around the circle, not bunched next to each other.
I am applying A* (and IDA*) search with manhattan heuristic for finding solution to 15-puzzle problem.
Using the fact that i dont want an optimal solution for the problem how can i can speed up the search as the current routine is too slow.
Well, it's not exactly a solution, but it might help. Once I've been working for a HOG game with that same puzzle as a minigame and it turned much easier to generate a problem, than find a solution.
What I mean is, we can turn a solved puzzle into unsolved by randomly moving "window" according to rules. And logging each field position for future use. Then we let user play a bit and if she gives up, we can solve a puzzle for her easily by finding the common position in user and our log. We just play back via user log to the common position and back from it to the solved position via ours log.
Of course, this is a hack and not a real solution, but it works fine in gamedev. And not only for this particular game. Most repositioning puzzles can be "solved" this way.
I searched a bit around and didn't find nothing about this particular issue. I am currently developing something that involves Socket.IO on Node.js.
My question is pretty simple : is there a way to know how many messages are dropped from a socket.volatile.emit() ?
Thanks for any tips!
https://github.com/LearnBoost/socket.io/blob/master/lib/transport.js#L524-534
No counter incremented, but you could turn on logging to take a look.
I know this isn't a coding question but i wanted to throw it out there as the wealth of experience in the forum is high.
When we perform a search for the first time it's slow and it is fine after this.
Anyone got any ideas about why this is?
I think it's something to do with the cache being cleared out and was wondering if anyone could shed some light on how to get around this?
Thanks
More than likely caused by the first "hit", the server is doing a lot of background processing. This would be the same as a webpage or database query. The initial execution may be the slowest due to the volume of work it has to initially process, afterwards the data is cached.