We encountered a situation where CPU usage hit 100% due to a frequently running query. The issue resolved after performing a manual ANALYZE on the table involved in the query. However, I noticed the following: Auto-analyze ran at 11:46 UTC…
I have a algorithm that is spitting out a list of scores: list_of_scores = [100, 101, 102, 101, 43, 42, 42, 41, 20, 21, 22, 23] in the above list, there is a 'cluster' of scores around 100, another 'cluster'…
Background: I have a number of sources that reference a relationship. I have calculated the percentage of the sources in which any particular relationship is found (since multiple sources sometimes reference the same relationship). Any relationship that is found in…
I've done this sometime last year, but now I really can't recall and can't find any helpful resources. I want to get the statistics of my collection based on types. This is my data object { "_id": { "$oid": "63bfc374378c59a5328f229e"…
I'm trying to make a call from within R to execute BASH commands, to get my feet wet: I wanted to simply capture a listing of my current files located in a specific directory through use of the "ls -al"…
I'm new to R and I'm attempting to do something that I believe should be very simple but code online has not helped. data <- structure(list(Group = c(1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3), Time…
Some Context I found myself confronting a mathematical meme on Facebook (try not to laugh): Clearly, this is a simple problem which can be solved by first looking at each number as if they're elements in a 2-dimensional grid, then…
Twitter, Google, Amazon, del.icio.us etc. all give you a lot of data to play with, all for free. There's also a lot of textual data available through initiatives like Project Gutenberg. And that, it seems, is just the tip of…