Interesting approach, thanks. Yeah, I don't mind a question and conversation like that to start things off. But I do think getting into something a little deeper (which you also mentioned) later in the interview is important, too.
The overflow thing would be about computing the median of some sub-range of a sorted array. It is an often-quizzed thing that comes up as an edge case in binary search of a large array, but could apply to anything where you need to select the middle element of a sub-range of an array and the sum of the start/end indices could overflow.
I think the lore is that it was a bug in Java?'s binary search lib decades ago?
Same. I think it's probably easier on a touch screen than with mouse, but I'm stuck on level 10 for now. Maybe it's intentionally frustrating. Need to finish this level to unlock the last number I think, but I guess I've I've sunk enough time into it and will let it rest there.
I'm aware of this to an extent. Do you know of any list of what degree of parallelization to expect out of various components? I know this whole napkin-math thing is mostly futile and the answer should mostly be "go test it", but just curious.
I was interviewing recently and was asked about implementing a web crawler and then were discussing bottlenecks (network fetching the pages, writing the content to disk, CPU usage for stuff like parsing the responses) and parallelism, and I wanted to just say "well, i'd test it to figure out what I was bottlenecked on and then iterate on my solution".
What happens when something is put on the scale while it's sampling? Does the curve depend on properties of the scale, or just properties of the object and the manner in which it was put on the scale?
I guess everyone has their own preferences, I just find this opinion surprising given the wealth of other hikes in the country.
As someone who grew up hiking in the White Mountains before moving to Washington, the mountains in Washington (and many places in the West) are just on a whole different level.
It's higher than average/median in the US, but certainly not exceptional. Pretty normal for certain groups of people. There's a huge gap in miles driven between urban and rural area. US average is something like 13-15k miles per year (for all driving, not just commute).
20,000 miles solely for commuting would be about 43 miles each way (if you work 235 days per year), which is obviously more unusual than 20k total miles driven from all sources.
People (non-tech) don't tend to refer to "go to page 106" as using an index. The pages at the back of the book providing the word->page numbers lookup are commonly known as the book's "index"
I've sometimes been confused by the term "inverted index". The example in this post feels like what I would just call an "index"... i.e documents indexed by the words they contain. Feels about the same as the index in the back of a physical book.
Is the distinction that an index on a multi-valued attribute is called an inverted index?