

 B-Trees - Balanced Search Trees for Slow Storage - nickb
http://scienceblogs.com/goodmath/2008/07/btrees_balanced_search_trees_f.php

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timr
This is a really sloppy summary. First, the given example is broken (the
numbers in the nodes change from fig 1 to fig 2). Second, the delete operation
is only like the insert operation if you look at it from a distance, squint,
and tap your heels together three times. Implementing the delete is about an
order of magnitude more difficult than the insert, IMO. An article on the
details of _that_ would be enlightening.

(Personal anecdote: in college, I spent a nightmarish two days implementing
the delete operation on a B-tree, because I had put it off until the last
minute, thinking that it was _"just like the insert, but with contractions"_.
I was wrong. I don't think I've spent that much consecutive time in one chair
before or since....)

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noodle
b-trees. ugh. i wrote code around b-trees in my data structures class in
college. but to my surprise, when i got out, pretty much no one in the "real
world" (hiring for entry-level positions) use them. they mostly use things
that we didn't ever actually play around with -- stuff like hash tables.

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ajross
B-trees (and related data structures) are pervasive in the real world. Pretty
much any application that requires high speed access from disk uses them.
Think about filesystems, databases, etc... They're hugely useful.

But they're not useful for the same purpose as a hash table, which is also a
pervasive data structure, but for a different problem area: constant time
access to in-memory data.

~~~
noodle
yes, i know. my point is, try finding an entry-level position that requires
knowledge and experience of b-trees and not hashtables.

~~~
lampy
Try finding a senior-level engineering position that _doesn't_ require
knowledge of B-trees or similar computer science topics.

~~~
Tamerlin
So far in my experience the companies hiring want you to know that sort of
thing, but that knowledge is largely wasted at most jobs.

