Advanced data structures in practice

Question

In the 10 years I\'ve been programming, I can count the number of data structures I\'ve used on one hand: arrays, linked lists (I\'m lumping stacks and queues in with this),

Answer 1

B-trees are in databases.

R-trees are for geographic searches (e.g. if I have 10000 shapes each with a bounding box scattered around a 2-D plane, which of these shapes intersect an arbitrary bounding box B?)

deques of the form in the C++ STL are growable vectors (more memory-efficient than linked lists, and constant-time to "peek" arbitrary elements in the middle). As far as I can remember, I've never used the deque to its full extent (insert/delete from both ends) but it's general enough that you can use it as a stack (insert/delete from one end) or queue (insert to one end, delete from the other) and also have high-performance access to view arbitrary elements in the middle.

I've just finished reading Java Generics and Collections -- the "generics" part hurts my head, but the collections part was useful & they point out some of the differences between skip lists and trees (both can implement maps/sets): skip lists give you built-in constant time iteration from one element to the next (trees are O(log n) ) and are much simpler for implementing lock-free algorithms in multithreaded situations.

Priority queues are used for scheduling among other things (here's a webpage that briefly discusses application); heaps are usually used to implement them. I've also found that the heapsort (for me at least) is the easiest of the O(n log n) sorts to understand and implement.