I was under the impression that redis wouldn't be all that useful to store a lot of data. Would be great if something as quick as redis could work with large data sets.

Curious how. O(1) an array index lookup, not a string lookup, I thought.

O(1) implies that the location of the member in the list is already known, with no search required. I don't see how that could be the case when it's a key lookup. The key could be anywhere in the list, even if the list is sorted. They key would have to be searched for, it seems.

Think of it this way (this isn't literally what happens, but it's close).

1) Take the url you're looking for. Run it through a hash function. This takes an (amortized) constant amount of time.

2) Now you have an index to check. (the return value from the hash function). So index into your actual table, and check to see what's stored there. If there's a value stored there, then the url is a member of the set. This also takes a constant amount of time.

Does this help?

But that check isn't a constant time lookup. The lookup time can vary. (Analogously, a lookup in a phone book can vary in time; we can't necessarily go to the exact spot the first time.) So the total time for both steps must vary as well. I think.

That's not what's going on here. Instead, you use the value as in input into a function that tells you where to look for it, then you look, to see if it's there.

If it's not there, it won't be anywhere else, so you don't have to keep looking. Things get interesting with collisions but that's a subject for another time.