Is it because of the tree structure of the index?
Is it because of the tree structure of the index?
I'm not 100% sure I understand exactly what you're asking, but, perhaps some more info will be useful. First off, the goal with this isn't just to find the next unique item, it's to find the set of all the unique items, so you'd need to iterate the search, which is basically what the skipscan is doing internally.
Internally, the index is using something like a binary search (it's a btree, so slightly different, IIRC) to skip to the next unique item. A lot of the work here was in teaching the planner / executor to actually do that rather than the simpler, less efficient way that PG usually does it (brute force unique over a full scan). There's some more complexity on top of that in terms of teaching it to do that over all the chunks and then combine the results (because each has a separate index) and some more complexity in terms of knowing when you can use multi-column indexes and the like, but at its most basic level, it basically is using some sort of binary search to find the next item. But perhaps I'm missing what you're asking, feel free to clarify if I can better help here...
Of course, things get more complicated when more tuples need to be distinct but I was a bit confused as to why the ordered property was not exploited by PG before (and still is not).
Say you have a table with two rows. One is time, the other is temperature. Your table is sorted by time, but you want all the unique temperatures.
Given the temperatures are unordered, you can't perform a binary search. If you also create a proper index against the times, your temperatures will also live in leaves of a tree that you'll need to access to get the values.
So trick 1 is to just index that column, like you said, a precomputed binary search if you will But since we're interested in distinct queries, we can optimize further by pointing to the next greatest value with the index tree too (hence skip scan.)
You mean two columns, right?