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by colanderman
5587 days ago
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Ah thank you, this answers my original question. In response: 1) I contest that this is "unlikely" for SQL -- MySQL (unless I'm misremembering) orders data on disk by its primary key, which would be an equivalent optimization. (PostgreSQL does not do this to my knowledge.) 2) In my two queries above, I demonstrate both O(graph) and O(traversed) (in that order). At least in PostgreSQL, this is very much under control of the user as well, since WITH queries are evaluated in a specific order. 3) There is no way to specify such things in SQL. However most SQLs are designed with the idea that the query planner is smarter than you (it almost always is, at least in PostgreSQL), so you shouldn't be trying to specify execution plans anyway. Overall, I see no reason for graph databases & SQL to be separate. It seems that if graph DBs really only address performance issues as you claim, that one is throwing out the baby with the bathwater by creating a new kind of database rather than simply adding specialized optimizations to e.g. PostgreSQL. |
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In fact, looking up the edges is multiple seeks. For an edge (A, B), if the primary key is the row itself, edges are only stored in sequence if you are starting at node A.
Graph DB's usually cheat by store edges on both nodes, if possible within the same page as the node.
2) I'll take your word for it.
3) I generally agree that the query planner is smarter, but I'd be very surprised if that is true for complicated recursive queries. In particular, I really doubt that a query planner can exploit the structure of your data to improve things.
I.e., I really doubt the planner will know whether a DFS or BFS is better, or come up with heuristics to select the optimal path to go down (this is heavily dependent on data). Graph databases tend to provide such functionality.
I absolutely agree with you that better graph support for a SQL DB would be ideal.