Timeline for A data structure / algorithm to combine search tree and hash table?
Current License: CC BY-SA 4.0
10 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Nov 1, 2021 at 9:30 | review | Close votes | |||
| Nov 16, 2021 at 3:03 | |||||
| Oct 6, 2021 at 19:01 | comment | added | Doc Brown | @Dims: there is pretty huge difference wether you are after a simple solution you can implement in main memory, in a single program, or if you need a distributed system with hundreds of machines working in parallel on externally stored data. When you ask for "Bigdata", you ask for the latter. So no. this is not just the same problem on a bigger scale, it is a way larger problem. | |
| Oct 6, 2021 at 18:00 | comment | added | Dims | @DocBrown in case of terabytes you meet the same problems in different form | |
| Oct 6, 2021 at 13:57 | comment | added | Doc Brown | @Dims: "Bigdata" usually means thousands of Terabytes of Data, in the order of magnitudes what companies like Amazon or Google process. You should really edit this misleading term out of the question. And to the order of running time: you probably meant O(m) where m is the number of cities returned. O(1) is nonsense. | |
| Oct 6, 2021 at 13:36 | answer | added | Philipp | timeline score: 2 | |
| Oct 6, 2021 at 13:10 | comment | added | Dims | I can put n items into hash table and will return (each) item in O(1). I need to do similar in 2D | |
| Oct 6, 2021 at 13:03 | comment | added | Stack Exchange Broke The Law | No, it is not possible to find O(n) items in O(1) time. I hope this seems trivial to you. Just returning the items will take O(n) time because there are O(n) items. | |
| Oct 6, 2021 at 12:22 | comment | added | Dims | @VincentSavard the question is general, so suppose it fits in memory. BidData means to avoid brute force scanning... | |
| Oct 6, 2021 at 12:19 | comment | added | Vincent Savard | "Suppose this database is bigdata." Can you clarify this statement? Does your data set fit in memory? | |
| Oct 6, 2021 at 11:32 | history | asked | Dims | CC BY-SA 4.0 |