1 / 11

Popular Ranking Algorithms

Popular Ranking Algorithms. Prepared by -Ranjan Dash. Contents. Efficient ways of Ranking Algorithms for ranking Sort Algorithm Scan Algorithm FA Algorithm TA Algorithm. Efficient ways of Ranking.

yul
Download Presentation

Popular Ranking Algorithms

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Popular Ranking Algorithms Prepared by -Ranjan Dash

  2. Contents • Efficient ways of Ranking • Algorithms for ranking • Sort Algorithm • Scan Algorithm • FA Algorithm • TA Algorithm

  3. Efficient ways of Ranking • Besides choosing a proper ranking function, efficient way to execute also decides the performance. • So given a ranking function the execution of this following a particular ranking algorithm plays a key role in the efficiency.

  4. Algorithms for ranking • Prominent Algorithms to get top K results are • Sort Algorithm • Scan Algorithm • FA Algorithm • TA Algorithm

  5. Sort Algorithm • Most simple way to decide the top K results of a ranking function like Score (ObjectId) = Linear combinations of attributes is to sort the result and take the top K. • This will take nlogn time. • Very slow for very large relations where n is quite large.

  6. Scan Algorithm • Keep K tuples in a buffer. • Scan this buffer for every tuple in the relation. • Replace the lowest one in the buffer if the input tuple is more than that. • Takes O(n.K) time. • Still low for a large n.

  7. FA Algorithm • Fagin’s Algorithm known as FA Algorithm. Developed by Ron Fagin. • Takes the help of data structures prepared offline. • Though there is a cost associated with these data structures, yet the amortized cost is very low. • Sorted access to the attributes. Supports GetNext() operation and is sequential. One sorted table per attribute. • Random access through the ObjectId. Supports Get(ObjId) operation. • The pre processing requires the preparation of above two types of data structures which will be used again and again during the processing.

  8. FA Algorithm • Step1 • Example of determining top 1 restaurant based on the given ranking function Score(RestId) = 2.Cusine + Location Sorted for Cusine Sorted for Location Original relation

  9. FA Algorithm • Step1 • Do the GetNext from both sorted tables in round robin. • Stop when K objects have been seen in common from all lists – 1 in our example RestId 4 is winner in our case Sorted for Location Sorted for Cusine

  10. FA Algorithm • Step2 • Random access to calculate the score for all visited tuples in step 1. • Take the top K after evaluation • This algorithm is applicable if the problem shows monotonic property. • The worst case will be same as scan algorithm. • The worst case memory requirement is unbounded.

  11. TA Algorithm • Known as Threshold Algorithm • Similar to FA but sorted access and random access are interleaved. • Step 1 • Do sorted access (and corresponding random accesses) until you have seen the top K answers. • Step 2 • Determine threshold value (Hypothetical tuple) based on objects currently seen under sorted access. • K objects with overall score ≥ threshold value ? Stop. • Else go to next entry position in sorted list and repeat step 1 • Faster than FA. • Requires less memory.

More Related