1 / 33

The MV3R-Tree: A Spatio-Temporal Access Method for Timestamp and Interval Queries

The MV3R-Tree: A Spatio-Temporal Access Method for Timestamp and Interval Queries. Yufei Tao and Dimitris Papadias Hong Kong University of Science and Technology Present by Guangyue Jia. Overview. Motivation Related works MV3R-tree Strong and weak points Relation to our project

liona
Download Presentation

The MV3R-Tree: A Spatio-Temporal Access Method for Timestamp and Interval Queries

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. The MV3R-Tree: A Spatio-Temporal Access Method for Timestamp and Interval Queries Yufei Tao and Dimitris Papadias Hong Kong University of Science and Technology Present by Guangyue Jia

  2. Overview • Motivation • Related works • MV3R-tree • Strong and weak points • Relation to our project • Conclusion

  3. Motivation • Spatio-tempral queries are common. • Data: (tid, sid, x1, y1, x2, y2, t1, t2) • Query: space restriction + time restriction • Timestamp (or timeslice) query and interval query. • Process both timestamp and interval query efficiently.

  4. Overview • Motivation • Related works • MV3R-tree • Strong and weak points • Relation to our project • Conclusion

  5. Related works • MVB-tree: • Multi-version B-tree • HR-tree • Historical R-tree • 3D R-tree • 3 Dimension R-tree

  6. MVB-tree • Each entry has the form: <key, tstart, tend, point> • Insertions and deletions only happen at the current time. • An entry called alive at a timestamp t if tstart <=t<tend • Multiple roots and each root has a jurisdiction interval: • Minimum bounding lifespan of all the entries in the root. • Either none or b · pversion entries are alive for each timestamp t and each node except the roots. • Ensures that entries alive at the same timestamps are mostly grouped together. pversion =1/3 b=6 Example of MVB-tree

  7. Overflow • Insertion is carried out as B-tree except overflows. • Weak version overflow: block overflow. And it cause version split. • number of live entries in a new node must be in the range [b·psvu, b·psvo]. • Strong version overflow: number of live entries exceeds b·psvo. • Strong version overflow cause key split.

  8. Version split Description: 1, When weak version overflow. 2, All live entries are copied to a new node. 3, tstart modified to the current time. 4, tend of the live entries is changed from * to the current time. 5, create data redundancy. Example of MVB-tree Example: 1, insert <28, 4, *> at time 4. 2, A weak version overflow. 3, create new node D and copy the live entries to it. 4, all tstart are set to be 4 5, A ”dies”, all * are replaced by 4. Example of block overflow and version split

  9. Underflow • Deletion is carried out as B-tree except underflows. • Weak version underflow: number of live entries lower than b·pversion • Strong version underflow: number of live entries becomes lower than b·psvu. • Underflow: copy sibling node using only its live entries.

  10. Mergence and key split pversion =psvu=1/3 psvo=5/6 Root A B C <5, 1, *, A> <43, 1, *, B> <72, 1, *, C> <5, 1, *> <8, 1, *> <13, 1, *> <25, 1, 3> <27, 1, 3> <39, 1, 3> <43, 1, *> <48, 1, *> <52, 1, 2> <59, 1, 3> <27, 1, 3> <68, 1, 3> <72, 1, *> <78, 1, *> <83, 1, *> <95, 1, 3> <99, 1, *> <102, 1, *> 1, delete entry <48, 1, *> at timestamp 4. 2, B weak version underflow since only entry <43, 1, *> is alive. 3, copy live entries from sibling node C to C´. 3, insert <43, 4, *> into C´cause strong version overflow. 4, key split and node D and E are created.

  11. Mergence and key split pversion =psvu=1/3 psvo=5/6 Root A B C <5, 1, *, A> <43, 1, *, B> <72, 1, *, C> <5, 1, *> <8, 1, *> <13, 1, *> <25, 1, 3> <27, 1, 3> <39, 1, 3> <43, 1, *> <48, 1, 4> <52, 1, 2> <59, 1, 3> <27, 1, 3> <68, 1, 3> <72, 1, *> <78, 1, *> <83, 1, *> <95, 1, 3> <99, 1, *> <102, 1, *> 1, delete entry <48, 1, *> at timestamp 4. 2, B weak version underflow since only entry <43, 1, *> is alive. 3, copy live entries from sibling node C to C´. 3, insert <43, 4, *> into C´cause strong version overflow. 4, key split and node D and E are created.

  12. Mergence and key split pversion =psvu=1/3 psvo=5/6 Root A B C <5, 1, *, A> <43, 1, *, B> <72, 1, *, C> <72, 1, *, C´> <5, 1, *> <8, 1, *> <13, 1, *> <25, 1, 3> <27, 1, 3> <39, 1, 3> <43, 1, *> <48, 1, 4> <52, 1, 2> <59, 1, 3> <27, 1, 3> <68, 1, 3> <72, 1, *> <78, 1, *> <83, 1, *> <95, 1, 3> <99, 1, *> <102, 1, *> 1, delete entry <48, 1, *> at timestamp 4. 2, B weak version underflow since only entry <43, 1, *> is alive. 3, copy live entries from sibling node C to C´. 3, insert <43, 4, *> into C´cause strong version overflow. 4, key split and node D and E are created. C´ <72, 1, *> <78, 1, *> <83, 1, *> <99, 1, *> <102, 1, *>

  13. Mergence and key split pversion =psvu=1/3 psvo=5/6 Root A B C <5, 1, *, A> <43, 1, *, B> <72, 1, *, C> <43, 1, *, C´> <5, 1, *> <8, 1, *> <13, 1, *> <25, 1, 3> <27, 1, 3> <39, 1, 3> <43, 1, 4> <48, 1, 4> <52, 1, 2> <59, 1, 3> <27, 1, 3> <68, 1, 3> <72, 1, *> <78, 1, *> <83, 1, *> <95, 1, 3> <99, 1, *> <102, 1, *> 1, delete entry <48, 1, *> at timestamp 4. 2, B weak version underflow since only entry <43, 1, *> is alive. 3, copy live entries from sibling node C to C´. 3, insert <43, 4, *> into C´cause strong version overflow. 4, key split and node D and E are created. C´ <43, 4, *> <72, 1, *> <78, 1, *> <83, 1, *> <99, 1, *> <102, 1, *>

  14. Mergence and key split pversion =psvu=1/3 psvo=5/6 Root A B C <5, 1, *, A> <43, 1, *, B> <72, 1, *, C> <43, 4, *, D> <83, 4, *, E> <5, 1, *> <8, 1, *> <13, 1, *> <25, 1, 3> <27, 1, 3> <39, 1, 3> <43, 1, 4> <48, 1, 4> <52, 1, 2> <59, 1, 3> <27, 1, 3> <68, 1, 3> <72, 1, *> <78, 1, *> <83, 1, *> <95, 1, 3> <99, 1, *> <102, 1, *> 1, delete entry <48, 1, *> at timestamp 4. 2, B weak version underflow since only entry <43, 1, *> is alive. 3, copy live entries from sibling node C to C´. 3, insert <43, 4, *> into C´cause strong version overflow. 4, key split and node D and E are created. D E <43, 4, *> <72, 1, *> <78, 1, *> <83, 1, *> <99, 1, *> <102, 1, *>

  15. Historical R-tree • The structure maintains an R-tree for each timestamp. • Good for timestamp queries. • Need a lot of space. Example of an HR-tree

  16. 3D R-tree • Good for time interval queries A timestamp query in 3D R-tree

  17. Overview • Motivation • Related works • MV3R-tree • Strong and weak points • Relation to our project • Conclusion

  18. MV3R-tree • Intruduction • MVR-tree • Insertion and overflow handling in MVR-tree • Reinsertion • Deletion and underflow handling in MVR-tree • Auxiliary 3D R-tree • Query processing with MV3R-tree

  19. Introduction • An idea to deal with both timestamp and interval queries. • MVR-tree + 3DR-tree Overview of an MV3R-tree

  20. MVR-Tree • Multi-version R-tree. • Can contain multiple R-trees. • Each entry has the form <s, tstart, tend, pointer> 1, A to G are object boxes. 2, H, I, and J are leaf nodes. 3, C, I and K are alive (unbounded). A small MVR-tree with height 2 b=3 pversion=1/3

  21. Insertion and overflow handling in MVR-tree • Not overflow in intermediate nodes: • Set tstart to the current time. • Overflow in intermediate nodes: Insertion in intermediate nodes

  22. Insertion and overflow handling in MVR-tree • Not overflow in leaf nodes: • Set tstart to the current time. • Overflow in leaf nodes: Insertion in leaf nodess

  23. Reinsertion • Any leaf node of MVR-trees can store a reinserted entry. • Different from MVB-tree. • If general key split fails.

  24. Deletion and underflow handling in MVR-tree • Not underflow in intermediate nodes: • Modify tend from * to the current time. • Underflow in intermediate nodes: • Set tend of its live entries to current time. • All entries are dead. • Reinsert these entries to the most recent logical R-tree after setting tstart=current time. • MVB-tree handle underflows by merging with sibling nodes.

  25. Deletion and underflow handling in MVR-tree • Not underflow in leaf nodes: • Modify tend from * to the current time. • Underflow in leaf nodes: • First attempt to borrow a live entry from a sibling node. • entry reinsertion if the heuristic fails (cause redundancy). 1, At timestamp 2, entry A1 is deleted. 2, node A weak version underflow. 3, version condition must still be satisfied in B after removal. (removal of B2 or B3 can cause weak version underflow for timestamp 1.) Borrowing a live entry from a sibling node b=8, Pversion=1/3

  26. Auxiliary 3D R-tree • In order to process long time interval queries. • 3D R-tree is built on the leaves of the MVR-tree. • Whenever a leaf node of the MVR-tree is updated, the change is propagated to its entry in the 3D R-tree.

  27. Query processing with MV3R-tree • Choose between 3D R-tree and MVR-tree. • 3D R-tree is preferable for long time interval queries. • MVR-tree is good for timestamp queries. • Threshold is given for short time interval queries. • When use MVR-tree, it choose the MVR-trees whose roots´jurisdiction interval cover the queried timestamp or interval. • Duplicate visits for time interval queries. • Duplicate data is created in version split or entry reinsertion.

  28. Overview • Motivation • Related works • MV3R-tree • Strong and weak points • Relation to our project • Conclusion

  29. Strong and weak points • Strong points: • Appropriate related work and good structural sequence. • Good graphic explaination method. • Weak points: • No method to decide the parameters. • Does not give a solution to deal with the duplicate visit to the same node via different parents in query processing with MVR-trees.

  30. Overview • Motivation • Related works • MV3R-tree • Strong and weak points • Relation to our project • Conclusion

  31. Relation to our project • Similar work to our project but different direction. • MVB-tree is the extension of B-tree which we use in our project. • Many ideas can be used in our project.

  32. Overview • Motivation • Related works • MV3R-tree • Strong and weak points • Relation to our project • Conclusion

  33. Conclusion • MV3R-tree can handle both timestamp and interval queries efficiently. • But update process is complex. • Choose between MVR-tree and 3D R-tree is important. • Duplicate can only be reduced but not be avoided.

More Related