Recommended
Recommended
More Related Content
Similar to Bw tree presentation
Similar to Bw tree presentation (20)
Recently uploaded
Recently uploaded (20)
Bw tree presentation
- 2. 2 Key Features Implementation SMO Optimization Table of Contents
- 3. 3 Key Features Implementation SMO Optimization Table of Contents
- 4. 4 Latch-free Key Features Latch-free approach ensures a thread never yields in the face of conflict. Thus increase level of concurrency with multi-core CPUs. State changes are made using atomic CaS instructions.
- 5. 5 Mapping Table Key Features In order to implement latch-free design, Bw-tree uses CaS instruction to modify data. Mapping Table is helping tool that maps logical page to physical page with inter-links in Bw-Tree. Thus making atomic updates of several references to a tree node possible. Δ Remove PID Ptr L P R S Node L Node R Node P Node S
- 6. 6 Delta Updates Key Features Good multi-core processor performance depends on high CPU cache hit ratios. Instead of updating memory in place(which results in cache invalidation), Bw-Tree uses delta updates to prepend changes. K1 K3 K5 K8 V1 V3 V5 V8 Δdelete [K5, V5] Δinsert [K4, V4] }Delta Chain
- 7. 7 High Performance Key Features K1 K3 K5 K8 V1 V3 V5 V8 Δdelete [K5, V5] Δinsert [K4, V4] }Delta Chain + = High Performance
- 8. 8 Table of Contents Key Features Implementation SMO Optimization
- 9. 9 Mapping Table Implementation Every node have two inbound pointers from parent & left sibling. Meaning it is hard to update both pointers atomically. Bw-Tree use mapping table to translate PID into physical pointer. In this way, no matter how many inbounds node encounters, modification can be made atomically with one CaS instruction. logical pointer: parent-child, left-right sibling pointer. physical pointer: Mapping table-node, pointers within logical node(pointer for merge SMO).
- 10. 10 Logical Node Base Node inner base node: sorted (key, nodeID) array leaf base node : sorted (key, value) array Implementation K1 K3 K5 K8 V1 V3 V5 V8 Δdelete [K5, V5] Δinsert [K4, V4] Delta Chain metadata metadata Base Node metadata } Inbound pointer
- 11. 11 Logical Node Base Node inner base node: sorted (key, nodeID) array leaf base node : sorted (key, value) array Implementation Metadata low-key high-key right sibling size depth offset LSN The smallest key stored at the logical node The smallest key of a logical node’s right sibling The ID of the logical node’s right sibling The number of items in the logical node The number of records in the logical node’s Delta Chain The location of the inserted or deleted item in the base node Used to enforce WAL protocol K1 K3 K5 K8 V1 V3 V5 V8 Δdelete [K5, V5] Δinsert [K4, V4] Delta Chain metadata metadata Base Node metadata } Inbound pointer
- 12. 12 Logical Node Base Node Delta Chain inner base node: sorted (key, nodeID) array leaf base node : sorted (key, value) array singly linked list that holds history of modification All inbound pointer points to the head of Delta Chain Implementation Metadata low-key high-key right sibling size depth offset LSN The smallest key stored at the logical node The smallest key of a logical node’s right sibling The ID of the logical node’s right sibling The number of items in the logical node The number of records in the logical node’s Delta Chain The location of the inserted or deleted item in the base node Used to enforce WAL protocol K1 K3 K5 K8 V1 V3 V5 V8 Δdelete [K5, V5] Δinsert [K4, V4] Delta Chain metadata metadata Base Node metadata } Inbound pointer
- 13. 13 Delta Updates All page state changes are done by creating a delta record and prepending it to an existing page state. Implementation K1 K3 K5 K8 V1 V3 V5 V8 Δdelete [K5, V5] Δinsert [K4, V4] } Delta Chain metadata metadata Base Node metadata
- 14. 14 Delta Updates Implementation Only one delta update can be succeed using CaS instruction. If it fails, thread will retry All page state changes are done by creating a delta record and prepending it to an existing page state. K1 K3 K5 K8 V1 V3 V5 V8 Δdelete [K5, V5] Δinsert [K4, V4] Delta Chain metadata metadata Base Node metadata}
- 15. 15 Delta Updates Implementation K1 K3 K5 K8 V1 V3 V5 V8 Δdelete [K5, V5] Δinsert [K4, V4] metadata metadata metadata Mapping Table ptr.
- 16. 16 Delta Updates Implementation K1 K3 K5 K8 V1 V3 V5 V8 Δdelete [K5, V5] Δinsert [K4, V4] metadata metadata metadata Δinsert [K2, V2] metadata Δdelete [K8, V8] metadata t1 t2 Mapping Table ptr. 1. t1 & t2 make delta record and prepend it to the head
- 17. 17 Delta Updates Implementation K1 K3 K5 K8 V1 V3 V5 V8 Δdelete [K5, V5] Δinsert [K4, V4] metadata metadata metadata Δinsert [K2, V2] metadata Δdelete [K8, V8] metadata t1 t2 try CaS & failed try CaS & succeed 1. t1 & t2 make delta record and prepend it to the head 2. Both trying CaS instruction on mapping table. Only t1 succeed.
- 18. 18 Delta Updates Implementation K1 K3 K5 K8 V1 V3 V5 V8 Δdelete [K5, V5] Δinsert [K4, V4] metadata metadata metadata Δinsert [K2, V2] metadata Δdelete [K8, V8] metadata t1 t2 Abort & Retry 1. t1 & t2 make delta record and prepend it to the head 2. Both trying CaS instruction on mapping table. Only t1 succeed. 3. t2 abort delta record & retry whole process
- 19. 19 Page Search Implementation metadata K1 K3 K5 K8 V1 V3 V5 V8 Δdelete [K5, V5] Δinsert [K4, V4] Δupdate [K8, V'8] metadata metadata metadata 1. Thread travels delta chain to find the search key
- 20. 20 Page Search Implementation 1. Thread travels delta chain to find the search key 2. If key is present in delta chain and delta record is I.insert or update search succeeds and returns the record II. delete search fails metadata K1 K3 K5 K8 V1 V3 V5 V8 Δdelete [K5, V5] Δinsert [K4, V4] Δupdate [K8, V'8] metadata metadata metadata
- 21. 21 Page Search Implementation 1. Thread travels delta chain to find the search key 2. If key is present in delta chain and delta record is I.insert or update search succeeds and returns the record II. delete search fails 3. If not, thread performs binary search on base nodemetadata K1 K3 K5 K8 V1 V3 V5 V8 Δdelete [K5, V5] Δinsert [K4, V4] Δupdate [K8, V'8] metadata metadata metadata
- 22. 22 Consolidation Implementation delta chain length↑ == overhead of traversing tree↑ K1 K3 K5 K8 V1 V3 V5 V8 Δdelete [K5, V5] Δinsert [K4, V4] PID Ptr
- 23. 23 Consolidation Implementation K1 K3 K5 K8 V1 V3 V5 V8 Δdelete [K5, V5] Δinsert [K4, V4] ① metadata K1 K3 K5 K8 V1 V3 V5 V8 New base node PID Ptr delta chain length↑ == overhead of traversing tree↑ 1.The thread creates new base node.
- 24. 24 Consolidation Implementation K1 K3 K5 K8 V1 V3 V5 V8 Δdelete [K5, V5] Δinsert [K4, V4] ② delete② insert metadata K1 K3 K4 K5 K8 V1 V3 V4 V5 V8 New base node PID Ptr delta chain length↑ == overhead of traversing tree↑ 1.The thread creates new base node. 2.Applies the delta chain to new base node.
- 25. 25 Consolidation Implementation 1.The thread creates new base node. 2.Applies the delta chain to new base node. 3.Change mapping table's physical pointer to new node and reclaim old logical node when it is safe to do(using epoch-mechanism) ③ CaS K1 K3 K5 K8 V1 V3 V5 V8 Δdelete [K5, V5] Δinsert [K4, V4] metadata K1 K3 K4 K8 V1 V3 V4 V8 New base node PID Ptr delta chain length↑ == overhead of traversing tree↑
- 26. 26 Range Search Implementation Page P Page R Page Q K1 K3 K5 K8 V1 V3 V5 V8 K17 K19 K20 K22 V17 V19 V20 V22 K10 K13 K15 K16 V10 V13 V15 V16 Min key cursor A range scan is specified by a key range. A cursor is set for providing how far search is progressed.
- 27. 27 Range Search Implementation Page P Page R Page Q K1 K3 K5 K8 V1 V3 V5 V8 K17 K19 K20 K22 V17 V19 V20 V22 K10 K13 K15 K16 V10 V13 V15 V16 Min key cursor A range scan is specified by a key range. A cursor is set for providing how far search is progressed. 1.Construct a vector of records could be part of the scan.
- 28. 28 Range Search Implementation Page P Page R Page Q K1 K3 K5 K8 V1 V3 V5 V8 K17 K19 K20 K22 V17 V19 V20 V22 K10 K13 K15 K16 V10 V13 V15 V16 Min key cursor 1.Construct a vector of records could be part of the scan. 2."next record" operation is atomic but entire scan is not. A range scan is specified by a key range. A cursor is set for providing how far search is progressed.
- 29. 29 Range Search Implementation Page P Page R Page Q K1 K3 K5 K8 V1 V3 V5 V8 K17 K19 K20 K22 V17 V19 V20 V22 K10 K13 K15 K16 V10 V13 V15 V16 Min key cursor If update has been occurred, reconstruct record vector. So check is needed for update has affected the subrange in our record vector.
- 30. 30 Garbage Collection Implementation 1.A latch-free environment, so readers can be active even being updated. 2.Not to deallocate the old page while another threads still accessing. 3.By using "epoch" mechanism, protect objects being deallocated. It has two ways for Garbage Collection
- 31. 31 Garbage Collection Centralized scheme Implementation Epoch E1 Count = 0 NULL Garbage nodes 1.This is the final state of one epoch. No enrolled threads in epoch, ∴ garbage nodes are ready to be reclaimed. ①
- 32. 32 Garbage Collection Centralized scheme Implementation 1.This is the final state of one epoch. No enrolled threads in epoch, ∴ nodes are ready to be reclaimed. 2.New epoch object is appended at every fixed intervals. Epoch E1 Count = 0 Epoch E2 Count = 0 NULL ②
- 33. 33 Garbage Collection Centralized scheme Implementation 1.This is the final state of one epoch. No enrolled threads in epoch, ∴ nodes are ready to be reclaimed. 2.New epoch object is appended at every fixed intervals. 3.Node must enrolls itself to the current epoch object before access to the tree. Epoch E1 Count = 0 Epoch E2 Count = 2 NULL③
- 34. ④ 34 Garbage Collection Centralized scheme Implementation Epoch E1 Count = 0 Epoch E2 Count = 2 CaS NULL 1.This is the final state of one epoch. No enrolled threads in epoch, ∴ nodes are ready to be reclaimed. 2.New epoch object is appended at every fixed intervals. 3.Node must enrolls itself to the current epoch object before access to the tree. 4.t2 add new node to garbage list. But nodes are not reclaimed until all threads exit.
- 35. 35 Garbage Collection Centralized scheme Implementation Epoch E1 Count = 0 Epoch E2 Count = 2 CaS NULL Changing global var. "Count" becomes bottleneck because of cache coherence traffic.
- 36. 36 Garbage Collection Centralized scheme Implementation Epoch E1 Count = 0 Epoch E2 Count = 2 CaS NULL Changing global var. "Count" becomes bottleneck because of cache coherence traffic. How to avoid using global memory?
- 37. 37 Garbage Collection Decentralized scheme Implementation Each worker thread maintains a private epoch(elocal) Global Epoch eglobal = 103 Local thread t1 elocal = 102 Local thread t2 elocal = 103
- 38. 38 Garbage Collection Decentralized scheme Implementation Each worker thread maintains a private epoch(elocal) and linked list of objects that are marked for deletion(edelete) Global Epoch eglobal = 103 Local thread t1 elocal = 102 Local thread t2 elocal = 103 edelete = 98 edelete = 100 edelete = 103
- 39. Local thread t2 elocal = 100 39 Garbage Collection Decentralized scheme Implementation 1.Thread copies eglobal to its elocal at the beginning of new operation. Global Epoch eglobal = 102 Local thread t1 elocal = 102 edelete = 99 ①
- 40. Local thread t2 elocal = 100 40 Garbage Collection Decentralized scheme Implementation 1.Thread copies eglobal to its elocal at the beginning of new operation. 2.When garbage is created, edelete is tagged with latest eglobal Global Epoch eglobal = 102 Local thread t1 elocal = 102 edelete = 99 edelete = 102 ②
- 41. Local thread t2 elocal = 100 41 Garbage Collection Decentralized scheme Implementation 1.Thread copies eglobal to its elocal at the beginning of new operation. 2.When garbage is created, edelete is tagged with latest eglobal 3.At the end of operation, thread copies eglobal to its elocal again. Global Epoch eglobal = 103 Local thread t1 elocal = 103 edelete = 99 edelete = 102 Periodically increment ③
- 42. 42 Garbage Collection Decentralized scheme Implementation 1.Thread copies eglobal to its elocal at the beginning of new operation. 2.When garbage is created, edelete is tagged with latest eglobal 3.At the end of operation, thread copies eglobal to its elocal again. 4.Initiate Garbage Collection Global Epoch eglobal = 103 Local thread t1 elocal = 103 edelete = 99 edelete = 102 ④ reclaim Thread retrieves the elocal from all other threads and reclaim any edelete that is less than the minimum elocal Local thread t2 elocal = 100 minimum elocal = 100
- 43. 43 Table of Contents Key Features Implementation OptimizationSMO
- 44. ② 44 Node Split SMO PID Ptr L P R S Node L Node R Node P Node S ① Accessor thread notices node size ≥ threshold ② Creates new base Node S with consolidated upper half of Node L ① Not CaS Node S is still invisible to other threads and Node L still has all the records
- 45. ③ 45 Node Split SMO ③ add Δsplit to original node L Δsplit has separator key Ks & logical pointer to new node Δsplit also informs other threads that SMO is ongoing. PID Ptr L P R S Node L Node R Node P Node S Δ SplitCaS
- 46. ③ 46 Node Split SMO ③ add Δsplit to original node L Δsplit has separator key Ks & logical pointer to new node Δsplit also informs other threads that SMO is ongoing. PID Ptr L P R S Node L Node R Node P Node S Δ SplitCaS Half Split
- 47. 47 Node Split SMO ④ add Δseparator to parent node P ④ PID Ptr L P R S Node L Node R Node P Node S Δ Split CaS Δ separator Δseparator has separator key KL, KS & logical pointer to new node
- 48. 48 Node Split SMO What if parent node is merged to other node? PID Ptr L P R S Node L Node R Node P Node S Δ Split Δ separator
- 49. 49 Node Split SMO PID Ptr L P R S Node L Node R Node P Node S Δ Split Δ separator By epoch mechanism we are guaranteed to see Δremove of parent node ∴ we can find appropriate left sibling of parent to insert Δseparator What if parent node is merged to other node?
- 50. 50 Node Merge SMO Δ Remove PID Ptr L P R S Node L Node R Node P Node S ① ① Accessor thread notices node size ≤ threshold thread is only allowed to merge with left sibling
- 51. 51 Node Merge SMO ② add Δremove to node R This stops all further use of node R. A thread encountering a Δremove needs to read or update the contents previously contained in R by going to the left sibling Δ Remove PID Ptr L P R S Node L Node R Node P Node S ②
- 52. ③ 52 Node Merge SMO ③ add Δmerge to left sibling node L Δmerge physically points to node R. After ∆merge, L and R are considered as part of the same logical node. ∆merge contains a merge key (copied from R’s low-key) CaS Δ Remove PID Ptr L P R S Node L Node R Node P Node S Δ Merge Logical Node L
- 53. ⑤ 53 Node Merge SMO ④ add ΔSeparator to parent node P This record indicates R is deleted & L's new key range ⑤ delete Δremove & PID for node R only after epoch mechanism says it is safe to do so CaS Δ Remove PID Ptr L P R S Node L Node R Node P Node S Δ Merge Δ Separator ④ low-key from L high-key from R
- 54. 54 Table of Contents Key Features Implementation SMO Optimization
- 55. 55 Possible Optimization Optimization •retry CaS not from root but from parent. •don't abandon failed consolidation. add inserted delta on created consolidation node and retry. •consolidate periodically. •Change CaS to TaS
- 56. 56 References References •David B. Lomet, Sudipta Sengupta, and Justin J. Levandoski. 2013. The Bw-Tree: A B-tree for New Hardware Platforms. •Ziqi Wang, Andrew Pavlo, Hyeontaek Lim, Viktor Leis, Huanchen Zhang, Michael Kaminsky, and David G. Anderson. 2018. Building a Bw-Tree Takes More Than Just Buzz Words