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Lecture 11 data structures and algorithms

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Lecture 11 data structures and algorithms

  1. 1. Data Structure and Algorithm (CS 102) Ashok K Turuk 1
  2. 2. m-Way Search Tree An m-way search tree T may be an empty tree. If T is non-empty, it satisfies the following properties: (i) For some integer m known as the order of the tree, each node has at most m child nodes. A node may be represented as A0 , (K1, A1), (K2, A2) …. (Km-1 , Am-1 ) where Ki 1<= i <= m-1 are the keys and Ai, 0<=i<=m-1 are the pointers to the subtree of T 2
  3. 3. m-Way Search Tree [2] If the node has k child nodes where k<=m, then the node can have only (k-1) keys, K1 , K2 , …… Kk-1 contained in the node such that Ki < Ki+1 and each of the keys partitions all the keys in the subtrees into k subsets [3] For a node A0 , (K1 , A1), (K2 , A2) , …. (Km-1 , Am-1 ) all key values in the subtree pointed to by Ai are less than the key Ki+1 , 0<=i<=m-2 and all key values in the subtree pointed to by Am-1 are greater than Km-1 3
  4. 4. m-Way Search Tree [4] Each of the subtree Ai , 0<=i<=m-1 are also m-way search tree 4
  5. 5. m-Way Search Tree [ m=5] 18 44 X 7 8 X X X 262 141 X X 148 151 172 186 77 10 X 92 X X 198 X 80 12 X 76 X X X X X X 272 286 350 X X X X 5
  6. 6. Searching in an m-Way Search Tree 18 44 X 7 8 X X X 262 141 X X 148 151 172 186 77 10 X 92 X X 198 X 80 12 X 76 Look for 77 X X X X X X 272 286 350 X X X X 6
  7. 7. Insertion in an m-Way Search Tree 18 44 X 7 8 X X X 262 141 X X 148 151 172 186 77 10 X 92 X X 198 X 80 12 X 76 Insert 6 X X X X X X 272 286 350 X X X X 7
  8. 8. Insertion in an m-Way Search Tree 18 44 X 6 X 7 8 X X X Insert 146 262 141 X X 148 151 172 186 77 10 X 92 X X 198 X 80 12 X 76 Insert 6 X X 146 X X X X 272 286 350 X X X X 8
  9. 9. Deletion in an m-Way Search Tree Let K be the key to be deleted from the m-way search tree. K Ai Aj K : Key Ai , Aj : Pointers to subtree 9
  10. 10. Deletion in an m-Way Search Tree [1] If (Ai = Aj = NULL) then delete K [2] If (Ai  NULL, Aj = NULL ) then choose the largest of the key elements K’ in the child node pointed to by Ai and replace K by K’. [3] If (Ai = NULL, Aj  NULL ) then choose the smallest of the key element K” from the subtree pointed to by Aj , delete K” and replace K by K”. 10
  11. 11. Deletion in an m-Way Search Tree [4] If (Ai  NULL, Aj  NULL ) then choose the largest of the key elements K’ in the subtree pointed to by Ai or the smallest of the key element K” from the subtree pointed to by Aj to replace K. 11
  12. 12. 5-Way Search Tree 18 44 X 7 8 X X X 262 141 X X 148 151 172 186 77 10 X 92 X X Delete 151 198 X 80 12 X 76 X X X X X X 272 286 350 X X X X 12
  13. 13. 5-Way Search Tree 18 44 X 7 8 X X X 262 141 X X 148 172 186 77 10 X 92 X X Delete 151 198 X 80 12 X 76 X X X X X 272 286 350 X X X X 13
  14. 14. 5-Way Search Tree 18 44 X 7 8 X X X 262 141 X X 148 151 172 186 77 10 X 92 X X Delete 262 198 X 80 12 X 76 X X X X X X 272 286 350 X X X X 14
  15. 15. 5-Way Search Tree 18 44 X 7 8 X X X 272 141 X X 148 151 172 186 77 10 X 92 X X Delete 262 198 X 80 12 X 76 X X X X X X 286 350 X X X 15
  16. 16. 5-Way Search Tree 18 44 X 7 8 X X X 262 141 X X 148 151 172 186 77 10 X 92 X X Delete 12 198 X 80 12 X 76 X X X X X X 272 286 350 X X X X 16
  17. 17. 5-Way Search Tree 18 44 X 7 X X 10 92 X X 262 141 X X 148 151 172 186 77 X Delete 12 198 X 80 X 8 76 X X X X X X 272 286 350 X X X X 17
  18. 18. B Trees B tree is a balanced m-way search tree A B tree of order m, if non empty is an mway search tree in which [i] the root has at least two child nodes and at most m child nodes [ii] internal nodes except the root have at least m/2 child nodes and at most m child nodes 18
  19. 19. B Trees [iii] the number of keys in each internal node is one less than the number of child nodes and these keys partition the keys in the subtrees of nodes in a manner similar to that of m-way search trees [iv] all leaf nodes are on the same level 19
  20. 20. B Tree of order 5 48 31 56 45 46 10 X 18 X X X X 36 X X 21 47 58 40 X 87 X X 42 X X 62 X 64 88 X X 75 X X X X 49 67 X 100 112 X X X 85 51 X 52 X X 20
  21. 21. Searching a B Tree Searching for a key in a B-tree is similar to the one on an m-way search tree. The number of accesses depends on the height h of the B-tree 21
  22. 22. Insertion in a B-Tree A key is inserted according to the following procedure [1] If the leaf node in which the key is to be inserted is not full, then the insertion is done in the node. A node is said to be full if it contains a maximum of (m-1) keys given the order of the B-tree to be m 22
  23. 23. Insertion in a B-Tree [2] If the node were to be full then insert the key in order into the existing set of keys in the node. Split the node at its median into two nodes at the same level, pushing the median element up by one level. Accommodate the median element in the parent node if it is not full. Otherwise repeat the same procedure and this may call for rearrangement of the keys in the root node or the formation of new root itself. 23
  24. 24. 5-Way Search Tree 8 2 X 7 X X 96 116 37 46 55 86 X X X X X 137 145 104 110 X X X X X Insert 4, 5, 58, 6 in the order X
  25. 25. 5-Way Search Tree 8 96 116 37 46 55 86 X X X X X 2 X 4 X 137 145 104 110 X X X X 7 X X Search tree after inserting 4 X X
  26. 26. 5-Way Search Tree 8 96 116 37 46 55 86 X X X X X 2 X 4 X 5 X 137 145 104 110 X X X X X 7 X X Search tree after inserting 4, 5 X
  27. 27. 5-Way Search Tree 8 96 116 37 46 55 86 X X X X X 2 X 4 X 5 X 137 145 104 110 X X X X X 7 X X 37,46,55,58,86 Split the node at its median into two node, pushing the median element up by one level X
  28. 28. 5-Way Search Tree 8 37 X 2 X 4 X 5 X X 116 X X 58 X 137 145 104 110 46 X 7 96 Insert 55 in the root X 86 X X X X X X X
  29. 29. 5-Way Search Tree 8 55 37 46 X 2 X 4 X 5 X X 7 X 96 116 X X 58 X 137 145 104 110 X X X X X 86 X X Search tree after inserting 4, 5, 58 X
  30. 30. 5-Way Search Tree 8 55 37 46 X 2 X 4 X 5 X X 7 X 96 Insert 6 116 X X 58 X 137 145 104 110 X X X X X 86 X X 2,4,5,6,7 Split the node at its median into two node, pushing the median element up by one level X
  31. 31. 5-Way Search Tree 8 55 37 46 X 2 X 4 X X 6 X X 96 Insert 5 at the root 137 145 104 110 X X 58 7 X 116 X X 86 X X X X X X X
  32. 32. 5-Way Search Tree 55 5 96 8 37 X 2 X 4 X 6 X X 116 X X 58 7 X 137 145 104 110 46 X Insert 5 at the root X X 86 X X X X X X X
  33. 33. 5-Way Search Tree 55 5 2 X 96 8 4 X Insert 5 at the root 37 X X 58 46 X X X 116 137 145 86 X X X 104 110 6 X 7 X X X X X X X
  34. 34. Deletion in a B-Tree It is desirable that a key in leaf node be removed. When a key in an internal node to be deleted, then we promote a successor or a predecessor of the key to be deleted ,to occupy the position of the deleted key and such a key is bound to occur in a leaf node. 34
  35. 35. Deletion in a B-Tree Removing a key from leaf node: If the node contain more than the minimum number of elements, then the key can be easily removed. If the leaf node contain just the minimum number of elements, then look for an element either from the left sibling node or right sibling node to fill the vacancy. 35
  36. 36. Deletion in a B-Tree If the left sibling has more than minimum number of keys, pull the largest key up into the parent node and move down the intervening entry from the parent node to the leaf node where key is deleted. Otherwise, pull the smallest key of the right sibling node to the parent node and move down the intervening parent element to the leaf node. 36
  37. 37. Deletion in a B-Tree If both the sibling node has minimum number of entries, then create a new leaf node out of the two leaf nodes and the intervening element of the parent node, ensuring the total number does not exceed the maximum limit for a node. If while borrowing the intervening element from the parent node, it leaves the number of keys in the parent node to be below the minimum number, then we propagate the process upwards ultimately resulting in a reduction of the height of B-tree 37
  38. 38. B-tree of Order 5 110 65 86 70 81 32 44 X X 120 226 X X X 115 118 X X 90 X X 200 221 X X X X 95 100 X X X 300 440 X X X 550 X 601 X Delete 95, 226, 221, 70 38
  39. 39. B-tree of Order 5 110 65 86 70 81 32 44 X X 120 226 X X X 115 118 X X 90 X X 200 221 X X X X 100 X X 300 440 X X X 550 X 601 X B-tree after deleting 95 39
  40. 40. B-tree of Order 5 110 65 86 70 81 32 44 X X 120 300 X X X 115 118 X X 90 X X 200 221 X X X X 100 X X 300 440 X X X 550 X 601 X 40
  41. 41. B-tree of Order 5 110 Delete 221 65 86 70 81 32 44 X X 120 300 X X X 115 118 X X 90 X X X 200 221 X X X 100 X X 440 X 550 601 X X X B-tree after deleting 95, 226 41
  42. 42. B-tree of Order 5 Delete 70 110 65 86 70 81 32 44 X X 120 440 X X X 115 118 X X 90 X X X 200 300 X X X 100 X X 550 X X 601 X B-tree after deleting 95, 226, 221 42
  43. 43. B-tree of Order 5 Delete 65 110 65 86 120 440 115 118 32 44 65 81 X X X X X X 90 X X X 200 300 X X X 100 X X 550 X X 601 X 43
  44. 44. B-tree of Order 5 86 110 120 440 115 118 32 44 65 81 X X X X X X 90 X X X 200 300 X X X 100 X X 550 X X 601 X B-tree after deleting 95, 226, 221, 70 44
  45. 45. Heap Suppose H is a complete binary tree with n elements H is called a heap or maxheap if each node N of H has the following property Value at N is greater than or equal to the value at each of the children of N. 45
  46. 46. Heap 97 95 88 66 55 66 35 40 18 48 48 95 55 62 77 38 25 26 24 30 9 7 8 8 9 5 6 6 5 5 9 5 4 8 6 6 3 5 4 8 5 5 6 2 7 7 2 5 3 8 1 8 4 0 3 0 2 6 2 4 1 2 3 4 5 6 7 8 9 1 0 11 1 2 1 3 1 4 1 5 1 6 1 7 1 8 1 9 2 0 46
  47. 47. Inserting into a Heap Suppose H is a heap with N elements Suppose an ITEM of information is given. Insertion of ITEM into heap H is given as follows: [1] First adjoin ITEM at the end of H so that H is still a complete tree, but necessarily a heap [2] Let ITEM rise to its appropriate place in H so that H is finally a heap 47
  48. 48. Heap Insert 70 97 95 88 66 55 66 35 40 18 48 55 62 77 38 25 70 26 24 30 48 95 9 7 8 8 9 5 6 6 5 5 9 5 4 8 6 6 3 5 4 8 5 5 6 2 7 7 2 5 3 8 1 8 4 0 3 0 2 6 2 4 1 2 3 4 5 6 7 8 9 1 0 11 1 2 1 3 1 4 1 5 1 6 1 7 1 8 1 9 2 0 48
  49. 49. Heap Insert 70 97 95 88 66 55 66 35 40 18 48 55 62 77 38 25 70 26 24 30 48 95 9 7 8 8 9 5 6 6 5 5 9 5 4 8 6 6 3 5 4 8 5 5 6 2 7 7 2 5 3 8 1 8 4 0 3 0 2 6 2 4 1 2 3 4 5 6 7 8 9 1 0 11 1 2 1 3 1 4 1 5 1 6 1 7 1 8 1 9 2 0 49
  50. 50. Heap Insert 70 97 95 88 66 66 9 7 1 18 55 70 35 40 55 62 38 25 77 48 26 24 30 48 95 8 8 9 5 6 6 5 5 9 5 4 8 6 6 3 5 4 8 5 5 6 2 7 7 2 5 3 8 1 8 4 0 3 0 2 6 2 4 2 3 4 5 6 7 8 9 1 0 11 1 2 1 3 1 4 1 5 1 6 1 7 1 8 1 9 2 0 50
  51. 51. Heap Insert 70 97 95 88 66 66 9 7 1 18 70 55 35 40 55 62 38 25 77 48 26 24 30 48 95 8 8 9 5 6 6 5 5 9 5 4 8 6 6 3 5 4 8 5 5 6 2 7 7 2 5 3 8 1 8 4 0 3 0 2 6 2 4 2 3 4 5 6 7 8 9 1 0 11 1 2 1 3 1 4 1 5 1 6 1 7 1 8 1 9 2 0 51
  52. 52. Build a Heap Build a heap from the following list 44, 30, 50, 22, 60, 55, 77, 55 52
  53. 53. 44, 30, 50, 22, 60, 55, 77, 55 44 44 44 30 30 50 50 30 50 44 30 44 22 Complete the Rest Insertion 77 55 50 60 30 44 55 22 53
  54. 54. Deleting the Root of a Heap Suppose H is a heap with N elements Suppose we want to delete the root R of H Deletion of root is accomplished as follows [1] Assign the root R to some variable ITEM [2] Replace the deleted node R by the last node L of H so that H is still a complete tree but necessarily a heap [3] Reheap. Let L sink to its appropriate place in H so that H is finally a heap. 54
  55. 55. 95 85 15 70 33 55 22 20 15 30 85 65 22 33 55 15 70 20 15 85 85 22 55 15 55 70 33 20 15 65 30 30 65 22 15 70 33 30 65 20 15 55

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