CN102521334A - Data storage and query method based on classification characteristics and balanced binary tree - Google Patents
Data storage and query method based on classification characteristics and balanced binary tree Download PDFInfo
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Abstract
The invention discloses a data storage and query method based on classification characteristics and balanced binary tree. The method comprises the following steps: constructing a balanced binary tree to create nodes; dynamically classifying and storing data information in corresponding nodes according to the sequence of inorder traversal, preorder traversal and postorder traversal; and inputting an enquired content, dynamically traversing the AVL tree to obtain the desired data information. The method provided by the invention can lower the time complexity of dynamic query to static query level, thereby greatly improving storage and query efficiency. The method has the advantages of high speed, low energy consumption, less memory usage, and simple algorithm, and can be implemented by a plurality of languages. The method is widely suitable for data management in the communication field, in particular to massive data storage and query in communication of the internet of things.
Description
Technical field
The invention belongs to storage, the querying method field of big data quantity in the Internet of Things communications field, particularly a kind of data storage, querying method based on sort feature and balanced binary tree.
Background technology
In the communication technology, the traditional data querying method comprises static lookup method and dynamic lookup method.The static lookup method comprises sequential search, binary chop, index search; Dynamically lookup method comprises that binary search tree, B-set, Hash (Hash) is searched method, key tree etc.
Hypothesis is for the look-up table of n record in the sequential search, and the average length of search when it is searched successfully is ASL (Average Search Length), ASL=
=
, and number of comparisons is=n-i+1 that the probability that finds is P
i=
ASL=nP then
1+ (n-1) P
2+ ... + 2P
N-1+ P
n=
=
, then its algorithm time complexity is O (n).
Binary chop is n=2 for the length of supposing ordered list generally speaking
h-1, at searching under the situation that probability all equates of each record, i.e. P
i=
, can get its ASL=
Log
2(n+1)-1, when the n value greater than 50, its ASL can be approximately log
2(n+1)-1, so the time complexity of its algorithm is O (log
2N).
The index search method is a kind of method between sequential search and binary chop, can be described as " piecemeal is orderly " again and searches method; Be about to sequence list and carry out piecemeal; Less than the minimum key word in back, inner key word is not necessarily orderly by last maximum key word, and the length of supposing concordance list is b; The length of sequence list is n, then its ASL=ASL
Index(b)+ASL
Seq(n/b) ≈ log
2(b+1)-and 1+ (n/b+1)/2, so the time complexity of its algorithm is (O (log
2N)+O (n))/2.
Binary search tree is searched method, and for the binary search tree that n node arranged, its height of tree is log under balance
2N, then its time cost of at every turn searching is O (log
2N); Under extreme case as its n node become a straight chain table shape then the height of tree be n; For the time cost that finds each node is O (n), knows that again it is that the traversal time cost that inserts node is O (n), and then the time complexity of its total algorithm the best is O (nlog
2N), the poorest is O (n
2).
B-tree is a kind of multichannel search tree of balance, and key word (in order) sequence of inter-node is carried out binary chop, if hit then finish, otherwise son's node of the affiliated scope of entering key word of the inquiry; Repeat, be empty up to pairing son's pointer, or be leafy node, so the time complexity of its algorithm is O (log
2N).
Hash (Hash) searches method because the hash property of self makes that its search efficiency in being applied to classification searching is not high.
The key tree generally is used for special searching, and one " path " from the root to the leaf node corresponds to a key word, is not suitable for the inquiry of general big data quantity.
In the current Internet of Things communications field, the development of communication data technology more and more trends towards high real-time and hugeization.Traditional static lookup method is difficult to satisfy current big data quantity and handles the requirement to real-time like sequential search, binary chop, index search.And for dynamically searching (DST), like binary search tree, the B-tree, Hash (Hash) is searched method, key tree etc., its time complexity is higher than static lookup far away.
Summary of the invention
The present invention is directed to above deficiency, provide that a kind of speed to mass data is fast, energy consumption is low, committed memory is few, algorithm is simply based on data storage, the querying method of sort feature and balanced binary tree.
The present invention provides a kind of data storage, querying method based on sort feature and balanced binary tree (Adelson-Velskii-Landis tree), and implementation method may further comprise the steps:
1.1 the structure Adelson-Velskii-Landis tree is created node;
1.2, dynamically data information memory is arrived corresponding node according to traversal rule;
1.3 input needs information inquiring, dynamically travels through Adelson-Velskii-Landis tree, returns and searches failure up to finding required data message or having traveled through Adelson-Velskii-Landis tree.
Said Adelson-Velskii-Landis tree is orderly, and Adelson-Velskii-Landis tree is (middle preface, preorder, postorder) traversal rule in order, dynamically data information memory is arrived corresponding node.
Said node data memory structure is divided into C language and C Plus Plus by the language of realizing.
Concrete implementation method of the present invention is following:
(1) newly-built Adelson-Velskii-Landis tree, at first making up a node number according to the achievement rule that Adelson-Velskii-Landis tree is arranged is n, the height of tree is log
2The Adelson-Velskii-Landis tree of n increases node then.Each node is represented a feature class C
1,C
2,C
3,C
4C
N, comprising the information of one type of refinement in each node again, the refinement information in the node uses different data structure storage to be convenient to data information memory and to search according to the different language of realizing.
(2) in Adelson-Velskii-Landis tree, insert data message, insert for the rule of Adelson-Velskii-Landis tree node employing order (middle preface, preorder, postorder) traversal, the time complexity of its algorithm is log
2N can be divided into C Plus Plus realization and the realization of C language according to the language of realizing:
1. C Plus Plus is realized: the VECTOR class when data message need be stored, at first judges whether Adelson-Velskii-Landis tree is empty as data store organisation in the node in the employing C Plus Plus; If a then newly-built root node also is saved in root node with data message and returns simultaneously and preserve successfully; If not, then travel through Adelson-Velskii-Landis tree, judge whether it belongs to storage node; If then according to the rule of canned data, the information that needs are preserved is saved in corresponding node, and returns and preserve successfully; If not, execution in step (1) then, the data message with required preservation is saved in the newly-built node again, by return function saving result is returned at last and keeps supplying layer and call;
2. the C language is realized: utilize the structure variable to make up a structure struct; All nodes adopt the storage organization of doubly linked list; To be defined as the member variable of structure to all operations of node, when data message need be preserved, judge at first whether Adelson-Velskii-Landis tree is empty; If a then newly-built root node also is saved in root node with data message and returns simultaneously and preserve successfully; If not, then travel through Adelson-Velskii-Landis tree, judge whether to be storage node class; If then call corresponding preservation of preservation member object execution of structure and operate and return and preserve successfully; If not, execution in step (1) then, the data message with required preservation is saved in the newly-built node class again, by return function saving result is returned at last and keeps supplying layer and call.
(3) data message of inquiry Adelson-Velskii-Landis tree is O (log according to the time complexity of orderly Adelson-Velskii-Landis tree
2N), so the inquiry node needs log at most
2N access memory through the data message in the node is read in the buffer zone, utilized binary search, and its time complexity also is O (log
2N).Preservation implementation according to node also can be divided into C Plus Plus realization and the realization of C language:
1. C Plus Plus is realized: when input inquiry information, call and search function, judge at first whether Adelson-Velskii-Landis tree is empty; If then directly return tree for empty; If not, then travel through Adelson-Velskii-Landis tree, judge whether to be storage node; If, then continue the visit node information, and node information is loaded into buffer area, utilize dichotomy to search, and Query Result is kept supplying layer to return function call; If not, then return no node class and give return function;
2. the C language is realized: when needs data query information, then call the function of searching variable and correspondence thereof of structure variable, judge at first whether Adelson-Velskii-Landis tree is empty; If then directly return tree for empty; If not, then travel through Adelson-Velskii-Landis tree, judge whether to be storage node; If, then call the query manipulation member object of structure and carry out corresponding query manipulation, continue the refinement information in the visit node class, up to inquiring required result or inquire about all recorded informations, and Query Result composed to keep supplying to return function layer call; If not, then return no node class to return function keep supplying the layer call.
(4) deletion balanced binary tree data message, the data message of at first preserving the mode of deletion during deletion and needing to delete calls then and obtains deletion mode (AVLTreeDeleteStyle) function, specifically divides following two kinds of situation:
1. work as the AVLTreeDeleteStyle value and be deletion node C
iThe time, then directly travel through Adelson-Velskii-Landis tree, inquire about the node C of required deletion
i,, then return and do not have this node deletion failure if having traveled through all nodes does not find; If find direct deletion node C
i, and return and delete successfully; To delete the result at last and compose and keep supplying layer to return function and call, execution in step (5) simultaneously, the tree structure of adjustment balanced binary tree;
2. work as the AVLTreeDeleteStyle value and be deletion node C
iIn data the time, then at first travel through Adelson-Velskii-Landis tree, inquiry node C
i, traveled through all nodes and do not found then to return and do not have this node information deletion failure; If find the node C of required deletion
i, then continue to search the information in the node, up to finding required deleted data, with its deletion and return and delete successfully; Perhaps inquire about all records and do not found information needed, returned the failure of no datat record deletion; To delete at last the result compose to return function keep supplying the layer call.
(5) insertion and the deletion action to balanced binary tree (Adelson-Velskii-Landis tree) all can exert an influence to tree structure, in order to keep the minimum log of being of traversal of tree complexity
2N need carry out the equilibrating adjustment to tree, can divide following four kinds of situation:
1. the L type of balanced binary tree rotation; When Adelson-Velskii-Landis tree inserts (inserting node in the left child's of minimum subtree root node left subtree) or deletion action (node of deletion is the right child of minimum subtree root node and is leaf node); And the balance factor bf that satisfies minimum subtree then need carry out the L type and rotate the structure of regulating Adelson-Velskii-Landis tree greater than 1 o'clock;
2. the R type of balanced binary tree rotation; When Adelson-Velskii-Landis tree inserts (inserting node in the right child's of minimum subtree root node right subtree) or deletion action (node of deletion is the left child of minimum subtree root node and is leaf node); And the bf that satisfies minimum subtree root node need carry out R type rotation adjustment less than-1 o'clock;
3. the LR type of balanced binary tree rotation; When balanced binary tree inserts (inserting node in the right child's of minimum subtree root node left subtree); Satisfy simultaneously minimum subtree root node bf less than-1 and its left child bf greater than 1 o'clock, then need carry out the LR type and rotate the structure of regulating Adelson-Velskii-Landis tree;
4. the RL type of balanced binary tree rotation, when balanced binary tree inserts (inserting node in the left child's of minimum subtree root node right subtree), the bf that satisfies minimum subtree root node simultaneously greater than 1 and its right child bf less than-1 o'clock; Then need carry out the RL type and rotate the structure of regulating Adelson-Velskii-Landis tree.
(6) traversal of continuous and full Adelson-Velskii-Landis tree is the Adelson-Velskii-Landis tree of n for continuous and full nodal point number, its total L=log
2N level node, CL are current progression, D
CLFor the layer of current progression node apart from poor (nodal value between the adjacent tree layer poor); The traversal formula of all nodes is so: root node Pr=2
L-1, the father node of current node is P
F, its left child P
L=P
F-D
CL, its right child P
R=P
F+ D
CL, D
CL=2
L-CL-1, CL ∈ [1, L); The preorder traversal formula is: Pr=1, P
L=P
F+ 1, P
R=P
F+ D
CL, D
CL=2
L-CL, CL ∈ [1, L); The postorder traversal formula is: Pr=2
L-1, P
L=P
F-D
CL, P
R=P
F-1, D
CL=2
L-CL, CL ∈ [1, L).
The comparison of this method and existing method has following beneficial effect:
(1) this method algorithm complex is little, realizes simply realizing rapidly and efficiently storing and inquiring about.The tree that this method is n according to node of structure principle construction of Adelson-Velskii-Landis tree, then its height of tree is h=log
2N, promptly when data were inquired about, the algorithm complex of its traversal was not more than O (log
2N), dichotomy is adopted in the information inquiry in the node class simultaneously, and its algorithm complex also is O (log
2N), its algorithm complex is minimum in the search algorithm of current use, and the time complexity of dynamic queries is reduced to the rank of static inquiry, has improved the efficient of storage and inquiry greatly, reaches the requirement of fast query.
(2) this method algorithm complex is low, effectively reduces the access times of processor, reduces energy consumption.The algorithm complex of this method provides in last characteristics, and with respect to other algorithms of present use, algorithm complex is relatively low, when program run, can effectively reduce the access times of processor for internal memory, can effectively cut down the consumption of energy.
(3) this method can be rationally memory allocated space flexibly, save memory headroom, improve the memory source utilization factor.Because the method is to be applied to dynamic memory and to search, and is not to use specified distribution for the distribution of resource, (for example VECTOR in the C Plus Plus has the self-propagation characteristic and be based on the self-characteristic of used descriptive language; Doubly linked list in the C language also has dynamic insertion characteristic), reach memory space dynamic allocation.Use C Plus Plus to be based on and support what VECTOR realized, utilize the self-propagation characteristic that has of VECTOR itself, with the element distribution according to need storage unit that is categorized into concrete node; And use the C language to realize being based on the structure structure; Utilize the structure can related member variable, its member variable be set to a function, when data deposit in; Be categorized into the node place of feature class earlier; Function according to the member variable of corresponding node carries out handled again, and returns accordingly result and keep supplying layer and call, and its inherent treatment mechanism also is to utilize chained list to store in order.It not exclusively uses binary tree as memory carrier simultaneously, has saved the storage space that is used for binary tree front and back pointer, thereby has effectively saved memory source.
(4) can support multilingual to realize, have wide range of applications.The inventive method can realize that this bilingual is the main flow of current descriptive language, can the method be applied to large-scale database platform based on the C++/C language, also can be applied to small-sized data terminal and use, and its range of application is effectively expanded.
Description of drawings
Fig. 1 isEmbodiment of the invention Adelson-Velskii-Landis tree storage node composition;
Fig. 2 isEmbodiment of the invention Adelson-Velskii-Landis tree inserts process flow diagram;
Fig. 3 isEmbodiment of the invention Adelson-Velskii-Landis tree is searched process flow diagram;
Fig. 4 isEmbodiment of the invention Adelson-Velskii-Landis tree deletion process flow diagram;
Fig. 5 isEmbodiment of the invention Adelson-Velskii-Landis tree L type rotation synoptic diagram;
Fig. 6 isEmbodiment of the invention Adelson-Velskii-Landis tree R type rotation synoptic diagram;
Fig. 7 isEmbodiment of the invention Adelson-Velskii-Landis tree LR type rotation synoptic diagram;
Fig. 8 isEmbodiment of the invention Adelson-Velskii-Landis tree RL type rotation synoptic diagram;
Fig. 9 isEmbodiment of the invention Adelson-Velskii-Landis tree postorder storage node composition;
Figure 10 isEmbodiment of the invention Adelson-Velskii-Landis tree preorder storage node composition.
Embodiment
Below in conjunction with accompanying drawing and instance the present invention being further described, is example with inorder traversal.
The present invention is applied to the data storage of the big data quantity of the Internet of Things communications field and method for quickly querying.For example; To 50000 people in the place, terminal in the Internet of Things (nodal point number N=50000); Wherein IC-card number (1 byte), name (10 byte), personnel number (2 byte), work attendance information (2 byte), and bulletin of assisting to investigate information (200 byte) and other carry out unified management for information about; Terminal ram space resource is 8M, can use for the inquiry of data message and swipe the card and manually dual mode inquiry.
Be directed to above demand, realize, adopt Adelson-Velskii-Landis tree as node class index with the present invention; Preserve left pointer (4 byte) in the Adelson-Velskii-Landis tree successively, IC-card number (1 byte), node information is preserved address (2 byte); Right pointer (4 byte) needs 11 * 50000 ≈ 530Kb altogether.
(1) at first build the root node of an Adelson-Velskii-Landis tree, with reference to accompanying drawing 1, making up a complexity is log
2The balanced binary tree of N (N is a nodal point number) calls and creates node (AVLTreeCreate) function, increases the node of Adelson-Velskii-Landis tree.Each node is represented a people C
1,C
2,C
3,C
4C
N, each node comprises one type of refinement information D again
1,D
2,D
3,D
4D
N(comprising personal information, work attendance information etc.), the refinement information in the node is used different data structure storage according to the language of realizing is different, is convenient to data information memory and searches.
(2) in Adelson-Velskii-Landis tree, deposit data message then in, can adopt the rule of inorder traversal in node, to insert data message for Adelson-Velskii-Landis tree here with reference to accompanying drawing 2, its algorithm complex be log
2N, its storage node number are that key word Key distinguishes with IC-card, can be divided into C Plus Plus and realizing and the realization of C language.
1. C Plus Plus is realized: when the people swipes the card or manually imports card number, preserve card number information, at first whether decision tree is empty; If then carry out the newly-built node class of AVLTreeCreate function; If not; Then travel through Adelson-Velskii-Landis tree, judge whether it belongs to storage node, if; Then carry out and insert (AVLTreeInsert) function; Read the node data message in the file and be loaded in the buffer memory, carry out being saved in file (AVLTreeSaveToFile) function then, with data according to the form of storage node (as charge time, on call time and date etc.) be saved among the VECTOR of corresponding node information class in the file; If not, then carry out the AVLTreeCreate function, be its newly-built node, the data message with required preservation is saved in the newly-built node class again.
2. the C language is realized: realize it being to utilize the structure variable to remove to make up a structure based on the C language; To be defined as a structure TPvector to the operation of data message, the member variable of structure is the operation to data, as (inserting Insert; Deletion Delete; Search Search, after turn over PushBack, the preceding PushFront that turns over).When the people swipes the card or manually imports card number, preserve card number information, at first whether decision tree is empty; If then call the newly-built node of AVLTreeCreate function; If not; Then travel through Adelson-Velskii-Landis tree, judge whether it belongs to storage node, if; Then carry out the AVLTreeInsert function; Read the node data message in the file and be loaded in the buffer memory, carry out the AVLTreeSaveToFile function then, with data according to the form of storage node class (as charge time, on call time and date etc.) be saved in the file of corresponding node; If not, then carry out the AVLTreeCreate function, be its newly-built node, the data message with required preservation is saved in the newly-built node again.
(3) information in the inquiry Adelson-Velskii-Landis tree can be with reference to accompanying drawing 3, preface sequential access in the foundation of the inquiry of Adelson-Velskii-Landis tree here, time complexity log
2N also can be divided into C Plus Plus according to the preservation implementation of node and to realize and the realization of C language.
1. C Plus Plus is realized: when the people swipes the card or manually imports card number, preserve card number information, and call through the upper strata and to search (AVLTreeSearch) function, judge at first whether Adelson-Velskii-Landis tree is empty; If then redirect finishes to return tree for empty, if not; Then by the inorder traversal Adelson-Velskii-Landis tree, the card number of preserving and the visit node key word (key) of balanced binary tree are compared, judge whether to be storage node; If, then read fileinfo and be loaded in the buffer memory, according to the mode of inquiry (as number searching by input; Search current last, search when front and back one, search the information that needs deletion etc.) utilize dichotomy to continue the information in the inquiry node; If find needed Query Information, Query Result returned through return function keep supplying layer and call; Do not find information needed if inquired about all records, then the tax of no datat record is kept supplying layer to return function and call; If not, then will not have these node data compose to return function keep supplying the layer call.
2. the C language is realized: define a structure TPVector, the member variable of structure is the operation to data, like (insert Insert, deletion Delete inquires about Search, then turn over PushBack, the preceding PushFront that turns over).When the people swipes the card or manually imports card number, preserve card number information, and call structure search member object TPVector.AVLTreeSearch, call and search (AVLTreeSearch) function, judge at first whether Adelson-Velskii-Landis tree is empty; If then redirect finishes to return tree for empty; If not, then travel through Adelson-Velskii-Landis tree, judge that whether it be storage node; If, then read fileinfo and be loaded in the buffer memory, according to the mode of inquiry (as number searching by input; PushFront, PushBack, Delete etc.) utilize dichotomy to continue the information in the inquiry node; If find needed information, Query Result returned through return function keep supplying layer and call; Do not find information needed if inquired about all records, then the tax of no datat record is kept supplying layer to return function and call; If not, then will not have these node data compose to return function keep supplying the layer call.
(4) information in the deletion Adelson-Velskii-Landis tree can be with reference to accompanying drawing 4, and the data message of at first preserving the mode (AVLTreeDeleteStyle) of deletion during deletion and needing to delete judges then whether Adelson-Velskii-Landis tree is empty; If then directly redirect finishes to return tree for empty, then travels through Adelson-Velskii-Landis tree if not, specifically divides following two kinds of situation:
1. when the AVLTreeDeleteStyle value is the deletion node; Then directly travel through Adelson-Velskii-Landis tree; Find the node
of required deletion; The direct whole node of deletion, and will delete the result and compose and keep supplying layer to return function and call, the tree structure that the equilibrating function is adjusted Adelson-Velskii-Landis tree called simultaneously.
2. when the AVLTreeDeleteStyle value for the deletion node in during data, then at first travel through Adelson-Velskii-Landis tree, judge whether it is with storage node; If not, then redirect finishes to return the no datat record; If, then call the LoadAVLTreeNode function and continue to search the information in the node, if find, the information that finds of deletion then, and will delete the result and compose to keep supplying to return function and layer call; If inquire about all records and do not find information needed, then will not have this and write down the result and compose to keep supplying and layer call to return function.
(5) adjustment Adelson-Velskii-Landis tree.The insertion of Adelson-Velskii-Landis tree and deletion action all can exert an influence to tree structure, cause balance factor bf (balance factor) greater than 1 or less than-1, in order to keep the minimum log of being of time complexity to tree
2N need carry out the equilibrating adjustment to tree, can divide following four kinds of situation to tree-like adjustment:
1. the L type of balanced binary tree rotation; When Adelson-Velskii-Landis tree inserts (inserting node in the left child's of minimum subtree root node left subtree) or deletion action (node of deletion is the right child of minimum subtree root node and is leaf node); And the bf that satisfies minimum subtree then need carry out the L type and rotate the structure of regulating Adelson-Velskii-Landis tree greater than 1 o'clock.
With reference to Fig. 5, when inserting C
NThe time, cause the bf of the root node A of minimum subtree to become 2, then need carry out L rotation adjustment, at first with B
RLifting is the root node of new subtree, and A drops to B
RRight child, simultaneously with B
LRotate to be B
RLeft child, B drops to B
LRight child; As deletion node A
RThe time, cause the bf of the root node A of minimum subtree to become 2, then need carry out L rotation adjustment, with B
RPromoting is minimum subtree root node, and A rotates to be B
RRight child, B rotates to be B
RLeft child.
2. the R type of balanced binary tree rotation; When Adelson-Velskii-Landis tree inserts (inserting node in the right child's of minimum subtree root node right subtree) or deletion action (node of deletion is the left child of minimum subtree root node and is leaf node); And the bf that satisfies minimum subtree root node need carry out R type rotation adjustment less than-1 o'clock.
With reference to Fig. 6, when inserting C
NThe time, cause the bf of the root node A of minimum subtree to become-2, then need carry out R rotation adjustment; At first promote the root node that B is minimum subtree, A drops to the left child of B, with B
LRotate to be the right child of A; As deletion A
LThe time, cause the bf of the root node A of minimum subtree to become-2, then need carry out the R rotation, at first promote the root node that B is minimum subtree, B
LRotate to be the left child of B, A rotates to be B
LLeft child.
3. the LR type of balanced binary tree rotation; When balanced binary tree inserts (inserting node in the right child's of minimum subtree root node left subtree); Satisfy simultaneously minimum subtree root node bf less than-1 and its left child bf greater than 1 o'clock, then need carry out the LR type and rotate the structure of regulating Adelson-Velskii-Landis tree.
With reference to Fig. 7, when inserting C
NThe time cause the bf of the root node A of minimum subtree become-2 and the bf of its left child B become 2, then need carry out LR rotation adjustment, at first carry out the L rotation, with C
LPromote and be the root node of right subtree, C
RRotate to be C
LRight child, C rotates to be C
RLeft child, B rotates to be C
RRight child; Carry out the R rotation this moment, promoting C is the root node of minimum subtree, and A is left child and the C of C
LRotate to be the right child of A, B rotates to be the right child of C, C
RRotate to be the left child of B.
4. the RL type of balanced binary tree rotation, when balanced binary tree inserts (inserting node in the left child's of minimum subtree root node right subtree), the bf that satisfies minimum subtree root node simultaneously greater than 1 and its right child bf less than-1 o'clock; Then need carry out the LR type and rotate the structure of regulating Adelson-Velskii-Landis tree.
With reference to Fig. 8, when inserting C
NThe time cause the bf of the root node A of minimum subtree become 2 and the bf of its left child B become-2, then need carry out RL rotation adjustment, at first carry out the R rotation, C promoted be the root node of left subtree, B drops to the left child of C, with C
LRotate to be the right child of B; Carry out the L rotation this moment, the C lifting is the root node of minimum subtree, A drops to the right child of C, with C
RRotate to be the left child of A.
(6) traversal of Adelson-Velskii-Landis tree under the actual conditions is 50000 Adelson-Velskii-Landis tree for continuous and full nodal point number, its total L=log
250000<log
265536=16 level node, CL are current progression, D
CLFor the layer of current progression node apart from poor; The traversal formula of all nodes is so: root node Pr=2
L-1, the father node of current node is P
F, its left child P
L=P
F-D
CL, its right child P
R=P
F+ D
CL, D
CL=2
L-CL-1, CL ∈ [1, L).
When needs are sought the node sequence number and are 20000, i.e. n
=20000, then by 2
14<20000<2
15=32768 can know, destination node is searched P for the first time in the left subtree of root node
L=32768-2
14=16384, P
R=32768+2
14=49152; Obviously destination node is searched P for the second time in its left subtree
L=16384-2
13=8192, P
R=16384+2
13=24576; Obviously destination node is searched P for the third time in its right subtree
L=24576-2
12=20480, P
R=24576+2
12=28672; Then carry out the 4th time and search P
L=20480-2
11=18332, P
R=20480+2
11=22528; Carry out P the 5th time
L=18332-2
10=17284, P
R=18332+2
10=19880; Carry out P the 6th time
L=19880-2
9=19368, P
R=19880+2
9=20392; Carry out P the 7th time
L=20392-2
8=20136, P
R=20392+2
8=20648; Carry out P the 8th time
L=20136-2
7=20008, P
R=20136+2
7=20264; Carry out P the 9th time
L=20008-2
6=19944, P
R=20008+2
6=20072; Carry out P the tenth time
L=19944-2
5=19912, P
R=19944+2
5=19976; Carry out the tenth once, P
L=19976-2
4=19960, P
R=19976+2
4=19992; Carry out the tenth secondary, P
L=19992-2
3=19984, P
R=19992+2
3=20000; Find needed destination node this moment.
The present invention has announced a kind of data storage based on sort feature and balanced binary tree, querying method, and above-mentioned instance has provided the entire method process based on inorder traversal, and the method based on preorder and postorder traversal of providing below is respectively like Fig. 9 and Figure 10.
The storage node composition that is based on the preorder traversal Adelson-Velskii-Landis tree that Fig. 9 announces; Be with inorder traversal storage organization difference; When data message is stored and inquired about, be to travel through according to the order about root, the traversal formula of all nodes is so: root node Pr=1, the father node of current node are P
F, its left child P
L=P
F+ 1, its right child P
R=P
F+ D
CL, D
CL=2
L-CL, CL ∈ [1, L).
The storage node composition that is based on the postorder traversal Adelson-Velskii-Landis tree that Figure 10 announces, its according to about the traversal order storage and the inquiry Adelson-Velskii-Landis tree of root, different with the middle preface traversal formula of its node that are with preorder are: root node Pr=2
L-1, the father node of current node is P
F, its left child P
L=P
F-D
CL, its right child P
R=P
F-1, D
CL=2
L-CL, CL ∈ [1, L).
In the above-mentioned instance, memory source is under the situation of 8M, and requiring nodal point number N is 50000, and using its height H of setting up binary tree of Adelson-Velskii-Landis tree so is log
250000<log
265536=16, i.e. height of tree h=16, the time complexity of search tree also is 16 so, finds any one node so and need visit internal memory at most 16 times.For 10000000 data recording of 50000 nodes, on average each node is 200, again these 200 recorded informations is carried out binary search, and algorithm complex also is O (log
2200) ﹤ 8, just maximum can confirm for 8 times the data that will search.
The orderly Adelson-Velskii-Landis tree structure of the method utilization is stored data message and inquire about by sort feature, makes that the time complexity of Adelson-Velskii-Landis tree of its storage node class is O (log
2N), search the specifying information employing simultaneously and utilize dichotomy to accomplish to buffer area data load, its time complexity also is O (log
2N), its algorithm complex of more current querying method commonly used is minimum, has improved search efficiency greatly, saves query time, has reduced the internal storage access number of times, has reduced energy consumption.Utilize the storage mode of binary tree index simultaneously, saved the memory headroom (8b * N, N nodal point number) of storage binary tree front and back pointers, realize inserting dynamically, distributed resource space flexibly, improved memory usage.
Claims (9)
1. the data storage based on sort feature and balanced binary tree, querying method is characterized in that, may further comprise the steps:
1.1 the structure balanced binary tree is created node;
1.2, dynamically data information memory is arrived corresponding node according to the rule of traversal;
1.3 input needs information inquiring, dynamically travels through balanced binary tree, returns and searches failure up to finding required data message or having traveled through balanced binary tree.
2. the data storage based on sort feature and balanced binary tree according to claim 1, querying method; It is characterized in that; Said balanced binary tree is orderly, can dynamically data information memory be arrived corresponding node according to the traversal rule of middle preface, preorder or postorder.
3. the data storage based on sort feature and balanced binary tree according to claim 1, querying method; It is characterized in that; Said step 1.1, realize as follows: at first the node number of achievement rule structure according to balanced binary tree is n, and the height of tree is log
2The balanced binary tree of n increases node then, and each node is represented a feature class C
1, C
2, C
3, C
4C
N, each node comprises the information of one type of refinement.
4. the data storage based on sort feature and balanced binary tree according to claim 1, querying method is characterized in that, nodal point number is the stored in form of C language or C Plus Plus according to this.
5. the data storage based on sort feature and balanced binary tree according to claim 1, querying method; It is characterized in that; Said step 1.2 to the insertion of data message, can be carried out the insertion of data message according to the traversal rule of middle preface, preorder or postorder to node; Adjust the tree structure of balanced binary tree simultaneously, can be divided into and utilize the realization of C Plus Plus form and utilize the C linguistic form to realize:
1. the C Plus Plus form realizes: the VECTOR class when data message need be stored, at first judges whether balanced binary tree is empty as data store organisation in the node in the employing C Plus Plus; If a then newly-built root node also is saved in root node with data message and returns simultaneously and preserve successfully; If not, then travel through balanced binary tree, judge whether it belongs to storage node; If then according to the rule of canned data, the information that needs are preserved is saved in corresponding node, and returns and preserve successfully; If not, then execution in step 1.1, and the data message with required preservation is saved in the newly-built node again, at last by return function with saving result return keep supplying the layer call;
2. the C language is realized: utilize the structure variable to make up a structure struct; All nodes adopt the storage organization of doubly linked list; To be defined as the member variable of structure to all operations of node, when data message need be preserved, judge at first whether balanced binary tree is empty; If a then newly-built root node also is saved in root node with data message and returns simultaneously and preserve successfully; If not, then travel through balanced binary tree, judge whether to be storage node class; If then call corresponding preservation of preservation member object execution of structure and operate and return and preserve successfully; If not, then execution in step 1.1, and the data message with required preservation is saved in the newly-built node class again, at last by return function with saving result return keep supplying the layer call.
6. according to any one described data storage, querying method in the claim 1 to 5 based on sort feature and balanced binary tree; It is characterized in that; The inquiry of node data message in the said step 1.3; Through the data message in the node is read in the buffer zone, utilize binary search, can be divided into and utilize the realization of C Plus Plus form and utilize the C linguistic form to realize:
1. C Plus Plus is realized: when input inquiry information, judge at first whether balanced binary tree is empty; If then directly return tree for empty; If not, then travel through balanced binary tree, judge whether to be storage node; If then continue the visit node information, and node information be loaded into buffer memory. the district, utilize dichotomy to search, and Query Result kept supplying layer to return function call; If not, then return no node class and give return function;
2. the C language is realized: utilize the structure variable to remove to make up a structure struct, all nodes adopt the storage organization of doubly linked list, will be defined as the member object of structure to all operations of node; When needs data query information, judge at first whether balanced binary tree is empty; If then directly return tree for empty; If not, then travel through balanced binary tree, judge whether to be storage node; If, then call the query manipulation member object of structure and carry out corresponding query manipulation, continue the refinement information in the visit node class, up to inquiring required result or inquire about all recorded informations, and Query Result composed to keep supplying to return function layer call; If not, then return no node class to return function keep supplying the layer call.
7. the data storage based on sort feature and balanced binary tree according to claim 6, querying method, its characteristic are that also the deletion action of balanced binary tree can be divided into two types, deletion node and the data of deleting in the node; At first preserve the mode and the data message that needs deletion of deletion during deletion, call the AVLTreeDeleteStyle function that obtains the deletion mode then, specifically divide following two kinds of situation:
1. work as the AVLTreeDeleteStyle value and be deletion node C
iThe time, then directly travel through balanced binary tree, inquire about the node C of required deletion
i,, then return and do not have this node deletion failure if having traveled through all nodes does not find; If find direct deletion node C
i, and return and delete successfully; To delete at last the result compose to return function keep supplying the layer call, adjust the tree structure of balanced binary tree simultaneously;
2. work as the AVLTreeDeleteStyle value and be deletion node C
iIn data the time, then at first travel through balanced binary tree, inquiry node C
i, traveled through all nodes and do not found then to return and do not have this node information deletion failure; If find the node C of required deletion
i, then continue to search the information in the node, up to finding required deleted data, with its deletion and return and delete successfully; Perhaps inquire about all records and do not found information needed, returned the failure of no datat record deletion; To delete at last the result compose to return function keep supplying the layer call.
8. according to claim 6 or 7 described data storage, querying method, it is characterized in that, balanced binary tree carried out the equilibrating adjustment, be divided into following four kinds of situation based on sort feature and balanced binary tree:
1. the L type of balanced binary tree rotation; When balanced binary tree inserts and insert node in the left child's of minimum subtree root node left subtree; Perhaps the node of deletion action and deletion is the right child of minimum subtree root node and when the leaf node; And the balance factor bf that satisfies minimum subtree then need carry out the structure that the L type rotates the adjustment binary tree greater than 1 o'clock;
2. the R type of balanced binary tree rotation; When balanced binary tree inserts and insert node in the right child's of minimum subtree root node right subtree; Perhaps the node of deletion action and deletion is the left child of minimum subtree root node and when the leaf node; And the balance factor bf that satisfies minimum subtree root node need carry out the structure that the R type rotates the adjustment binary tree less than-1 o'clock;
3. the LR type of balanced binary tree rotation; When balanced binary tree inserts and insert node in the right child's of minimum subtree root node left subtree the time; The balance factor bf that satisfies minimum subtree root node simultaneously less than-1 and its left child's balance factor bf greater than 1 o'clock, then need carry out the structure that the LR type rotates the adjustment binary tree;
4. the RL type of balanced binary tree rotation; When balanced binary tree inserts and inserts node in the left child's of minimum subtree root node right subtree the time, the balance factor bf that satisfies minimum subtree root node simultaneously greater than 1 and its right child's balance factor bf less than-1 o'clock; Then need carry out the structure that the RL type rotates the adjustment binary tree.
9. the data storage based on sort feature and balanced binary tree according to claim 8, querying method, its characteristic are that also continuous and full nodal point number is the balanced binary tree of n, its total L=log
2N level node, CL are current progression, D
CLFor the layer of current progression node apart from poor, layer is apart from difference poor for the nodal value between the adjacent tree layer; The inorder traversal formula of all nodes is so: root node Pr=2
L-1, the father node of current node is P
F, its left child P
L=P
F-D
CL, its right child P
R=P
F+ D
CL, D
CL=2
L-CL-1, CL ∈ [1, L); The preorder traversal formula is: Pr=1, P
L=P
F+ 1, P
R=P
F+ D
CL, D
CL=2
L-CL, CL ∈ [1, L); The postorder traversal formula is: Pr=2
L-1, P
L=P
F-D
CL, P
R=P
F-1, D
CL=2
L-CL, CL ∈ [1, L).
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