CN102402602A - B+ tree indexing method and device of real-time database - Google Patents
B+ tree indexing method and device of real-time database Download PDFInfo
- Publication number
- CN102402602A CN102402602A CN2011103675946A CN201110367594A CN102402602A CN 102402602 A CN102402602 A CN 102402602A CN 2011103675946 A CN2011103675946 A CN 2011103675946A CN 201110367594 A CN201110367594 A CN 201110367594A CN 102402602 A CN102402602 A CN 102402602A
- Authority
- CN
- China
- Prior art keywords
- node
- key word
- record
- tree
- leaf node
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Abstract
The invention is suitable for the data processing field, providing a B+ tree indexing method and device of real-time database, wherein the method includes the steps of: obtaining the number of the nodes according to the table or the recorded number in the real-time database, wherein the node includes a node domain and a control domain; dividing a corresponding memory space for storing the node domain and the control domain of each node according to the memory space for each node; storing the table or the recorded keyword to the node domain of the node, storing the pointer information to the control domain of the node and generating each node and B+ tree index. The invention provides an effective and stable indexing method, which increases the stability of the real-time database and the performance of the real-time database so that the user can rapidly visit the real-time database.
Description
Technical field
The invention belongs to data processing field, relate in particular to a kind of B+ tree indexing means and device of real-time data base.
Background technology
Along with the continuous expansion of data volume now, the data in the database are on the increase, when using, require database have initiatively, in real time, characteristic such as timeliness.Wherein, index is to improve a kind of effective tool that Database Systems are carried out efficient.Because the index of real-time data base receives the quick access of internal memory and the influence of high effective rate of utilization; Therefore the index structure that is applicable to real-time data base roughly can be divided into two big types: one type is the index structure that data keep certain natural ordering, like various data structures; Another kind of is the index structure of data stochastic distribution, like various Hash structures.
The tradition index structure mainly contains following three kinds, below will describe in detail.
The first, adopt the array structure that indexes.
Its concrete grammar is: the size through knowing data in advance perhaps makes the appropriate growth of data through the virtual store mapping techniques, and the space that array indexing is used is minimum.Yet the array indexing structure can not Dynamic Maintenance, and the caused data amount of movement of each attended operation is O (n) level (n is the array element number), makes maintenance cost too high.And array indexing structure practicality is not strong.
The second, structure indexes to adopt Adelson-Velskii-Landis tree (a kind of self-equilibrating binary search tree).
Because the time complexity of Adelson-Velskii-Landis tree operation is less,, therefore has higher access performance for O (Log2N) (N is the record number).But because its each node has only a data elements, two pointers and relevant pointer information are arranged but, cause the effective rate of utilization of its internal memory very low.
The 3rd, structure indexes to adopt B tree (a kind of data structure).
The B tree is a kind of balanced tree of dynamic adjustments; B tree the operation cost is
wherein; K is the rank (order) of B tree; N is the record number, and C is a very little integer.Yet; When setting B as index structure; Because key word is distributed in the whole B tree; And the key word that in interior node (node beyond the leaf node), occurred no longer appears in the leaf node, makes that daisy chaining can not be with all keywords links in the tree together, and this needing to be unfavorable for the operation of sequential search or ordering.Secondly, in the B tree, deletion action is more loaded down with trivial details.Therefore, B tree can't be satisfied real-time data base and carried out efficient efficiently.
Summary of the invention
The purpose of the embodiment of the invention is to provide a kind of B+ tree indexing means and device of real-time data base, and it is not high to be intended to solve the existing index structure efficient that is used for real-time data base, the problem that practicality is not strong.
The embodiment of the invention is achieved in that a kind of B+ tree indexing means of real-time data base, and said method comprises:
Number according to table in the real-time data base or record obtains the node number, and said node comprises nodes domains and control domain;
According to the required memory headroom that takies of each node, divide nodes domains and control domain that corresponding memory headroom is used to store each node;
The key word of table or record is stored to the nodes domains of node, pointer information is stored to the control domain of node, generate each node and B+ tree index with this.
Another purpose of the embodiment of the invention has been to provide a kind of B+ tree indexing unit of real-time data base, and said device comprises:
Node number acquiring unit is used for the number according to real-time data base table or record, obtains the node number, and said node comprises nodes domains and control domain;
Memory partitioning unit is used for according to the required memory headroom that takies of each node, divides nodes domains and control domain that corresponding memory headroom is used to store each node;
The index generation unit is used for the key word of table or record is stored to the nodes domains of node, and pointer information is stored to the control domain of node, generates each node and B+ tree index with this.
In embodiments of the present invention, set the index of realizing real-time data base, a kind of both efficient, stable again indexing means is provided through B+.Both improve the stability of real-time data base, improved the performance of real-time data base again, and made the user can visit real-time data base more quickly.
Description of drawings
Fig. 1 is the B+ tree indexing means process flow diagram of the real-time data base that provides of the embodiment of the invention one;
Fig. 2 is the instance according to B+ tree index search key word that the embodiment of the invention two provides;
Fig. 3 is a kind of instance according to B+ tree index insertion key word that the embodiment of the invention three provides;
Fig. 4 is a kind of instance according to B+ tree index insertion key word that the embodiment of the invention three provides;
Fig. 5 is a kind of instance according to B+ tree index deletion key word that the embodiment of the invention four provides;
Fig. 6 is a kind of instance according to B+ tree index deletion key word that the embodiment of the invention four provides;
Fig. 7 is the B+ tree indexing unit structural representation of the real-time data base that provides of the embodiment of the invention five.
Embodiment
In order to make the object of the invention, technical scheme and advantage clearer,, the present invention is further elaborated below in conjunction with accompanying drawing and embodiment.Should be appreciated that specific embodiment described herein only in order to explanation the present invention, and be not used in qualification the present invention.
The embodiment of the invention provides B+ tree (a kind of data structure) indexing means of a kind of real-time data base, after the nodes domains through defining the B+ tree again and the data structure of control domain, creates the B+ tree, utilizes the B+ tree to set up the index of real-time data base.
The invention provides a kind of B+ tree indexing means and device of real-time data base:
Said method comprises:
Number according to table in the real-time data base or record obtains the node number, and said node comprises nodes domains and control domain;
According to the required memory headroom that takies of each node, divide nodes domains and control domain that corresponding memory headroom is used to store each node;
The key word of table or record is stored to the nodes domains of node, pointer information is stored to the control domain of node, generate each node and B+ tree index with this.
Said device comprises:
Node number acquiring unit is used for the number according to real-time data base table or record, obtains the node number, and said node comprises nodes domains and control domain;
Memory partitioning unit is used for according to the required memory headroom that takies of each node, divides nodes domains and control domain that corresponding memory headroom is used to store each node;
The index generation unit is used for the key word of table or record is stored to the nodes domains of node, and pointer information is stored to the control domain of node, generates each node and B+ tree index with this.
For technical scheme of the present invention is described, describe through specific embodiment below.
Embodiment one:
Be illustrated in figure 1 as the process flow diagram of the B+ tree indexing means of real-time data base provided by the invention,, only show the part relevant with the embodiment of the invention for the ease of explanation.
In step S101, the number according to table in the real-time data base or record obtains the node number, and said node comprises nodes domains and control domain.
In embodiments of the present invention, because index both can be the index of showing in the real-time data base, also can be the index of each bar record in the real-time data base.In B+ tree, represent the record in a table or the database with a node, the number of therefore showing or the bar number of record are identical with the node number.If create the index of table, then obtain the number of node according to the number of table; If create the index of record, then obtain the number of node according to the number of record.
In embodiments of the present invention, node comprises nodes domains and control domain.Wherein, nodes domains is used for memory node information, is the key word of table or record here; Control domain is used to store pointer information, and the pointer information here includes but not limited to: point to the pointer of other nodes and point to the corresponding table of key word or the pointer of record.
In step S102,, divide nodes domains and control domain that corresponding memory headroom is used to store each node according to the required memory headroom that takies of each node.
In embodiments of the present invention, because each size of node is different, the memory headroom size that takies is just different.After calculating the shared memory headroom of each node, divide nodes domains and control domain that corresponding memory headroom is used to store each node.As: the nodes domains that memory address 0X00 is used to store first node to the memory headroom of 0X11.
In step S103, the key word of table or record is stored to the nodes domains of node, pointer information is stored to the control domain of node, generate each node and B+ tree index with this.
In embodiments of the present invention; The key word of table or record is stored to the nodes domains of each node, and the key word that will show or write down is stored to pointer information (like pointer information) control domain of node as the key word of node; Initialization B+ tree generates each node and B+ tree index.
In embodiments of the present invention; The subtree number of each node is smaller or equal to the exponent number of B+ tree in the B+ tree that generates; The exponent number that the included subtree number of said each branch of B+ tree is set more than or equal to B+, except that leaf node, other nodes have two subtrees at least in the said B+ tree.In the B+ tree, the subtree number of each node is identical with the key word number of this node, and the number of the key word that leaf node comprises is more than or equal to 1/2nd of the subtree number.Leaf node is used for the key word of memory node and points to the corresponding table of this key word or the pointer of record; Or be used for the maximum key word of every blocks of data file behind the storing data files piecemeal and point to the corresponding table of this maximum key word or the pointer of record; The size order that leaf node according to keywords is worth links, and all leaf nodes are all at one deck.All branch nodes comprise maximum key word of the child node intermediate value of this branch node or value minimum key word cut off value and point to the pointer of this cut off value.In Fig. 2, the first left node comprises key word F and J in the second layer, and F and the J cut off value of the minimum key word of the child node intermediate value of this node just.Wherein, node comprises root node, branch node and leaf node, is the general name of root node, branch node and leaf node.The node that is positioned at the treetop end is a root node; Be positioned at B+ tree lowermost end, do not have the node of child node to be called leaf node; Node except leaf node and root node is called branch node.Remove in addition, also available parent node and child node are explained internodal relation, link to each other with node, and the node that is positioned at this node last layer is called the parent node of this node; And link to each other with this node, the node that is positioned at one deck under this node is called the child node of this node.
In embodiments of the present invention, set the index of realizing real-time data base, a kind of both efficient, stable again indexing means is provided through B+.Both improve the stability of real-time data base, improved the performance of real-time data base again, and made the user can visit real-time data base more quickly.
Embodiment two:
Embodiment two is the method that the B+ that creates according to embodiment one provided by the invention sets the search index key word, for the ease of explanation, only shows the part relevant with the embodiment of the invention.
In embodiments of the present invention, the table of desired seek or the key word of record are successively compared with all key words of each node in the B+ tree, up in leaf node, finding and the table of said desired seek or the identical key word of key word of record.
Lifting a concrete instance below specifies.
If the B+ that is set up tree is as shown in Figure 2, wherein, the key word of table or record representes that with English alphabet the size order that leaf node according to keywords is worth links.Need be in this B+ tree search key G.Then concrete lookup method is following:
At first, key word G is compared with key word P in the root node, draw G,, skip to the node that has comprised key word F and J in the second layer therefore according to the pointer in the root node less than P.At this moment, key word G again with key word F and J relatively, draw G greater than F less than J after, get into the 3rd layer node again along pointer, in the 3rd layer node, inquire key word G.And in the leaf node that comprises key word G, find one to point to the corresponding table of key word G or the pointer of record.
In embodiments of the present invention; Owing to having only leaf node to be used for the key word of memory node and pointing to the corresponding table of this key word or the pointer of record; Therefore when in the B+ tree, inquiring about,, do not stop inquiry if not the key word that leaf node comprises equals the key word that need search.But continue to search downwards, up to finding the leaf node that comprises the key word that need search.
Embodiment three:
Embodiment three is the method that the B+ tree index of creating according to embodiment one provided by the invention inserts key word, for the ease of explanation, only shows the part relevant with the embodiment of the invention.
In embodiments of the present invention, because the size order that leaf node according to keywords is worth links, the keyword root that then will insert inserts in the corresponding leaf node according to the size of its value.Wherein, have note at following 2:
One of which is if after needing the corresponding leaf node of key word of insertion to add the key word that needs to insert, the number of the key word that it comprised is then directly inserted this key word in the corresponding leaf node smaller or equal to this leaf node exponent number.
Its two, if after the corresponding leaf node of the key word that need to insert added the key word that needs to insert, the number of the key word that it comprised then need divide this leaf node greater than this leaf node exponent number.Concrete splitting method is:
The corresponding leaf node of key word that need are inserted is split into two nodes, and the number of these two key words that node comprised is respectively: (m+1)/2 round the integer of back gained downwards, the integer of the back gained that (m+1)/2 rounds up.Wherein, m is the node exponent number.At this moment, whether the parent node of judging this leaf node again satisfies key word number that this parent node comprises smaller or equal to this parent node exponent number, if satisfy, finishes to insert flow process; If do not satisfy, then continue to divide as stated above this parent node, all satisfy key word number that node comprises smaller or equal to this node exponent number up to all nodes.
Following comparison diagram 3 and Fig. 4 explain the process of inserting key word E.If according to shown in Figure 3, directly E is inserted the first left leaf node, then cause key word number that the discontented podomere point of this leaf node comprises smaller or equal to this node exponent number, cause mistake.Therefore; Will be according to method shown in Figure 4; The leaf node at division E place makes E place leaf node be divided into two nodes, and one comprises key word A and B; Another comprises key word C, D and E, makes these two leaf nodes all satisfy key word number that node comprises smaller or equal to this node exponent number.
Embodiment four:
Embodiment four is the method that key word deleted in the B+ tree index of creating according to embodiment one provided by the invention, for the ease of explanation, only shows the part relevant with the embodiment of the invention.
In embodiments of the present invention, at first find the node at the key word place that needs deletion, then with this key word deletion.
Two kinds of situation are specifically arranged:
One of which behind the node that the key word that inquiring needs deletion belongs to, reaches the table corresponding with pointing to this key word or the pointer of record if the key word number in this node, is then directly deleted this key word greater than 1/2nd of this node exponent number.
They are two years old; After inquiring the node at the key word place that needs deletion; If the key word number in this node equals 1/2nd of this node exponent number; Then from the brotgher of node of this node, move one or more key words in this node, make key word number contained in this node and its brotgher of node basic identical.
Be specially; If the key word number in this node equals 1/2nd of this node exponent number; Behind the deletion key word, possibly cause key word number in this node less than 1/2nd of this node exponent number, therefore; Need this moment from the brotgher of node of this node, to move one or more key words in this node, make key word number contained in this node and its brotgher of node basic identical.Yet,, can not move the key word in this brotgher of node, but a node merged in a key word in this node and its brotgher of node or the parent node if the key word number that this brotgher of node comprised equals 1/2nd of node exponent number.
The process of deletion key word G is described through Fig. 5 and Fig. 6 below.As shown in Figure 5, at first from the leaf node that comprises key point G, delete key point G.Yet because the original both keyword of G place node (promptly before deletion key word G), the number of this node key word equals 1/2nd of node exponent number.Therefore, behind deletion key word G, must the one or more key words in the brotgher of node of this node be added in this node.But because the key word number that its brotgher of node comprised also equals 1/2nd of node exponent number, therefore, merge this node and its brotgher of node, soon key word F, J, K are combined in the node (as shown in Figure 6).At this moment, because behind the synthetic node, key word J has not been the cut off value of the minimum key word of the child node intermediate value of this parent node in the parent node of the node after this is synthetic, therefore also needs deletion key word J from this parent node.
Embodiment five:
Fig. 7 for the ease of explanation, only shows the part relevant with the embodiment of the invention for the B+ of the real-time data base that the embodiment of the invention provides sets the indexing unit structural representation.This device can be to be built in the unit that software unit, hardware cell or the software and hardware of electronic equipment such as computer combine, and perhaps is integrated in the application system of these electronic equipments or electronics as suspension member independently.Wherein:
Node number acquiring unit 71 is used for the number according to real-time data base table or record, obtains the node number, and said node comprises nodes domains and control domain.
In embodiments of the present invention; The subtree number of each node is smaller or equal to the exponent number of B+ tree in the B+ tree that generates; The exponent number that the included subtree number of said each branch of B+ tree is set more than or equal to B+, except that leaf node, other nodes have two subtrees at least in the said B+ tree.In the B+ tree, the subtree number of each node is identical with the key word number of this node, and the number of the key word that leaf node comprises is more than or equal to 1/2nd of said subtree number.Leaf node is used for the key word of memory node and points to the corresponding table of this key word or the pointer of record; Or be used for the maximum key word of every blocks of data file behind the storing data files piecemeal and point to the corresponding table of this maximum key word or the pointer of record; The size order that leaf node according to keywords is worth links, and all leaf nodes are all at one deck.All branch nodes comprise maximum key word of the child node intermediate value of this branch node or value minimum key word cut off value and point to the pointer of this cut off value.
Preferably, the B+ of said real-time data base tree indexing unit also comprises:
Query unit is used for the table of desired seek or the key word of record are successively compared with all key words of each node of B+ tree, up in leaf node, finding and the table of said desired seek or the identical key word of key word of record.
Insert the unit, the keyword root that is used for need are inserted inserts corresponding leaf node according to the size of its value; If after needing the corresponding leaf node of key word of insertion to add the key word that needs to insert, the number of the key word that is comprised is smaller or equal to this leaf node exponent number, the key word that then will insert directly inserts in the corresponding leaf node; If after needing the corresponding leaf node of key word of insertion to add the key word that needs to insert, the number of the key word that is comprised then divides this leaf node greater than this leaf node exponent number.
Delete cells behind the node that the key word that being used to inquire needs deletion belongs to, reaches the table corresponding with pointing to this key word or the pointer of record if the key word number in this node, is then directly deleted this key word greater than 1/2nd of this node exponent number; If the key word number in this node equals 1/2nd of this node exponent number, then from the brotgher of node of this node, move one or more key words in this node, make key word number contained in this node and its brotgher of node basic identical.
In embodiments of the present invention, set the index of realizing real-time data base, a kind of both efficient, stable again indexing means is provided through B+.Both improve the stability of real-time data base, improved the performance of real-time data base again, and made the user can visit real-time data base more quickly.
One of ordinary skill in the art will appreciate that; Realize that all or part of step in the foregoing description method is to instruct relevant hardware to accomplish through program; Described program can be in being stored in a computer read/write memory medium; Described storage medium is like ROM/RAM, disk, CD etc.
The above is merely preferred embodiment of the present invention, not in order to restriction the present invention, all any modifications of within spirit of the present invention and principle, being done, is equal to and replaces and improvement etc., all should be included within protection scope of the present invention.
Claims (10)
1. the B+ of a real-time data base sets indexing means, it is characterized in that said method comprises:
Number according to table in the real-time data base or record obtains the node number, and said node comprises nodes domains and control domain;
According to the required memory headroom that takies of each node, divide nodes domains and control domain that corresponding memory headroom is used to store each node;
The key word of table or record is stored to the nodes domains of node, pointer information is stored to the control domain of node, generate each node and B+ tree index with this.
2. the method for claim 1 is characterized in that, in said B+ tree, the subtree number of node is identical with the key word number of node, and the number of the key word that leaf node comprises is more than or equal to 1/2nd of said subtree number; Leaf node is used for storage key and points to the corresponding table of this key word or the pointer of record, and the size order that leaf node according to keywords is worth links; All branch nodes comprise maximum key word of the child node intermediate value of this branch node or value minimum key word cut off value and point to the pointer of this cut off value.
3. according to claim 1 or claim 2 method is characterized in that, utilizes the method for said B+ tree index search table or record to be:
The table of desired seek or the key word of record are successively compared with the key word of each node of B+ tree, up in leaf node, finding and the table of said desired seek or the identical key word of key word of record.
4. according to claim 1 or claim 2 method is characterized in that, utilizes the method for said B+ tree index insertion table or record to be:
The keyword root that need are inserted inserts in the corresponding leaf node according to the size of its value;
If after needing the corresponding leaf node of key word of insertion to add the key word that needs to insert, the number of the key word that is comprised is smaller or equal to this leaf node exponent number, the key word that then will insert directly inserts in the corresponding leaf node;
If after needing the corresponding leaf node of key word of insertion to add the key word that needs to insert, the number of the key word that is comprised then divides this leaf node greater than this leaf node exponent number.
5. according to claim 1 or claim 2 method is characterized in that, utilizes the method for said B+ tree index delete list or record to be:
After inquiring the node at the key word place that needs deletion,, the key word number in this node reaches the table corresponding or the pointer of record with pointing to this key word if, then directly deleting this key word greater than 1/2nd of this node exponent number;
After inquiring the node at the key word place that needs deletion; If the key word number in this node equals 1/2nd of this node exponent number; Then from the brotgher of node of this node, move one or more key words in this node, make key word number contained in this node and its brotgher of node basic identical.
6. the B+ of a real-time data base sets indexing unit, it is characterized in that said device comprises:
Node number acquiring unit is used for the number according to real-time data base table or record, obtains the node number, and said node comprises nodes domains and control domain;
Memory partitioning unit is used for according to the required memory headroom that takies of each node, divides nodes domains and control domain that corresponding memory headroom is used to store each node;
The index generation unit is used for the key word of table or record is stored to the nodes domains of node, and pointer information is stored to the control domain of node, generates each node and B+ tree index with this.
7. device as claimed in claim 6 is characterized in that, in said B+ tree, the subtree number of node is identical with the key word number of node, and the number of the key word that leaf node comprises is more than or equal to 1/2nd of said subtree number; Leaf node is used for storage key and points to the corresponding table of this key word or the pointer of record, and the size order that leaf node according to keywords is worth links; All branch nodes comprise maximum key word of the child node intermediate value of this branch node or value minimum key word cut off value and point to the pointer of this cut off value.
8. like claim 6 or 7 described devices, it is characterized in that said device also comprises:
Query unit is used for the table of desired seek or the key word of record are successively compared with the key word of each node of B+ tree, up in leaf node, finding and the table of said desired seek or the identical key word of key word of record.
9. like claim 6 or 7 described devices, it is characterized in that said device also comprises:
Insert the unit, the keyword root that is used for need are inserted inserts corresponding leaf node according to the size of its value; If after needing the corresponding leaf node of key word of insertion to add the key word that needs to insert, the number of the key word that is comprised is smaller or equal to this leaf node exponent number, the key word that then will insert directly inserts in the corresponding leaf node; If after needing the corresponding leaf node of key word of insertion to add the key word that needs to insert, the number of the key word that is comprised then divides this leaf node greater than this leaf node exponent number.
10. like claim 6 or 7 described devices, it is characterized in that said device also comprises:
Delete cells behind the node that the key word that being used to inquire needs deletion belongs to, reaches the table corresponding with pointing to this key word or the pointer of record if the key word number in this node, is then directly deleted this key word greater than 1/2nd of this node exponent number; After inquiring the node at the key word place that needs deletion; If the key word number in this node equals 1/2nd of this node exponent number; Then from the brotgher of node of this node, move one or more key words in this node, make key word number contained in this node and its brotgher of node basic identical.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN2011103675946A CN102402602A (en) | 2011-11-18 | 2011-11-18 | B+ tree indexing method and device of real-time database |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN2011103675946A CN102402602A (en) | 2011-11-18 | 2011-11-18 | B+ tree indexing method and device of real-time database |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN102402602A true CN102402602A (en) | 2012-04-04 |
Family
ID=45884802
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN2011103675946A Pending CN102402602A (en) | 2011-11-18 | 2011-11-18 | B+ tree indexing method and device of real-time database |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN102402602A (en) |
Cited By (19)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102722449A (en) * | 2012-05-24 | 2012-10-10 | 中国科学院计算技术研究所 | Key-Value local storage method and system based on solid state disk (SSD) |
| CN104281685A (en) * | 2014-10-09 | 2015-01-14 | 国电南瑞科技股份有限公司 | Realtime database integer-type keyword storage method and lookup algorithms thereof |
| CN104794196A (en) * | 2015-04-21 | 2015-07-22 | 浙江大学 | Tree structure data collecting and updating method |
| CN108694219A (en) * | 2017-04-12 | 2018-10-23 | 腾讯科技（深圳）有限公司 | A kind of data processing method and device |
| CN108989400A (en) * | 2018-06-28 | 2018-12-11 | 郑州云海信息技术有限公司 | A kind of method, device and equipment of cloud storage gateway reading and writing of files |
| CN109359164A (en) * | 2018-09-12 | 2019-02-19 | 中国人民解放军陆军工程大学 | A kind of road network mobile object prediction probability range query method |
| CN110233946A (en) * | 2019-06-17 | 2019-09-13 | 三角兽（北京）科技有限公司 | Execute outbound call service method, electronic equipment and computer readable storage medium |
| CN110888934A (en) * | 2019-11-12 | 2020-03-17 | 中核控制系统工程有限公司 | Scatter-based big data storage method |
| CN111190903A (en) * | 2019-12-27 | 2020-05-22 | 柏科数据技术（深圳）股份有限公司 | Btree block indexing technology for disaster recovery client |
| CN111274349A (en) * | 2020-01-21 | 2020-06-12 | 北方工业大学 | Public security data hierarchical indexing method and device based on information entropy |
| CN111522814A (en) * | 2020-04-14 | 2020-08-11 | 西云图科技(北京)有限公司 | Information management method of water affair system |
| CN111581205A (en) * | 2019-03-15 | 2020-08-25 | 北京忆芯科技有限公司 | B + tree operation device with node index and method thereof |
| CN111581204A (en) * | 2019-03-15 | 2020-08-25 | 北京忆芯科技有限公司 | Multi-B + tree operation device and method thereof |
| CN111597146A (en) * | 2020-05-20 | 2020-08-28 | 浙江大华技术股份有限公司 | Video file processing method and device, storage medium and electronic device |
| CN111857490A (en) * | 2020-07-17 | 2020-10-30 | 苏州易卖东西信息技术有限公司 | Vue-based pull-down selection component construction method supporting multi-tree structure |
| CN113190645A (en) * | 2021-05-31 | 2021-07-30 | 国家电网有限公司大数据中心 | Index structure establishing method, device, equipment and storage medium |
| CN113380356A (en) * | 2021-05-10 | 2021-09-10 | 广州零端科技有限公司 | Medical examination data recording method, query method and device based on branch chain type tracing |
| CN114153851A (en) * | 2021-12-06 | 2022-03-08 | 智慧足迹数据科技有限公司 | GEOHASH indexing method, GEOHASH indexing device, computer equipment and storage medium |
| CN117312327A (en) * | 2023-11-28 | 2023-12-29 | 苏州元脑智能科技有限公司 | Data storage method, device, equipment and computer readable storage medium |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20070118574A1 (en) * | 2005-11-22 | 2007-05-24 | Franklin William J | Reorganizing data with update activity |
| CN101286160A (en) * | 2008-05-30 | 2008-10-15 | 同济大学 | Data base indexing process |
-
2011
- 2011-11-18 CN CN2011103675946A patent/CN102402602A/en active Pending
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20070118574A1 (en) * | 2005-11-22 | 2007-05-24 | Franklin William J | Reorganizing data with update activity |
| CN101286160A (en) * | 2008-05-30 | 2008-10-15 | 同济大学 | Data base indexing process |
Non-Patent Citations (2)
| Title |
|---|
| 杜冀秦: "基于B+树索引的实时数据库缓冲区管理算法", 《计算机光盘软件与应用》, no. 12, 31 December 2010 (2010-12-31), pages 116 * |
| 王英强等: "B + 树在数据库索引中的应用", 《长江大学学报(自然科学版)》, vol. 5, no. 1, 31 March 2008 (2008-03-31), pages 233 - 235 * |
Cited By (27)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2013174305A1 (en) * | 2012-05-24 | 2013-11-28 | 华为技术有限公司 | Ssd-based key-value type local storage method and system |
| CN102722449B (en) * | 2012-05-24 | 2015-01-21 | 中国科学院计算技术研究所 | Key-Value local storage method and system based on solid state disk (SSD) |
| CN102722449A (en) * | 2012-05-24 | 2012-10-10 | 中国科学院计算技术研究所 | Key-Value local storage method and system based on solid state disk (SSD) |
| CN104281685B (en) * | 2014-10-09 | 2018-06-19 | 国电南瑞科技股份有限公司 | A kind of real-time data base integer type key word storing method and its lookup algorithm |
| CN104281685A (en) * | 2014-10-09 | 2015-01-14 | 国电南瑞科技股份有限公司 | Realtime database integer-type keyword storage method and lookup algorithms thereof |
| CN104794196B (en) * | 2015-04-21 | 2018-07-31 | 浙江大学 | A kind of acquisition of tree structure data and update method |
| CN104794196A (en) * | 2015-04-21 | 2015-07-22 | 浙江大学 | Tree structure data collecting and updating method |
| CN108694219A (en) * | 2017-04-12 | 2018-10-23 | 腾讯科技（深圳）有限公司 | A kind of data processing method and device |
| CN108694219B (en) * | 2017-04-12 | 2023-05-19 | 腾讯科技（深圳）有限公司 | Data processing method and device |
| CN108989400A (en) * | 2018-06-28 | 2018-12-11 | 郑州云海信息技术有限公司 | A kind of method, device and equipment of cloud storage gateway reading and writing of files |
| CN109359164A (en) * | 2018-09-12 | 2019-02-19 | 中国人民解放军陆军工程大学 | A kind of road network mobile object prediction probability range query method |
| CN111581205A (en) * | 2019-03-15 | 2020-08-25 | 北京忆芯科技有限公司 | B + tree operation device with node index and method thereof |
| CN111581204A (en) * | 2019-03-15 | 2020-08-25 | 北京忆芯科技有限公司 | Multi-B + tree operation device and method thereof |
| CN110233946A (en) * | 2019-06-17 | 2019-09-13 | 三角兽（北京）科技有限公司 | Execute outbound call service method, electronic equipment and computer readable storage medium |
| CN110888934A (en) * | 2019-11-12 | 2020-03-17 | 中核控制系统工程有限公司 | Scatter-based big data storage method |
| CN111190903A (en) * | 2019-12-27 | 2020-05-22 | 柏科数据技术（深圳）股份有限公司 | Btree block indexing technology for disaster recovery client |
| CN111274349A (en) * | 2020-01-21 | 2020-06-12 | 北方工业大学 | Public security data hierarchical indexing method and device based on information entropy |
| CN111522814A (en) * | 2020-04-14 | 2020-08-11 | 西云图科技(北京)有限公司 | Information management method of water affair system |
| CN111597146A (en) * | 2020-05-20 | 2020-08-28 | 浙江大华技术股份有限公司 | Video file processing method and device, storage medium and electronic device |
| CN111597146B (en) * | 2020-05-20 | 2023-04-07 | 浙江大华技术股份有限公司 | Video file processing method and device, storage medium and electronic device |
| CN111857490A (en) * | 2020-07-17 | 2020-10-30 | 苏州易卖东西信息技术有限公司 | Vue-based pull-down selection component construction method supporting multi-tree structure |
| CN113380356A (en) * | 2021-05-10 | 2021-09-10 | 广州零端科技有限公司 | Medical examination data recording method, query method and device based on branch chain type tracing |
| CN113380356B (en) * | 2021-05-10 | 2024-04-16 | 广州零端科技有限公司 | Branch chain type traceable medical examination data recording method, inquiring method and device |
| CN113190645A (en) * | 2021-05-31 | 2021-07-30 | 国家电网有限公司大数据中心 | Index structure establishing method, device, equipment and storage medium |
| CN114153851A (en) * | 2021-12-06 | 2022-03-08 | 智慧足迹数据科技有限公司 | GEOHASH indexing method, GEOHASH indexing device, computer equipment and storage medium |
| CN117312327A (en) * | 2023-11-28 | 2023-12-29 | 苏州元脑智能科技有限公司 | Data storage method, device, equipment and computer readable storage medium |
| CN117312327B (en) * | 2023-11-28 | 2024-03-08 | 苏州元脑智能科技有限公司 | Data storage method, device, equipment and computer readable storage medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN102402602A (en) | B+ tree indexing method and device of real-time database | |
| US10642515B2 (en) | Data storage method, electronic device, and computer non-volatile storage medium | |
| JP6025149B2 (en) | System and method for managing data | |
| CN102122285B (en) | Data cache system and data inquiry method | |
| US11468027B2 (en) | Method and apparatus for providing efficient indexing and computer program included in computer readable medium therefor | |
| CN103914483B (en) | File memory method, device and file reading, device | |
| CN107016100A (en) | A kind of metadata management method based on Nonvolatile memory file system | |
| CN103384256A (en) | Cloud storage method and device | |
| CN106570113B (en) | Mass vector slice data cloud storage method and system | |
| CN105488050A (en) | Database multi-index method, apparatus and system | |
| CN111427847A (en) | Indexing and query method and system for user-defined metadata | |
| CN102479189A (en) | Indexing method for high-speed uniform access to massive timestamp data in internal memory | |
| CN105447166A (en) | Keyword based information search method and system | |
| CN104424219A (en) | Method and equipment of managing data documents | |
| Ramamohanarao et al. | Recursive linear hashing | |
| CN103279489A (en) | Method and device for storing metadata | |
| CN104572862A (en) | Mass data storage access method and system | |
| US9767107B1 (en) | Parallel file system with metadata distributed across partitioned key-value store | |
| JP2015528957A (en) | Distributed file system, file access method, and client device | |
| US8156126B2 (en) | Method for the allocation of data on physical media by a file system that eliminates duplicate data | |
| CN104699815A (en) | Data processing method and system | |
| WO2015129109A1 (en) | Index management device | |
| CN105468599A (en) | Metadata hierarchy management method for storage virtualization system | |
| JP2007048318A (en) | Relational database processing method and relational database processor | |
| KR100878142B1 (en) | Method of configuring a modified b-tree index for an efficient operation on flash memory |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C12 | Rejection of a patent application after its publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20120404 |