CN102156759A - Binary tree parallel inquiry method and device - Google Patents
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Abstract
The embodiment of the invention relates to a binary tree parallel inquiry method and a device thereof. The binary tree parallel inquiry method comprises the following steps of: dividing the binary tree into a plurality of sub-tress via a selected sub-tree order; constructing a common key word to each sub-tree, comprising extracting the same high-bit data of all the node data in the sub-tree as the common key word from the high bit of each node data of each sub-tree; constructing a high-bit key word to be inquired from the key word to be inquired according to the bit number of the common key word of the sub-tree, comprising extracting the high bit data of the key word to be inquired as the high-bit key word to be inquired from the highest bit according to the bit number of the common key word; comparing the high-bit key word to be inquired with the common key word of the sub-tree, determining the direction of the sub-tree to be inquired next time if the high-bit key word to be inquired is not equal to the common key word of the sub-tree, and comparing the direction of the sub-tree to be inquired next time according to parallel key words if the high-bit key word to be inquired is equal to the common key word of the sub-tree. Via the embodiment of the invention, the binary tree is compressed into a low-order sub-tree to reduce the height of the target inquiry tree; the common key word of each sub-tree is extracted; and a parallel inquiry key words to each sub-tree is constructed so that the access time of a data memory region is greatly reduced, and the inquiring efficiency is improved.
Description
Technical field
The embodiment of the invention relates to the communications field, is specifically related to parallel lookup method of binary tree and equipment.
Background technology
Binary tree is widely used in various searching in the structure, and it is simple in structure, search performance only with the height correlation of tree.Can not effectively improve the performance of searching of binary tree based on traditional binary tree.Prior art must be finished finally by the mode of node comparison successively and search when carrying out binary tree search.Owing to need successively carry out node relatively, therefore the binary tree that is H for a height need internally deposit into capable H visit.Use the existing technology of searching, can't be again have breakthrough searching on the performance.
Summary of the invention
The technical matters that the embodiment of the invention will solve on the one hand is to reduce the internal storage access number of times, and improves binary tree search efficient.
The embodiment of the invention has proposed the parallel lookup method of a kind of binary tree, comprising: with selected subtree exponent number binary tree is divided into a plurality of subtrees; Be each subtree structure common keywords, comprise:, extract in the subtree all identical high position datas of node datas, as the subtree common keywords of this subtree from the most significant digit of each node data of each subtree; According to figure place, from waiting that looking into the key word structure waits to look into high-order key word, comprising:,, extract the high position data of waiting to look into key word, as waiting to look into high-order key word from most significant digit according to the figure place of common keywords according to the common keywords of subtree; Relatively wait to look into high-order key word and subtree common keywords, when the comparative result of waiting to look into high-order key word and subtree common keywords is unequal, determine the subtree direction of next time searching according to comparative result.
A kind of parallel equipment of searching of binary tree that is used for, equipment comprises: compression module is used for selected subtree exponent number binary tree being divided into a plurality of subtrees; Parallel search key constructing module, be used to each subtree structure common keywords, comprise: from the most significant digit of each node data of each subtree, extract the identical high position data of whole node datas in the subtree, subtree common keywords as this subtree, parallel search key constructing module is used for according to the figure place according to the common keywords of subtree, from waiting that looking into the number structure waits to look into high-order key word, comprise: according to the figure place of common keywords, from most significant digit, extraction waits to look into the high position data of key word, as waiting to look into high-order key word; Comparison module is used for relatively waiting to look into high-order key word and subtree common keywords, and control module is used for when the comparative result of waiting to look into high-order key word and subtree common keywords is unequal, determines the subtree direction of next time searching according to comparative result.
According to the embodiment of the invention, with the subtree of the low exponent number of binary tree boil down to, extract the common keywords of each subtree and be the parallel search key of each subtree structure, can significantly reduce the access times of data memory area, thus the raising search efficiency.
Description of drawings
In order to be illustrated more clearly in the technical scheme of the embodiment of the invention, to do to introduce simply to the accompanying drawing of required use in embodiment or the description of the Prior Art below, apparently, accompanying drawing in describing below only is some embodiments of the present invention, for those of ordinary skills, under the prerequisite of not paying creative work, can also obtain other accompanying drawing according to these accompanying drawings.In the accompanying drawings:
Fig. 1 is the process flow diagram of embodiment of the invention method;
Fig. 2 is the structural drawing of the employed binary tree of the embodiment of the invention;
Fig. 3 is the structural drawing of the equipment of the embodiment of the invention.
Embodiment
Below in conjunction with the accompanying drawing in the embodiment of the invention, the technical scheme in the embodiment of the invention is clearly and completely described, obviously, described embodiment is the present invention's part embodiment, rather than whole embodiment.Based on the embodiment among the present invention, those of ordinary skills belong to the scope of protection of the invention not making the every other embodiment that is obtained under the creative work prerequisite.
The design of the embodiment of the invention is, when in binary tree, carrying out the node comparison, at first binary tree (for example is divided into the low order subtree, 3 rank subtrees), the high position data of the node data of each subtree is extracted, with described high position data with wait to look into the data high position data relatively, if it is unequal with the common keywords of subtree to wait to look into the high position data of key word, then according to the directly definite more selected next time low order subtree of the comparative result of high position data., illustrate and wait to look into whole node datas of key word during at the high position data of waiting to look into key word, then search the subtree chosen next time and be maximum subtree in one deck low order subtree down greater than current subtree greater than the common keywords of subtree., illustrate and wait to look into whole node datas of key word during at the high position data of waiting to look into key word, then search the subtree chosen next time and be minimum subtree in one deck low order subtree down less than current subtree less than the common keywords of subtree.Utilize this mode, can filter out the high position data subtree different of waiting to look into key word fast, and avoid the comparison low data, accelerated seek rate, improved search efficiency with the high position data of subtree node data.When the high position data of waiting to look into key word equals the high position data of node data, utilize the parallel search key of low data structure of a location number of subtree node data, by disposable comparison, determine to search selected subtree next time.Can reduce comparison step like this, accelerate seek rate.The concrete example of the embodiment of the invention will be described in detail with reference to accompanying drawing following.
Fig. 1 is the process flow diagram of the binary tree search method of the embodiment of the invention.This method comprises:
110: described binary tree is divided into a plurality of subtrees with selected subtree exponent number;
120: be each subtree structure common keywords, comprise:, extract in the described subtree all identical high position datas of node datas, as the subtree common keywords of this subtree from the most significant digit of each node data of each subtree;
130: according to figure place, from waiting that looking into the key word structure waits to look into high-order key word, comprising:,, extract the high position data of waiting to look into key word, as waiting to look into high-order key word from most significant digit according to the figure place of described common keywords according to the common keywords of described subtree;
140: more describedly wait to look into high-order key word and described subtree common keywords, when the described comparative result of waiting to look into high-order key word and described subtree common keywords is unequal, determine the subtree direction of next time searching according to comparative result.
Following with reference to Fig. 2, the method for the embodiment of the invention is described with concrete example.Fig. 2 is the structural drawing of binary tree of implementing the binary tree search method of the embodiment of the invention.Need to prove that what provide among Fig. 2 is complete binary tree, but the embodiment of the invention is applicable to non-complete binary tree comparably.In addition, the employed binary tree of the embodiment of the invention is an ordered binary tree.For example, binary tree shown in Fig. 2 is an ordered binary tree, and wherein the magnitude relationship of node data is that A to G increases progressively.According to the embodiment of the invention, for example binary tree shown in Figure 2 is divided into 3 rank subtrees, wherein node A to G constitutes one 3 rank subtree SS, and respectively there are two 3 rank subtrees node A, C, E and G below, and giving Reference numeral respectively is S0 to S7.Need to prove that it is a kind of illustrating that binary tree is divided into 3 rank subtrees.It will be understood by those skilled in the art that can be according to computing power and actual needs, and for example binary tree is non-complete binary tree, and left subtree or right subtree lack a plurality of nodes, then binary tree can be divided into 4 rank subtrees, 5 rank subtrees, to improve search efficiency.
After binary tree is divided into 3 rank subtrees, will be each subtree, comprise subtree SS, S0-S7 structure common keywords.For example, the data of the node A-G of SS subtree are as shown in the table among Fig. 2:
Table 1
| 19 | 18 | 17 | 16 | 15 | 14 | 13 | 12 | 11 | 10 | 9 | 8 | 7 | 6 | 5 | 4 | 3 | 2 | 1 | 0 | |
| A | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 1 |
| B | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 1 | 1 |
| C | 1 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 0 | 0 |
| D | 1 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 0 | 0 |
| E | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 1 | 0 | 1 | 0 | 1 | 1 | 0 | 0 |
| F | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 1 | 0 |
| G | 1 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 1 | 0 |
At first, extract the identical high position data of node A-G.As can be seen from Table 1, the 17-19 bit data of node A-G is identical, this 3 bit data is extracted, as the subtree common keywords CmSS of SS subtree.Then, extract the 17-19 bit data the key word K from waiting to look into, as waiting to look into high-order key word CmK.
Like this, just can compare the subtree common keywords CmSS that waits to look into high-order key word CmK and SS subtree of K earlier,, therefore search next time and directly enter the S7 subtree if CmK＞CmSS then illustrates K＞G; If CmK＜CmSS then illustrates K＜A, then search next time and directly enter the S0 subtree.So, will no longer compare K and Node B size, and also no longer compare the 0-16 bit data of K and the 0-16 bit data of node A to G, accelerate seek rate greatly to F.
Under the situation of CmK=CmSS, illustrate that then K might equate with node A-G is some, perhaps search next time and will enter subtree S1 to S6, then in order further to determine K with which node among the A-G equates, perhaps search next time and will enter which subtree, be the parallel search key of subtree SS structure.
Specifically, as shown in table 1, from the high position of node A-G, be connected on after the CmSS, extract 8 bit data, i.e. the 9-16 bit data, be called the compression key word, according to order from left to right, with node A-G from big to small, promptly from G to A, the compression key word cG-cA of each node is stitched together, before each compression key word sign bit s is set, the value of sign bit s is set to 0, constitutes 63 data thus.Initial value was set then is 1 effective marker position v before this 63 bit data most significant digit, constitute 64 bit data, be called the parallel search key of subtree SS.With binary tree shown in Figure 2 is example, and the compression key word of node A-G is respectively:
cA：00101001
cB：00101?010
cC：00110?000
cD：00110?001
cE：10000?011
cF：10000?100
cG：11000?100
Parallel search key P0 according to following form structure subtree SS:
v-s-cG-s-cF-s-cE-s-cD-s-cC-s-cB-cA
The parallel search key P0 that obtains subtree SS is:
1?0?11000100?0?10000100?0?10000011?0?0011?0?001000110000?0?001010100?00101001
For example, it is as shown in table 2 to wait to look into the data of key word K:
Table 2
| 19 | 18 | 17 | 16 | 15 | 14 | 13 | 12 | 11 | 10 | 9 | 8 | 7 | 6 | 5 | 4 | 3 | 2 | 1 | 0 | |
| K | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 1 | 1 | 0 | 0 | 1 | 0 | 1 | 1 | 1 | 0 |
At this moment, the 17-19 bit data CmK of K equates with CmSS, is 110.In this case, the low 9-16 bit data of K is extracted, as waiting to look into key word cK.According to table 2, key word to be looked into is: 00101011, according to the same way as of the parallel search key of constructing subtree SS, promptly wait to look into parallel key word P1 then according to following form structure:
v-s-cK-s-cK-s-cK-s-cK-s-cK-s-cK-s-cK
What obtain waiting looking into key word waits that looking into parallel key word P1 is:
1?0?00101011?0?00101011?0?00101011?0?00101011?0?00101011?0?001010110?00101011
Wait to look into parallel key word P1 and deduct parallel search key P0 described, obtain comparative result P2, that is:
P2＝P1-P0＝1?0?00101011?000101011?0?00101011?0?00101011?0?00101011?000101011?0?00101011-
1?0?11000100?0?10000100?0?10000011?0?00110001?0?00110000?0?001010100?00101001＝
1?1?01100110?1?10100110?1?1010011?1?11111100?1?111111011?0?000000010?00000010
Then, check the number that sign bit s changes among the comparative result P2.Specifically, with P2 and check key word Px with, the sign bit s among the extraction P2, Px=
0?1?00000000?1?00000000?1?00000000?1?00000000?1?00000000?1?000000001?00000000。
Assay P3=P2﹠amp; Px=
1?1?01100110?1?10100110?1?1010011?1?111111001?1?11111011?0?00000001?000000010&
0?1?00000000?1?00000000?1?00000000?1?00000000?1?00000000?1?000000001?00000000＝
0?1?00000000?1?00000000?1?00000000?1?00000000?1?00000000?0?000000000?00000000
1 number is 5 among the P3, illustrate that sign bit s has 5 to change, and have 2 sign bit s not change, this be because cK greater than cA and cB, but less than the reason of cC to cG.Can draw thus, search next time and enter subtree S2.That is to say, can determine to search the subtree Sn that will enter next time according to the number n of the sign bit s that does not change among the P3.
If 1 number is 4 among the P3, the number of the sign bit s that does not then change is 3, and cC＜cK＜cD then is described, then search next time and enter subtree S3, and the like.
If find that in P2 certain sign bit s is 0, for example, find that the sign bit s before the cD is 0, and 8 bit data thereafter are 0, cK=cD then is described.In this case, can read the partial data of node D, itself and K are compared, whether D is the data that need search with the checking node.
Here it is emphasized that in above example the compression key word select is got 8, it is bright that this only is that a kind of example is stated, and the figure place of compression key word can be determined according to data-handling capacity, subtree exponent number, subtree node number.For example, if having 64 data-handling capacity according to CPU, then parallel key word selects 64 bit comparisons suitable, like this for 3 rank complete subtree with 7 nodes, then the length of compression key word just is | 64/7|=9,9 deduct 1 as sign bit s, obtain 8.If 3 rank subtrees have only 4 effective nodes, the length of then compressing KEY can be | 64/5|=12, deduct 1 bit sign position s, and obtain 11, promptly the compression key word can select 11.If use the hardware logic of the higher special use of figure place to come deal with data, for example adopt 128 application specific processor, then the length of parallel key word can be accomplished longlyer, then also can to choose ground bigger for the figure place of compression key word.Optimal situation is that the hardware logic figure place is enough high, the figure place of compression key word can be chosen as remaining whole figure places except common keywords, then can finish the affirmation and the next search direction of lookup result simultaneously and confirm in once compare.
If in the SS subtree, do not find the data that need, when entering subtree S0-S7 and search, equally according to the method described above, compare the subtree common keywords earlier, the parallel search key of structure repeats above process then, waits to look into key word K up to finding, perhaps find minimum one deck subtree of binary tree, return the state notifying that does not find.
Need to prove, in search procedure, for subtree SS, S0-S7 and more the low layer subtree extract subtree common keywords, the parallel search key of structure, generally only carry out once, and will construct good subtree common keywords, parallel search key is preserved, under the situation that sub-tree structure and subtree node data do not change, do not need all to extract the parallel search key of subtree common keywords and structure, with further raising search efficiency at every turn.
The embodiment of the invention also relates to a kind of parallel equipment of searching of binary tree that is used for, as shown in Figure 2.With reference to Fig. 2, described equipment 300 comprises: compression module 310 is used for selected subtree exponent number described binary tree being divided into a plurality of subtrees; Parallel search key constructing module 320, be used to each subtree structure common keywords, comprise: from the most significant digit of each node data of each subtree, extract the identical high position data of whole node datas in the described subtree, subtree common keywords as this subtree, described parallel search key constructing module 320 is used for according to the figure place according to the common keywords of described subtree, from waiting that looking into the key word structure waits to look into high-order key word, comprise: according to the figure place of described common keywords, from most significant digit, extraction waits to look into the high position data of key word, as waiting to look into high-order key word; Comparison module 330 is used for more described wait to look into high-order key word and described subtree common keywords; Control module 340 is used for when the described comparative result of waiting to look into high-order key word and described subtree common keywords is unequal, determines the subtree direction of next time searching according to comparative result.
According to the embodiment of the invention, described when waiting to look into high-order key word and equating with the comparative result of described subtree common keywords, described parallel search key constructing module 320 is used to the parallel search key of each subtree structure, wherein from the described identical high position data of each node data, the data of figure place are selected in intercepting successively, as the compression key word, search the magnitude relationship order of node data in the subtree according to each, to be spliced into the parallel search key of described subtree from the described compression key word of each node data, separate with sign bit between each compression key word, and described parallel search key constructing module 320 is used for waiting to look into parallel key word according to data configuration described to be looked into, wherein from the described described high position data of waiting to look into data, intercept the data of described selected figure place successively, as key word to be looked into, and according to the interstitial content of described subtree key word described to be looked into is repeated to be spliced into and wait to look into parallel key word, each is waited to look between the key word and separates with sign bit; Described comparison module 330 is used for waiting to look into parallel key word and deducting parallel search key described, obtains key word as a result; Described control module 340 is determined the number of the sign bit that changes in described key word as a result, and according to the number of the sign bit that changes in the described key word as a result, determines the subtree direction of next time searching.
According to the embodiment of the invention, described control module 340 is used at described key word as a result, determine the position that described sign bit does not change, and judge in position that described sign bit does not change, constitute described wait to look into parallel key word wait whether look into key word equates with the compression key word of the described parallel search key of formation, when equal, described comparison module 330 is used to obtain and the corresponding node data of described compression key word, and waits to look into data and described node data compares with described.
According to the embodiment of the invention, with the subtree of the low exponent number of binary tree boil down to, extract the common keywords of each subtree and be the parallel search key of each subtree structure, can significantly reduce the read-write number of times of data memory area, improve search efficiency.
Those of ordinary skills can recognize, the unit and the algorithm steps of each example of describing in conjunction with embodiment disclosed herein, can realize with electronic hardware, computer software or the combination of the two, for the interchangeability of hardware and software clearly is described, the composition and the step of each example described prevailingly according to function in the above description.These functions still are that software mode is carried out with hardware actually, depend on the application-specific and the design constraint of technical scheme.The professional and technical personnel can use distinct methods to realize described function to each specific should being used for, but this realization should not thought and exceeds scope of the present invention.
The method of describing in conjunction with embodiment disclosed herein or the step of algorithm can use the software module of hardware, processor execution, and perhaps the combination of the two is implemented.Software module can place the storage medium of any other form known in random access memory (RAM), internal memory, ROM (read-only memory) (ROM), electrically programmable ROM, electrically erasable ROM, register, hard disk, moveable magnetic disc, CD-ROM or the technical field.
Although illustrated and described some embodiments of the present invention, it will be understood by those skilled in the art that without departing from the principles and spirit of the present invention can carry out various modifications to these embodiment, such modification should fall within the scope of the present invention.
Claims (10)
1. the parallel lookup method of binary tree is characterized in that,
With selected subtree exponent number described binary tree is divided into a plurality of subtrees;
Be each subtree structure common keywords, comprise:, extract in the described subtree all identical high position datas of node datas, as the subtree common keywords of this subtree from the most significant digit of each node data of each subtree;
According to the figure place of the common keywords of described subtree, from waiting that looking into the tree structure waits to look into high-order key word, comprising:,, extract the high position data of waiting to look into key word, as waiting to look into high-order key word from most significant digit according to the figure place of described common keywords;
More describedly wait to look into high-order key word and described subtree common keywords, when the described comparative result of waiting to look into high-order key word and described subtree common keywords is unequal, directly determine the subtree direction of next time searching according to comparative result.
2. the method for claim 1 is characterized in that, described method also comprises:
Described when waiting to look into high-order key word and equating with the comparative result of described subtree common keywords,
Be the parallel search key of each subtree structure, wherein from the described identical high position data of each node data, the data of figure place are selected in intercepting successively, as the compression key word, search the magnitude relationship order of node data in the subtree according to each, to be spliced into the parallel search key of described subtree from the described compression key word of each node data, separate with sign bit between each compression key word
Wait to look into parallel key word according to data configuration described to be looked into, wherein from the described described high position data of waiting to look into data, intercept the data of described selected figure place successively, as key word to be looked into, and according to the interstitial content of described subtree key word described to be looked into is repeated to be spliced into and wait to look into parallel key word, each is waited to look between the key word and separates with sign bit
Wait to look into parallel key word and deduct parallel search key described, obtain key word as a result;
In described key word as a result, the number of definite sign bit that does not change according to the number of the sign bit that does not change in the described key word as a result, is determined the subtree direction of next time searching.
3. method as claimed in claim 2 is characterized in that,
In described key word as a result, determine the position that described sign bit does not change, and judge in position that described sign bit does not change, constitute described wait to look into parallel key word wait whether look into key word equates with the compression key word of the described parallel search key of formation, when equal, obtain and the corresponding node data of described compression key word, and wait to look into data and described node data compares described.
4. as each described method of claim 1 to 3, it is characterized in that, describedly described binary tree be divided into a plurality of subtrees, comprising with selected subtree exponent number:
Described binary tree is divided into a plurality of 3 rank subtrees;
5. as claim 2 or 3 described methods, it is characterized in that,
Described is the parallel search key of each subtree structure, and wherein from the described identical high position data of each node data, the data of figure place are selected in intercepting successively, as the compression key word, comprising:
Described for the parallel search key of each subtree structure, wherein, intercept 8 bit data successively, as the compression key word from the described identical high position data of each node data.
6. one kind is used for the parallel equipment of searching of binary tree, it is characterized in that described equipment comprises:
Compression module is used for selected subtree exponent number described binary tree being divided into a plurality of subtrees;
Parallel search key constructing module, be used to each subtree structure common keywords, comprise:, extract in the described subtree all identical high position datas of node datas from the most significant digit of each node data of each subtree, subtree common keywords as this subtree
Described parallel search key constructing module is used for according to the figure place according to the common keywords of described subtree, from waiting that looking into the number structure waits to look into high-order key word, comprising: according to the figure place of described common keywords, from most significant digit, extraction waits to look into the high position data of key word, as waiting to look into high-order key word;
Comparison module is used for more described wait to look into high-order key word and described subtree common keywords,
Control module is used for when the described comparative result of waiting to look into high-order key word and described subtree common keywords is unequal, determines the subtree direction of next time searching according to comparative result.
7. equipment as claimed in claim 6 is characterized in that,
Described when waiting to look into high-order key word and equating with the comparative result of described subtree common keywords,
Described parallel search key constructing module is used to the parallel search key of each subtree structure, wherein from the described identical high position data of each node data, the data of figure place are selected in intercepting successively, as the compression key word, search the magnitude relationship order of node data in the subtree according to each, to be spliced into the parallel search key of described subtree from the described compression key word of each node data, separate with sign bit between each compression key word
And described parallel search key constructing module is used for waiting to look into parallel key word according to data configuration described to be looked into, wherein from the described described high position data of waiting to look into data, intercept the data of described selected figure place successively, as key word to be looked into, and according to the interstitial content of described subtree key word described to be looked into is repeated to be spliced into and wait to look into parallel key word, each is waited to look between the key word and separates with sign bit;
Described comparison module is used for waiting to look into parallel key word and deducting parallel search key described, obtains key word as a result;
Described control module is in described key word as a result, and the number of definite sign bit that does not change according to the number of the sign bit that does not change in the described key word as a result, is determined the subtree direction of next time searching.
8. equipment as claimed in claim 7 is characterized in that,
Described control module is used at described key word as a result, determine the position that described sign bit does not change, and judge in position that described sign bit does not change, constitute described wait to look into parallel key word wait whether look into key word equates with the compression key word of the described parallel search key of formation, when equal, described comparison module is used to obtain and the corresponding node data of described compression key word, and waits to look into data and described node data compares with described.
9. as each described equipment of claim 6 to 8, it is characterized in that described compression module is divided into a plurality of 3 rank subtrees with described binary tree.
10. as claim 7 or 8 described equipment, it is characterized in that described parallel search key constructing module intercepts 8 bit data successively from the described identical high position data of each node data, as described compression key word.
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| CN102739520A (en) * | 2012-05-31 | 2012-10-17 | 华为技术有限公司 | Checking method and checking device |
| CN103765381A (en) * | 2011-08-29 | 2014-04-30 | 英特尔公司 | Parallel operation on B+ trees |
| CN105335411A (en) * | 2014-07-31 | 2016-02-17 | 国际商业机器公司 | Method and system for data processing |
| CN107798073A (en) * | 2017-09-29 | 2018-03-13 | 华为技术有限公司 | The method and apparatus of data acquisition system of the processing with tree structure |
| US10943618B1 (en) | 2020-03-19 | 2021-03-09 | Wang Chau Tyler Kot | Ethereum state data storage optimization method, Ethereum system and storage medium |
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Cited By (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103765381A (en) * | 2011-08-29 | 2014-04-30 | 英特尔公司 | Parallel operation on B+ trees |
| US9405782B2 (en) | 2011-08-29 | 2016-08-02 | Intel Corporation | Parallel operation in B+ trees |
| CN103765381B (en) * | 2011-08-29 | 2016-08-31 | 英特尔公司 | Parallel work-flow to B+ tree |
| CN102739520A (en) * | 2012-05-31 | 2012-10-17 | 华为技术有限公司 | Checking method and checking device |
| CN102739520B (en) * | 2012-05-31 | 2015-03-18 | 华为技术有限公司 | Checking method and checking device |
| CN105335411A (en) * | 2014-07-31 | 2016-02-17 | 国际商业机器公司 | Method and system for data processing |
| US10747781B2 (en) | 2014-07-31 | 2020-08-18 | International Business Machines Corporation | Determination of data partition |
| CN107798073A (en) * | 2017-09-29 | 2018-03-13 | 华为技术有限公司 | The method and apparatus of data acquisition system of the processing with tree structure |
| CN107798073B (en) * | 2017-09-29 | 2020-07-24 | 华为技术有限公司 | Method and device for processing data set with tree structure |
| US10943618B1 (en) | 2020-03-19 | 2021-03-09 | Wang Chau Tyler Kot | Ethereum state data storage optimization method, Ethereum system and storage medium |
| WO2021184325A1 (en) * | 2020-03-19 | 2021-09-23 | Wang Chau Tyler Kot | Ethereum state data storage optimization method, ethereum system and storage medium |
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