CN105913656B - Based on the frequent method and system for crossing vehicle of distributed statistics - Google Patents
Based on the frequent method and system for crossing vehicle of distributed statistics Download PDFInfo
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0125—Traffic data processing
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- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/27—Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0137—Measuring and analyzing of parameters relative to traffic conditions for specific applications
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Abstract
The present invention is disclosed based on the frequent method for crossing vehicle of distributed statistics, comprising: is frequently crossed vehicle statistical condition according to presetting and is generated that statistics is frequent to cross vehicle request；The frequent vehicle of crossing of statistics is sent to each node of distributed memory system to request；It receives each node and car data is crossed according to the bayonet for meeting preset bayonet information, information of vehicles and vehicle time requirement excessively that the frequent request of vehicle excessively determines, and bayonet is crossed into car data and is saved by the format of bayonet information and vehicles identifications；The bayonet that traversal saves crosses car data, merges the car data excessively of each bayonet, counts the train number number excessively of every trolley in each bayonet data and saves；Traverse every trolley in each bayonet crosses train number number, crosses vehicle frequency threshold value according to preset, deletes the car data of crossing that train number number does not meet threshold requirement, and statistics obtains frequently crossing the bayonet information of vehicle, information of vehicles, spends the vehicle time and cross train number number and save.The present invention, which improves, counts the frequent statistical efficiency for crossing vehicle.
Description
Technical field
The present invention relates to the technical fields for crossing car data statistics, and in particular, to one kind counts frequent mistake based on distributed
The method and system of vehicle.
Background technique
In recent years, with the improvement of people's living standard and the progress of technology, automobile also becomes people's daily trip
Vehicles of common greatly facilitates people's lives and work.But on the other hand, automobile is for people's lives and work
While making to provide convenient, chance also is provided for many law-breakers, now using automobile as the thing of guilty tool
Part emerges one after another, for example hit-and-run, drives to run away, tracking etc. of driving.If the stroke letter of these crime vehicles can be found
Breath often tracks down the case of violation of law to people's police and provides great convenience condition.With the hair of Internet technology and the information processing technology
Exhibition, the intelligent analysis of various information and is treated as popular research content in the industry.In addition the transit equipment of various regions now
It increases significantly, the construction of Traffic Information Engineering, also forms the information acquiring technology of mature vehicle.In the prior art, pass through
The vehicle data acquisition equipment collection of bayonet crosses car data in the vehicle of each bayonet, and is stored in relational database or disperses not having
In related text data.If it is desired to obtain vehicle crosses train number number there are two types of mode: manually carrying out statistics and from relationship number
It is counted in.
But acquire that equipment is collected into it is imperfect by the characteristic information of bayonet vehicle when, for example do not see vehicle product
Board, license plate shading etc., imperfect feature here is not necessarily to be caused by human factor, it is also possible to due to acquisition equipment shooting
The reasons such as direction, angle, light cause, or record personnel only remembered a part of Chu's license plate, the color of vehicle, brand at that time
Situations such as.In the case where car data amount of storage is so big excessively, to find out the infull automobile of feature as sea is fished out
Needle is general.To cross in car data from these will first reduce the seeking scope of car data by screening, can also subtract at double, at hundred times
Few subsequent workload, saves the cost of lookup.In the prior art, frequent vehicle of crossing is calculating vehicle by somewhere (bayonet)
Number, by vehicle cross the number of vehicle screen out according to preset condition/capture vehicle data, to reduce seeking scope, and sieve
It selects and reaches the car data set excessively that certain amount crosses train number number, i.e., it is referred to as frequent to cross vehicle.
The bayonet data of the prior art are there are relational database or to disperse in no associated text data, such
In huge data volume, it is clearly unpractical that artificial statistics searches frequent car data excessively；And relevant database is according to friendship
The form storing data of bivariate table is pitched, can also be deposited because of traversing in bivariate table because of the big increase carrying cost of storage data quantity
The huge data of storage are unable to quick search and navigate to target to cross car data, cannot also realize and frequently cross looking into real time for car data
It askes.Simple inquiry also needs several minutes of waiting time, and the frequent speed for crossing car data of statistics is slack-off therewith, far can not
Meet the purpose of actual real-time query and statistics.
Therefore it provides a kind of method counted in big data platform to frequent mistake vehicle efficiently easily implemented is this
Field urgent problem to be solved.
Summary of the invention
In view of this, counting the frequent method and system for crossing vehicle based on distributed the present invention provides a kind of, solve
It crosses in car data and counts frequent the problem of crossing vehicle at high cost, inefficiency.
In order to solve the above-mentioned technical problem, the present invention proposes a kind of based on the frequent method for crossing vehicle of distributed statistics, comprising:
According to preset frequently cross vehicle statistical condition generate statistics it is frequent cross vehicle request；
The frequent vehicle of crossing of the statistics is sent to each node of distributed memory system to request；
It receives each node and meets preset bayonet information, vehicle letter according to what the frequent request of vehicle excessively determined
Breath and the bayonet for crossing vehicle time requirement cross car data, and the bayonet is crossed car data by bayonet information and the format of vehicles identifications
It is saved；Wherein, the vehicles identifications include: license plate number and mistake train number number；
The bayonet that traversal saves crosses car data, and merge each bayonet crosses car data, counts in each bayonet data
Every trolley is crossed train number number and is saved；
The train number number excessively for traversing every trolley in each bayonet crosses vehicle frequency threshold value according to preset, deleted vehicle
Number does not meet the car data of crossing of threshold requirement, and statistics obtains frequently crossing the bayonet information of vehicle, information of vehicles, crosses vehicle time and mistake
Train number number simultaneously saves.
Further, wherein this method further comprises:
Give up each node and requests what is determined not meet preset bayonet information, vehicle according to the frequent vehicle of crossing
Information and the bayonet for spending the vehicle time cross car data.
Further, wherein each bayonet of merging crosses car data, counts every trolley in each bayonet data
It crosses train number number and saves, further comprise:
The car data of crossing of the identical bayonet traversed is merged into the same set；
In each bayonet set, by same license plate number it is all cross train number numbers and be added to obtain the license plate number correspond to vehicle
It train number number and is saved in crossing for corresponding bayonet.
Further, wherein it is described receive each node according to it is described it is frequent cross that vehicle request determines meet and set in advance
Fixed bayonet information, information of vehicles and the bayonet of vehicle time requirement excessively crosses car data, and the bayonet is crossed car data by bayonet
The format of information and vehicles identifications is saved, and further comprises:
Meet preset bayonet from the acquisition of each node of distributed memory system using distributed service framework to believe
The bayonet of breath, information of vehicles and vehicle time requirement excessively crosses car data.
Further, wherein the bayonet crosses car data, further comprises: bayonet number, license plate number, body color,
Vehicle model, vehicle running state and mistake vehicle time.
In addition, the present invention also provides a kind of based on the frequent system for crossing vehicle of distributed statistics, comprising: processing module, transmission
Module, receiving module, filing merging module and statistical module；Wherein,
The processing module, for according to preset frequently cross vehicle statistical condition generate statistics it is frequent cross vehicle request；
The sending module, for sending to each node of distributed memory system, statistics is frequent to cross vehicle request；
The receiving module, for receive each node according to it is described it is frequent cross that vehicle request determines meet and preset
Bayonet information, information of vehicles and cross the bayonet of vehicle time requirement and cross car data, and the bayonet is crossed into car data and is believed by bayonet
The format of breath and vehicles identifications is saved；Wherein, the vehicles identifications include: license plate number and mistake train number number；
The filing merging module crosses car data for traversing the bayonet saved, and merge each bayonet crosses vehicle number
According to counting crossing train number number and saving for every trolley in each bayonet data；
The statistical module crosses vehicle according to preset for traversing the train number number excessively of every trolley in each bayonet
Frequency threshold value, deleted the car data of crossing that train number number does not meet threshold requirement, and statistics obtains bayonet information, the vehicle of frequently crossing vehicle
Information spends the vehicle time and crosses train number number and save.
Further, wherein the receiving module is further used for:
Give up each node and requests what is determined not meet preset bayonet information, vehicle according to the frequent vehicle of crossing
Information and the bayonet for spending the vehicle time cross car data.
Further, wherein the filing merging module is further used for:
The car data of crossing of the identical bayonet traversed is merged into the same set；
In each bayonet set, by same license plate number it is all cross train number numbers and be added to obtain the license plate number correspond to vehicle
It train number number and is saved in crossing for corresponding bayonet.
Further, wherein the receiving module is further used for:
Meet preset bayonet from the acquisition of each node of distributed memory system using distributed service framework to believe
The bayonet of breath, information of vehicles and vehicle time requirement excessively crosses car data.
Further, wherein the bayonet crosses car data, further comprises: bayonet number, license plate number, body color,
Vehicle model, vehicle running state cross train number number and spend the vehicle time.
Compared with prior art, of the invention based on the frequent method and system for crossing vehicle of distributed statistics, it realizes as follows
The utility model has the advantages that
(1) of the present invention based on the frequent method and system for crossing vehicle of distributed statistics, the frequency based on big data platform
It is numerous cross vehicle statistical method, receive on the node of big data platform distributed storage carry out distributed arithmetic as a result, then again into
Row integration, statistics, big data platform can be established in a distributed manner on cheap business PC, and according to the big of data volume
The actual conditions such as small determine the size of distributed type assemblies, can store the data of magnanimity, have saved being made for the frequent vehicle excessively of statistics
Resource, and can use distributed type assemblies and concurrently car data excessively is inquired, is counted, improve the frequent vehicle excessively of statistics
Statistical efficiency.
(2) of the present invention based on the frequent method and system for crossing vehicle of distributed statistics, according to preset requirement
Ineligible data are filtered out in rough estimates, eliminate it is many and diverse cross car data treatment process, thus reduce into
Data volume when row integration statistics, thus shortens and counts the frequent operation time for crossing vehicle and calculating speed.
(3) of the present invention based on the frequent method and system for crossing vehicle of distributed statistics, it is first sieved at data statistics initial stage
Select the requirement that conforms to a predetermined condition cross car data, then count each bayonet every trolley cross train number number after, utilize frequent mistake
The scheduled vehicle frequency threshold value of crossing of vehicle is selected and counts the information for frequently crossing vehicle, in inquiry, statistic processes, the information of each vehicle
Omission is not had, be ensure that and is counted the frequent accuracy for crossing vehicle.
Certainly, implementing any of the products of the present invention must be not necessarily required to reach all the above technical effect simultaneously.
Detailed description of the invention
The drawings described herein are used to provide a further understanding of the present invention, constitutes a part of the invention, this hair
Bright illustrative embodiments and their description are used to explain the present invention, and are not constituted improper limitations of the present invention.In the accompanying drawings:
Figure 1A is the process signal of an alternative embodiment of the invention based on the frequent method for crossing vehicle of distributed statistics
Figure；
Figure 1B is the operating principle schematic diagram of the invention based on the frequent method for crossing vehicle of distributed statistics；
Fig. 2 is that the process of the embodiment based on the frequent method for crossing vehicle of distributed statistics described in the embodiment of the present invention 2 is shown
It is intended to；
Fig. 3 is a specific embodiment based on the frequent method for crossing vehicle of distributed statistics described in the embodiment of the present invention 3
Flow diagram；
Fig. 4 is that the present invention is based on the structural schematic diagrams of an alternative embodiment of the frequent system for crossing vehicle of distributed statistics.
Specific embodiment
As used some vocabulary to censure specific components in the specification and claims.Those skilled in the art answer
It is understood that hardware manufacturer may call the same component with different nouns.This specification and claims are not with name
The difference of title is as the mode for distinguishing component, but with the difference of component functionally as the criterion of differentiation.Such as logical
The "comprising" of piece specification and claim mentioned in is an open language, therefore should be construed to " include but do not limit
In "." substantially " refer within the acceptable error range, those skilled in the art can within a certain error range solve described in
Technical problem basically reaches the technical effect.Specification subsequent descriptions are to implement better embodiment of the invention, so described
Description is the range that is not intended to limit the invention for the purpose of illustrating rule of the invention.Protection scope of the present invention
As defined by the appended claims.
Embodiment 1
As shown in FIG. 1A and 1B, Figure 1A is one based on the frequent method for crossing vehicle of distributed statistics of the invention optional
The flow diagram of embodiment；Figure 1B is the operating principle signal of the invention based on the frequent method for crossing vehicle of distributed statistics
Figure.The present invention is based on distributed memory systems, and the vehicle excessively for the requirement that conforms to a predetermined condition first is filtered out by distributed management control
Data, then carried out the filing of car data, integration and cleaning count it is accurately frequent cross vehicle information, accelerate and frequently cross vehicle
The efficiency of statistics.Described in the present embodiment based on the frequent method for crossing vehicle of distributed statistics the following steps are included:
Step 101 frequently crosses vehicle statistical condition and generates that statistics is frequent to cross vehicle request according to presetting, and deposits to distribution
Each node of storage system sends the frequent vehicle of crossing of statistics and requests.
Distributed memory system (Hadoop), has the characteristics that high fault tolerance, disposes memory node on cheap hardware,
Information transmitting after being managed collectively the data processing of each node by Distributed Services agreement, but because the height that it is provided is handled up
Amount can be used to access application data, make full use of the parallel computation power of distributed type assemblies can be realized high-speed computation and
Storage.It is requested according to the actual frequent frequent vehicle of crossing of vehicle statistical demand generation statistics of crossing, is issued to by distributed management protocol
Each distributed node.
Step 102, each node of reception are believed according to the preset bayonet that meets that the frequent request of vehicle excessively determines
The bayonet of breath, information of vehicles and vehicle time requirement excessively crosses car data, and the bayonet is crossed car data by bayonet information and vehicle
The format of mark is saved；Wherein, the vehicles identifications include: license plate number and mistake train number number.
Each node of distributed memory system receives that statistics is frequent cross vehicle request after, what is stored from it crosses in car data library
Obtain eligible requirement cross car data, wherein each node traverses its storage cross car data, and with preset card
Message breath, information of vehicles and vehicle time requirement excessively are compared, and judge satisfactory car data excessively, so can be according to reality
Border needs to set required condition require information, can carry out filtering out preliminary satisfactory frequent vehicle excessively by each node
Data reduce subsequent merging, statistical work amount, and ensure that the car data of crossing for frequently crossing vehicle does not have omission.
The bayonet that step 103, traversal save crosses car data, and merge each bayonet crosses car data, counts each card
Every trolley crosses train number number and saves in mouth data.
In this step, the car data excessively that preliminary screening goes out in first traversal step 102, that finds out each bayonet crosses car data
It brings together, then the train number number statistics of crossing of every trolley in each bayonet data acquisition system is crossed into train number number for total.In this way,
Crossing train number number and crossing vehicle information for every trolley in each bayonet can accurately be counted, according to bayonet set form into
Row storage, facilitates subsequent further screening.
The train number number excessively of every trolley in step 104, each bayonet of traversal, crosses vehicle frequency threshold value according to preset,
The car data of crossing that train number number does not meet threshold requirement was deleted, statistics obtains frequently crossing the bayonet information of vehicle, information of vehicles, crosses vehicle
Time and excessively train number number simultaneously save.
Wherein, Figure 1B is the operating principle schematic diagram of the invention based on the frequent method for crossing vehicle of distributed statistics.From figure
As can be seen that being converged by step 105,106,107 and 108 pairs of crossing after car data counts for each node in the schematic diagram of 1B
After collecting together；After the filing of car data excessively of each bayonet is merged by step 109；It is closed again using step 110 cleaning filing
Car data is crossed after and；Final frequent vehicle statistical result excessively is obtained eventually by step 111.
The merging that train number number is crossed by every trolley of preliminary screening and each bayonet, taxonomically finds out every trolley
Each bayonet cross train number number data, every trolley and its each bayonet cross vehicle number information uniquely determine.Root
According to required data cleansing rule, traversal filing merge after each bayonet set in every trolley cross vehicle number information,
The statistical data for frequently crossing vehicle can be obtained.For example, it is frequent cross vehicle preset requirement counted train number number less than/more than m, i.e.,
To cross train number number more than/less than the vehicle of m cross train number number information deletion, the frequent information of vehicles for crossing vehicle finally required with
And its train number number data are crossed in bayonet.
In the present embodiment, car data storage system is crossed based on distributed, received in big data platform distributed storage
On node according to preset after requiring to carry out distributed screening cross car data after, then carry out integration, statistics, and clean
Meet frequently the frequent of mistake vehicle predetermined threshold out and cross car data, not only can use the parallel computation mode of distributed system, also
It is able to use the mode that first primary dcreening operation remerges cleaning, promotes the frequent statistical efficiency for crossing vehicle of statistics.
Embodiment 2
As shown in Fig. 2, being the embodiment of the present invention 2 based on the frequent method for crossing vehicle of distributed statistics.In the present embodiment,
Provided with based on the specific method for carrying out data merging and cleaning in the frequent method for crossing vehicle of distributed statistics.Base in the present embodiment
In the frequent method for crossing vehicle of distributed statistics the following steps are included:
Step 201 frequently crosses vehicle statistical condition and generates that statistics is frequent to cross vehicle request according to presetting, and deposits to distribution
Each node of storage system sends the frequent vehicle of crossing of statistics and requests.
Step 202 receives each node using distributed service framework according to the frequent symbol crossing vehicle request and determining
The bayonet for closing preset bayonet information, information of vehicles and vehicle time requirement excessively crosses car data, and the bayonet is crossed vehicle number
It is saved according to by the format of bayonet information and vehicles identifications；Wherein, the vehicles identifications include: license plate number and mistake train number
Number.
Preferably, the bayonet crosses car data, further comprises: bayonet number, license plate number, body color, vehicle type
Number, vehicle running state and cross the vehicle time.
Step 203, give up each node according to it is described it is frequent cross vehicle request determine do not meet preset bayonet
The bayonet of information, information of vehicles and vehicle time excessively crosses car data.
The bayonet that step 204, traversal save crosses car data, and the every trolley for obtaining each bayonet crosses car data.
The car data of crossing of the identical bayonet traversed is merged into the same set by step 205.
Step 206, in each bayonet set, by same license plate number it is all cross train number numbers be added to obtain the license plate number
Code corresponds to vehicle in the train number number excessively of corresponding bayonet and saves.
The train number number excessively of every trolley in step 207, each bayonet of traversal, crosses vehicle frequency threshold value according to preset,
The car data of crossing that train number number does not meet threshold requirement was deleted, statistics obtains frequently crossing the bayonet information of vehicle, information of vehicles, crosses vehicle
Time and excessively train number number simultaneously save.
The present embodiment counts the frequent method for crossing vehicle based on distributed, according to preset requirement in rough estimates
Ineligible data are filtered, many and diverse car data treatment process excessively is eliminated, to reduce when carrying out integration statistics
Data volume, thus shorten and count the frequent operation time for crossing vehicle and calculating speed, while decreasing the frequent mistake of statistics
The cost of vehicle.
Embodiment 3
As shown in figure 3, for an optional tool based on the frequent method for crossing vehicle of distributed statistics described in the embodiment of the present invention 3
Body embodiment.The step of the present embodiment, is as follows:
Step 301, the preset bayonet information of setting, information of vehicles and cross vehicle time requirement are as follows: cross the vehicle time from
2016-03-01 numbers the information of vehicles for being 1,2,3 by bayonet to during 2016-03-03 are as follows: popular brand crosses car data
It is filtered, counts.
Step 302, acquisition meets the mistake that condition is preset in step 301 on the distributed node for crossing vehicle storage system
Car data.
Successively judge whether each car data excessively meets above three condition on each node, selection meets above-mentioned condition
It is required that cross car data, encounter do not meet it is any one in above three condition all give up to fall, and continue next cross vehicle number
According to traversal and judgement.
Step 303 judges whether there is the consistent car data excessively of vehicle license plate number in each bayonet data of selection,
And each train number number of crossing for crossing car data for finding out same vehicle license plate number merges preservation.It traverses in each bayonet data
All vehicles cross vehicle number information, after merging final each bayonet cross car data set according to vehicle license plate number guarantor
That stays each vehicle crosses train number number in the bayonet.
Wherein, specific steps include:
(1) data by previous node after preliminary screening and below node cross car data carry out traversal comparison.
If a certain bayonet information in the node of back is not present in crossing in car data for previous node, by the bayonet information and the card
The car data value of crossing of mouth is added in previous node.
(2) if there is also traverse some the bayonet information of previous node crossed in car data in node below
It crosses car data.If it, which is crossed in car data, identical " license plate number n ", crossing in car data for previous node is accordingly blocked
The corresponding train number numerical value of crossing of mouth is added with the corresponding train number numerical value of crossing for crossing corresponding bayonet in car data of node below, saves as phase
That answers vehicle crosses train number number；
(3) if some license plate number in car data of crossing in previous node is not present in node below, by institute
State previous node cross corresponding bayonet in car data it is corresponding cross train number numerical value and save as the vehicle cross train number in corresponding bayonet
Number.
(4) it so uses previous node and the data of other nodes merges below, completed until all nodes merge,
Finally obtained car data excessively is the car data excessively of every trolley in each bayonet.
Step 304 preset train number number threshold requirement to cross train number number not less than 4 times, then obtained after traversing merging
The car data excessively of every trolley in each bayonet obtained, rejected train number number less than 4 times and crosses car data.Specific steps include:
(1) first bayonet for crossing car data of every trolley is corresponding in each bayonet of acquisition crosses train number numerical value.It should
It crosses train number numerical value to be parsed, if a certain vehicle crosses train number number less than 4, by the mistake of its every trolley from each bayonet
It removes in car data, otherwise not operates.
After the corresponding each trolley of (2) first bayonets crosses train number numerical value traversal, if crossed in train number numerical value also
Corresponding data, then be not processed；Otherwise it rejects the bayonet each trolley corresponding with its and crosses train number numerical value.
(3) traverse every trolley in each bayonet crosses car data, crosses car data according to step to each bayonet of preservation
Suddenly (1) and (2) is handled, and finally obtains this frequent statistical data for crossing vehicle.
The frequent method for crossing vehicle is counted based on distributed according to described in the present embodiment, is first filtered out at data statistics initial stage
Conform to a predetermined condition requirement cross car data, then count each bayonet every trolley cross train number number after, using it is frequent cross vehicle it is pre-
The information for frequently crossing vehicle is selected and counted to fixed vehicle frequency threshold value of crossing, and in inquiry, statistic processes, the information of each vehicle is not
Omission is had, ensure that and count the frequent accuracy for crossing vehicle.
Embodiment 4
As shown in figure 4, for an optional reality based on the frequent system for crossing vehicle of distributed statistics disclosed in the present embodiment
Apply the structural schematic diagram of example.The system packet of bayonet vehicle search described in the present embodiment based on distributed full-text search system
It includes: processing module 401, sending module 402, receiving module 403, filing merging module 404 and statistical module 405, wherein
The processing module 401 connects with the sending module 402, receiving module 403 and filing 404 phase lotus root of merging module,
For according to preset frequently cross vehicle statistical condition generate statistics it is frequent cross vehicle request；
The sending module 402 connects with the 401 phase lotus root of processing module, for each section to distributed memory system
Point sends the frequent vehicle of crossing of statistics and requests.
The receiving module 403 connects with the 401 phase lotus root of processing module, for receiving each node according to described frequent
It crosses the bayonet for meeting preset bayonet information, information of vehicles and vehicle time requirement excessively that vehicle request determines and crosses car data,
And the bayonet is crossed into car data and is saved by the format of bayonet information and vehicles identifications；Wherein, the vehicles identifications include:
License plate number and excessively train number number.
The filing merging module 404 connects with the 401 phase lotus root of processing module, for traversing the bayonet mistake saved
Car data merges the car data excessively of each bayonet, counts the train number number excessively of every trolley in each bayonet data and saves.
The statistical module 405 connects with the 404 phase lotus root of filing merging module, for traversing every trolley in each bayonet
Cross train number number, according to it is preset cross vehicle frequency threshold value, deleted train number number do not meet threshold requirement cross car data,
Statistics obtains frequently crossing the bayonet information of vehicle, information of vehicles, spends the vehicle time and cross train number number and save.
Above-mentioned receiving module 403 is further used for giving up what each node was determined according to the frequent request of vehicle excessively
It does not meet preset bayonet information, information of vehicles and crosses the bayonet of vehicle time and cross car data.
The receiving module 403, is further also used to:
Met using distributed service framework (zookeeper) from the acquisition of each node of distributed memory system and is set in advance
Fixed bayonet information, information of vehicles and the bayonet of vehicle time requirement excessively crosses car data.
Distributed service framework (zookeeper) is the distributed application program coordination service of an open source, is Hadoop
Significant components, it is one and provides the software of Consistency service for Distributed Application, the function of providing include: configuring maintenance,
Domain name service, distributed synchronization, group service etc..
The filing merging module 404, is further used for:
The car data of crossing of the identical bayonet traversed is merged into the same set；
In each bayonet set, by same license plate number it is all cross train number numbers and be added to obtain the license plate number correspond to vehicle
It train number number and is saved in crossing for corresponding bayonet.
Wherein, the bayonet crosses car data and further comprises: bayonet number, license plate number, body color, vehicle model,
Vehicle running state crosses train number number and spends the vehicle time.
It counts frequent based on distribution described in the present embodiment and crosses vehicle and system, using the management of distributed memory system
Mechanism filters out ineligible data in rough estimates according to preset requirement, eliminates many and diverse car data excessively
Thus treatment process shortens to reduce the data volume when carrying out integration statistics and counts the frequent operation time for crossing vehicle
And calculating speed.
By above each embodiment it is found that of the invention existed based on the frequent method and system for crossing vehicle of distributed statistics
Beneficial effect be:
(1) of the present invention based on the frequent method and system for crossing vehicle of distributed statistics, the frequency based on big data platform
It is numerous cross vehicle statistical method, receive on the node of big data platform distributed storage carry out distributed arithmetic as a result, then again into
Row integration, statistics, big data platform can be established in a distributed manner on cheap business PC, and according to the big of data volume
The actual conditions such as small determine the size of distributed type assemblies, can store the data of magnanimity, have saved being made for the frequent vehicle excessively of statistics
Resource, and can use distributed type assemblies and concurrently car data excessively is inquired, is counted, improve the frequent vehicle excessively of statistics
Statistical efficiency.
(2) of the present invention based on the frequent method and system for crossing vehicle of distributed statistics, according to preset requirement
Ineligible data are filtered out in rough estimates, eliminate it is many and diverse cross car data treatment process, thus reduce into
Data volume when row integration statistics, thus shortens and counts the frequent operation time for crossing vehicle and calculating speed.
(3) of the present invention based on the frequent method and system for crossing vehicle of distributed statistics, it is first sieved at data statistics initial stage
Select the requirement that conforms to a predetermined condition cross car data, then count each bayonet every trolley cross train number number after, utilize frequent mistake
The scheduled vehicle frequency threshold value of crossing of vehicle is selected and counts the information for frequently crossing vehicle, in inquiry, statistic processes, the information of each vehicle
Omission is not had, be ensure that and is counted the frequent accuracy for crossing vehicle.
It should be understood by those skilled in the art that, the embodiment of the present invention can provide as method, apparatus or computer program
Product.Therefore, complete hardware embodiment, complete software embodiment or reality combining software and hardware aspects can be used in the present invention
Apply the form of example.Moreover, it wherein includes the computer of computer usable program code that the present invention, which can be used in one or more,
The computer program implemented in usable storage medium (including but not limited to magnetic disk storage, CD-ROM, optical memory etc.) produces
The form of product.
Several alternative embodiments of the invention have shown and described in above description, but as previously described, it should be understood that the present invention
Be not limited to forms disclosed herein, should not be regarded as an exclusion of other examples, and can be used for various other combinations,
Modification and environment, and the above teachings or related fields of technology or knowledge can be passed through within that scope of the inventive concept describe herein
It is modified.And changes and modifications made by those skilled in the art do not depart from the spirit and scope of the present invention, then it all should be in this hair
In the protection scope of bright appended claims.
Claims (2)
1. a kind of based on the frequent method for crossing vehicle of distributed statistics characterized by comprising
According to preset frequently cross vehicle statistical condition generate statistics it is frequent cross vehicle request；
The frequent vehicle of crossing of the statistics is sent to each node of distributed memory system to request；
Receive each node according to it is described it is frequent cross vehicle request determine meet preset bayonet information, information of vehicles and
Bayonet number, license plate number, body color, vehicle model, vehicle running state and the mistake vehicle time for crossing vehicle time requirement, give up
Each node according to it is described it is frequent cross vehicle request determine do not meet preset bayonet information, information of vehicles and cross vehicle when
Between bayonet number, license plate number, body color, vehicle model, vehicle running state and spend the vehicle time, and the bayonet is compiled
Number, license plate number, body color, vehicle model, vehicle running state and spend the vehicle time and press the lattice of bayonet information and vehicles identifications
Formula is saved, further are as follows:
Meet preset bayonet information, vehicle from the acquisition of each node of distributed memory system using distributed service framework
Information and bayonet number, license plate number, body color, vehicle model, vehicle running state and the mistake vehicle for crossing vehicle time requirement
Time, wherein the vehicles identifications include: license plate number and mistake train number number；
It traverses the bayonet number saved, license plate number, body color, vehicle model, vehicle running state and spends the vehicle time,
The car data excessively for merging each bayonet counts the train number number excessively of every trolley in each bayonet data and saves, further are as follows:
The car data of crossing of the identical bayonet traversed is merged into the same set, in each bayonet set, by same vehicle
Trade mark code it is all cross train number numbers and be added to obtain the license plate number correspond to vehicle in the mistake train number number of corresponding bayonet and saves；
The train number number excessively for traversing every trolley in each bayonet crosses vehicle frequency threshold value according to preset, deleted train number number
The car data of crossing of threshold requirement is not met, statistics obtains frequently crossing the bayonet information of vehicle, information of vehicles, spends the vehicle time and cross train number
It counts and saves.
2. a kind of based on the frequent system for crossing vehicle of distributed statistics characterized by comprising processing module, sending module, reception
Module, filing merging module and statistical module；Wherein,
The processing module, for according to preset frequently cross vehicle statistical condition generate statistics it is frequent cross vehicle request；
The sending module, for sending to each node of distributed memory system, statistics is frequent to cross vehicle request；
The receiving module requests what is determined to meet preset card for receiving each node according to the frequent vehicle of crossing
Message breath, information of vehicles and bayonet number, the license plate number, body color, vehicle model, vehicle driving shape of crossing vehicle time requirement
State and excessively vehicle time give up each node and are believed according to the preset bayonet that do not meet that the frequent request of vehicle excessively determines
Breath, the bayonet number of information of vehicles and vehicle time excessively, license plate number, body color, vehicle model, vehicle running state and mistake vehicle
Time, and the bayonet number, license plate number, body color, vehicle model, vehicle running state and vehicle time excessively are pressed into bayonet
The format of information and vehicles identifications is saved；Obtained using distributed service framework from each node of distributed memory system
Take meet preset bayonet information, information of vehicles and cross the bayonet number of vehicle time requirement, license plate number, body color,
Vehicle model, vehicle running state cross train number number and spend the vehicle time；Wherein, the vehicles identifications include: license plate number and mistake vehicle
Number；
The filing merging module, for traversing the bayonet number saved, license plate number, body color, vehicle model, vehicle
Driving status and the vehicle time is spent, merge each bayonet crosses car data, and count every trolley in each bayonet data crosses vehicle
Number simultaneously saves；The car data of crossing for the identical bayonet that will be traversed is merged into the same set, in each bayonet set,
By same license plate number it is all cross train number numbers be added to obtain the license plate number correspond to vehicle corresponding bayonet mistake train number number simultaneously
It saves；
The statistical module crosses train number number according to preset for traversing the train number number excessively of every trolley in each bayonet
Threshold value, deleted the car data of crossing that train number number does not meet threshold requirement, and statistics obtains frequently crossing the bayonet information of vehicle, vehicle letter
Breath spends the vehicle time and crosses train number number and save.
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| CN108022428B (en) * | 2016-11-02 | 2021-05-25 | 杭州海康威视***技术有限公司 | Vehicle identification method and device |
| CN107862867B (en) * | 2017-11-08 | 2019-08-27 | 泰华智慧产业集团股份有限公司 | The method and system for entering city vehicle analysis for the first time are carried out based on big data |
| CN107993444B (en) * | 2017-11-22 | 2021-02-02 | 紫光捷通科技股份有限公司 | Suspected vehicle identification method based on bayonet vehicle-passing big data analysis |
| CN107798142A (en) * | 2017-11-24 | 2018-03-13 | 泰华智慧产业集团股份有限公司 | The method and device of concealment vehicle is analyzed based on big data |
| CN110021161B (en) * | 2018-01-09 | 2021-12-21 | 株式会社日立制作所 | Traffic flow direction prediction method and system |
| CN110136452A (en) * | 2018-02-08 | 2019-08-16 | 杭州海康威视数字技术股份有限公司 | A kind of car statistics method and device |
| CN111368617B (en) * | 2019-07-31 | 2023-11-24 | 杭州海康威视***技术有限公司 | Vehicle access data processing method and device |
| CN110749335B (en) * | 2019-10-24 | 2021-05-04 | 成都路行通信息技术有限公司 | Method and system for calculating average mileage from owner to unit in target area |
| CN111199644B (en) * | 2020-01-06 | 2021-05-11 | 山东合天智汇信息技术有限公司 | Method and system for automatically fitting people and vehicles |
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| CN104750800A (en) * | 2014-11-13 | 2015-07-01 | 安徽四创电子股份有限公司 | Motor vehicle clustering method based on travel time characteristic |
| CN104616494B (en) * | 2014-12-23 | 2017-04-19 | 浙江宇视科技有限公司 | Method and device for recording and determining target object based on base station and block port |
| CN105447617A (en) * | 2015-11-06 | 2016-03-30 | 上海熙菱信息技术有限公司 | Vehicle track data analysis-based early-warning integrating method and system |
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-
2016
- 2016-04-28 CN CN201610274065.4A patent/CN105913656B/en active Active
Non-Patent Citations (1)
| Title |
|---|
| HBase在机动车缉查布控***中的应用;缪新顿 等;《中国交通信息化》;20140531;正文第123-125页 |
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