CN108241934A - Data query method and apparatus - Google Patents
Data query method and apparatus Download PDFInfo
- Publication number
- CN108241934A CN108241934A CN201611208000.6A CN201611208000A CN108241934A CN 108241934 A CN108241934 A CN 108241934A CN 201611208000 A CN201611208000 A CN 201611208000A CN 108241934 A CN108241934 A CN 108241934A
- Authority
- CN
- China
- Prior art keywords
- data
- operation data
- wide table
- library
- wide
- 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.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 42
- 230000002045 lasting effect Effects 0.000 claims abstract description 8
- 238000003860 storage Methods 0.000 claims description 27
- 230000014759 maintenance of location Effects 0.000 claims description 6
- PEDCQBHIVMGVHV-UHFFFAOYSA-N Glycerine Chemical compound OCC(O)CO PEDCQBHIVMGVHV-UHFFFAOYSA-N 0.000 claims description 4
- 238000013480 data collection Methods 0.000 claims description 4
- 230000006399 behavior Effects 0.000 claims description 3
- 238000004519 manufacturing process Methods 0.000 description 28
- 238000010586 diagram Methods 0.000 description 4
- 238000005516 engineering process Methods 0.000 description 3
- 241001269238 Data Species 0.000 description 2
- 241000406668 Loxodonta cyclotis Species 0.000 description 2
- 239000008187 granular material Substances 0.000 description 2
- 238000012544 monitoring process Methods 0.000 description 2
- 238000012545 processing Methods 0.000 description 2
- 230000002123 temporal effect Effects 0.000 description 2
- 230000006978 adaptation Effects 0.000 description 1
- 230000003044 adaptive effect Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 239000000470 constituent Substances 0.000 description 1
- 238000007796 conventional method Methods 0.000 description 1
- 238000013500 data storage Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 238000007726 management method Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000005498 polishing Methods 0.000 description 1
- 230000003252 repetitive effect Effects 0.000 description 1
- 238000005728 strengthening Methods 0.000 description 1
- 230000001502 supplementing effect Effects 0.000 description 1
- 239000002699 waste material Substances 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
- G06Q10/087—Inventory or stock management, e.g. order filling, procurement or balancing against orders
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/22—Indexing; Data structures therefor; Storage structures
- G06F16/2282—Tablespace storage structures; Management thereof
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/23—Updating
- G06F16/2365—Ensuring data consistency and integrity
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2453—Query optimisation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
- G06Q10/083—Shipping
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Economics (AREA)
- Physics & Mathematics (AREA)
- Entrepreneurship & Innovation (AREA)
- Operations Research (AREA)
- General Business, Economics & Management (AREA)
- Databases & Information Systems (AREA)
- Development Economics (AREA)
- Data Mining & Analysis (AREA)
- Tourism & Hospitality (AREA)
- Human Resources & Organizations (AREA)
- Marketing (AREA)
- General Engineering & Computer Science (AREA)
- Quality & Reliability (AREA)
- Strategic Management (AREA)
- Computational Linguistics (AREA)
- Computer Security & Cryptography (AREA)
- Accounting & Taxation (AREA)
- Finance (AREA)
- Software Systems (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
The disclosure provides a kind of data query method and apparatus.Data query method includes：Lasting to receive the operation data from multiple databases, the operation data includes multiple data elements of multiple data objects；It keeps in and handles the operation data, make each operation data value in the operation data that there are unique encodings；After all data elements for getting a data object, the one wide table into multiple wide tables adds a data record about the data object；The multiple wide table is stored so that displaying is inquired.The data query method that the disclosure provides can solve the problems, such as that multilist is related to query speed bottle-neck, improve inquiry velocity.
Description
Technical field
This disclosure relates to database technical field, in particular to a kind of data query method and apparatus.
Background technology
Logistic industry generates the logistics information of magnanimity daily, and therefore, effectively management becomes one with inquiring these logistics informations
Item necessity and urgent work.
In the prior art, the mode for inquiring logistics information generally includes to establish the monitoring being made of complicated SQL statement
Report, still, this mode can not be realized carries out multinode real time monitoring to logistics information data.In other inquiry logistics informations
Mode in, further include the mode based on the displaying of multiple database multi-list correlation inquiries+WEB page and develop data sheet.But
It, can be due to data volume to be checked in a manner that multiple databases carry out multilist correlation inquiry with increasing considerably for portfolio
It is excessive and lead to query timeout, bottleneck is encountered in inquiry velocity.Further, since in view of the stability of system, logistics company
Each operation system would generally be split, relevant logistics information data can also be stored in different databases or its
In his storage medium, existing data query method can not realize complexity in the case where this data aggregate degree is not high
Multilist, multiple database query composition.
Therefore, it is necessary to a kind of data query sides that quick search can be carried out to the magnanimity logistics information in complex data source
Method.
It should be noted that information is only used for strengthening the reason to the background of the disclosure disclosed in above-mentioned background technology part
Solution, therefore can include not forming the information to the prior art known to persons of ordinary skill in the art.
Invention content
The disclosure is designed to provide a kind of data query method and apparatus, for overcome at least to a certain extent by
One or more problems caused by the limitation of the relevant technologies and defect.
According to the disclosure in a first aspect, providing a kind of data query method.Including：
Lasting to receive the operation data from multiple databases, the operation data includes multiple numbers of multiple data objects
According to element；
It keeps in and handles the operation data, make each operation data value in the operation data that there are unique encodings；
After all data elements for getting a data object, one wide table into multiple wide tables add one about
The data record of the data object；
The multiple wide table is stored so that displaying is inquired.
In a kind of exemplary embodiment of the disclosure, the data object includes sending objects, the data element packet
Include dispatching case number (CN), package number, dispatching station name and operating time.
In a kind of exemplary embodiment of the disclosure, further include：
Wide table according to belonging to the source of the operation data judges the data object.
In a kind of exemplary embodiment of the disclosure, each operation data value made in the operation data has
Unique encodings include：
When multiple operation data values in the operation data are the same data element of same data object,
Unique encodings are set, and the multiple operation data value are recorded as according to the unique encodings for the multiple operation data value
The data element of the data object.
In a kind of exemplary embodiment of the disclosure, the multiple wide table of storage includes：In a manner that table is divided in a point library
The each wide table of storage.
In a kind of exemplary embodiment of the disclosure, including：By the addition month of the data record by the wide table
It is divided into multiple library storages.
In a kind of exemplary embodiment of the disclosure, in each library in the multiple library, by the data record
The addition date the wide table be divided into multiple sublists store.
According to the second aspect of the disclosure, a kind of data query arrangement is provided, including：
Data collection module, for persistently receiving the operation data from multiple databases, the operation data includes more
Multiple data elements of a data object；
Data temporary storage module for keeping in and handling the operation data, makes each operand in the operation data
There are unique encodings according to value；
Data add module, for when all data elements for getting a data object after, one into multiple wide tables
A wide table adds a data record about the data object；
Data memory module, for storing the multiple wide table so that displaying is inquired.
In a kind of exemplary embodiment of the disclosure, the data object includes sending objects, the data element packet
Include dispatching case number (CN), package number, dispatching station name and operating time.
In a kind of exemplary embodiment of the disclosure, the data add module is additionally operable to according to the operation data
Source judges the wide table belonging to the data object.
In a kind of exemplary embodiment of the disclosure, each operation data value made in the operation data has
Unique encodings include：
When multiple operation data values in the operation data are the same data element of same data object,
Unique encodings are set, and the multiple operation data value are recorded as according to the unique encodings for the multiple operation data value
The data element of the data object.
In a kind of exemplary embodiment of the disclosure, the data memory module includes：It is stored in a manner that table is divided in a point library
Each width table.
In a kind of exemplary embodiment of the disclosure, including：By the addition month of the data record by the wide table
It is divided into multiple library storages.
In a kind of exemplary embodiment of the disclosure, in each library in the multiple library, by the data record
The addition date the wide table be divided into multiple sublists store.
The data query method that the disclosure provides by receiving the data of multiple databases simultaneously, temporal data and to data
It is processed into line asynchronous to generate the high wide table of inquiry convenience, avoids and multilist correlation inquiry is carried out to mass data, overcome
The inquiry velocity bottleneck of the data of data source complexity.In addition, the mode for dividing table by using point library carries out most granule to wide table
The storage of degree is solved in the case where storing mass data, and inquiry velocity caused by single table inquiry data volume is excessive is slowly asked
Topic.
It should be understood that above general description and following detailed description are only exemplary and explanatory, not
The disclosure can be limited.
Description of the drawings
Attached drawing herein is incorporated into specification and forms the part of this specification, shows the implementation for meeting the disclosure
Example, and for explaining the principle of the disclosure together with specification.It should be evident that the accompanying drawings in the following description is only the disclosure
Some embodiments, for those of ordinary skill in the art, without creative efforts, can also basis
These attached drawings obtain other attached drawings.
Fig. 1 schematically shows a kind of flow chart of data query method in disclosure exemplary embodiment.
Fig. 2 schematically shows the work that data query method in disclosure exemplary embodiment inquires field for logistics information
Make schematic diagram.
Fig. 3 schematically shows a kind of block diagram of data query arrangement in disclosure exemplary embodiment.
Specific embodiment
Example embodiment is described more fully with reference to the drawings.However, example embodiment can be with a variety of shapes
Formula is implemented, and is not understood as limited to example set forth herein；On the contrary, these embodiments are provided so that the disclosure will more
Fully and completely, and by the design of example embodiment comprehensively it is communicated to those skilled in the art.Described feature, knot
Structure or characteristic can be in any suitable manner incorporated in one or more embodiments.In the following description, it provides perhaps
More details fully understand embodiment of the present disclosure so as to provide.It it will be appreciated, however, by one skilled in the art that can
One or more in the specific detail are omitted with technical solution of the disclosure or others side may be used
Method, constituent element, device, step etc..In other cases, be not shown in detail or describe known solution to avoid a presumptuous guest usurps the role of the host and
So that all aspects of this disclosure thicken.
In addition, attached drawing is only the schematic illustrations of the disclosure, identical reference numeral represents same or similar portion in figure
Point, thus repetition thereof will be omitted.Attached some block diagrams shown in figure are functional entitys, not necessarily necessary and object
The entity managed or be logically independent is corresponding.Software form may be used to realize these functional entitys or in one or more
These functional entitys are realized in hardware module or integrated circuit or in heterogeneous networks and/or processor device and/or microcontroller
These functional entitys are realized in device.
Disclosure example embodiment is described in detail below in conjunction with the accompanying drawings.
Fig. 1 schematically shows a kind of flow chart of data query method in disclosure exemplary embodiment.
With reference to figure 1, data query method 100 can include：
Step S102, lasting to receive the operation data from multiple databases, the operation data includes multiple data pair
Multiple data elements of elephant.
Step S104 keeps in and handles the operation data, has each operation data value in the operation data
Unique encodings.
Step S106, after all data elements for getting a data object, a wide table into multiple wide tables adds
Add a data record about the data object.
Step S108 stores the multiple wide table so that displaying is inquired.
The data query method that the disclosure provides by receiving the data of multiple databases simultaneously, temporal data and to data
It is processed into line asynchronous to generate the high wide table of inquiry convenience, avoids and multilist correlation inquiry is carried out to mass data, overcome
The inquiry velocity bottleneck of the data of data source complexity.In addition, the mode for dividing table by using point library carries out most granule to wide table
The storage of degree is solved in the case where storing mass data, and inquiry velocity caused by single table inquiry data volume is excessive is slowly asked
Topic.
Each step of data query method 100 is described in detail below.
Step S102, lasting to receive the operation data from multiple databases, the operation data includes multiple data pair
Multiple data elements of elephant.
In a kind of illustrative embodiments of the disclosure, data query method can be applied to inquire in logistics information and be led
Domain, at this point, since logistics information is related to multiple logistics systems and multiple logistics links, it can be by receiving each production system MQ
Message collection logistics data.MQ (message middleware, message-oriented middleware) message is a kind of message-oriented middleware
(MOM), it provides the communication channel based on queue between each application software, common MQ message include rabbitMQ, Kafka,
ActiveMQ etc..
It can be by the way that each production system asynchronous transmission MQ message when generating operation data be made to realize step S102.Due to
Each production system continuous service, and continue to be stored in operation data in the database of each production system subordinate, therefore, correspond to
The MQ message of the operation data of each database will be continuously transmitted with, and so as to transmit operation data, receiving terminal be made persistently to receive and is come
From the operation data of each database.
When this method is used in logistics enquiring field, above-mentioned data object can include sending objects, the number
Dispatching case number (CN), package number, the dispatching logistics informations such as station name and operating time are can include but is not limited to according to element.It is worth
One is mentioned that, the application field of this method is not limited to logistics information inquiry field, and those skilled in the art can be according to actual conditions
This method is applied in other data query fields.
Step S104 keeps in and handles the operation data, has each operation data value in the operation data
Unique encodings.
After the operation data for coming from each production system is got by collecting MQ message, it can be kept in by Redis
All operation datas, and these operation datas are handled.
In a kind of exemplary embodiment of the disclosure, above-mentioned processing procedure includes making each behaviour in the operation data
Make data value with unique encodings.Its detailed process can for example include：When multiple operation data values in the operation data
It is the multiple operation data value setting unique encodings when being the same data element of same data object, and according to
The multiple operation data value is recorded as the data element of the data object by the unique encodings.
Above-mentioned data, which uniquely change process, can enable the operation data from all production systems be recorded one by one, from
Without leading to data cover or loss because multiple production systems carry out same operation to same sending objects.It is for example, more
A production system can generate same sending objects multiple operations, this step can be encoded by combining production system, operation
The data elements such as time and sending objects coding are each operation setting unique encodings in above-mentioned multiple operations, so as to essence
Really record above-mentioned multiple operations.
Step S106, after all data elements for getting a data object, a wide table into multiple wide tables adds
Add a data record about the data object.
It is lasting acquisition operation data during, can continue judge a data object all data elements whether
By polishing.For example, when data object be sending objects when, can pre-set its required data element for dispatching case number (CN),
Package number, dispatching station name and operating time etc..When the above-mentioned required data element for judging a sending objects has had
It is standby, you can will to be added in a wide table about the information of this sending objects.
In a kind of exemplary embodiment of the disclosure, above-mentioned width table can be multiple, and each wide table can correspond to one
Production system, such as the wide table of pre-sorting can correspond to pre-sorting production system, for recording the behaviour generated during pre-sorting
Make data.At this point, the above-mentioned record of the interpolation data into wide table can include judging the number according to the source of the operation data
According to the wide table belonging to object.It, can will be about for example, when the dispatching case number (CN) of a sending objects derives from pre-sorting production system
The data record of the sending objects is added in the wide table of pre-sorting.
Step S108 stores the multiple wide table so that displaying is inquired.
Due to it is lasting reception MQ message, it is above-mentioned data record is added to wide table process be also it is lasting, it is above-mentioned multiple
Data in table can continue to increase.It is stored at this point it is possible to be updated after each data record is added and store wide table to rear end
Medium, using each wide table of storage as the data source of displaying inquiry.
In a kind of exemplary embodiment of the disclosure, storing multiple wide tables can include storing in a manner that table is divided in a point library often
A wide table.It for example, can be by the addition month of the data record the wide table being divided into multiple library storages, by the wide table of pre-sorting
In January data be stored as a library, February data are stored as another library etc..When judgement needs number to be added
During according to being recorded as new month, new library can be established so as to which new data record be added.In addition, in the multiple library
Each library in, the wide table can be divided into multiple sublists by the addition date of the data record and stored.For example, by 1
The operation data on the moon 1 is stored as sublist one, and it is second-class that the operation data of 2 days in January is stored as sublist.
Above-mentioned point of library divides the division rule of the wide table of table storage that can also include through major key strategy, major key+business major key plan
It slightly waits and a point library is carried out to wide table table is divided to store, the disclosure is not particularly limited this.Table is divided to store by carrying out a point library to wide table,
It can solve the problems, such as that single table storage inquiry data volume is excessive, effectively improve inquiry velocity.
The above method 100 is described in detail below by specific embodiment.
Fig. 2 is that work of the data query method 100 for logistics information inquiry field is shown in disclosure example embodiment
It is intended to.
With reference to figure 2, operation data can come from multiple physics production systems, such as pre-sorting production system, sorting production
System, outer single production system, terminal production system, transport production system and financial production system etc..Corresponding to above-mentioned production
System can generate multiple wide tables so that inquiry is shown.
It is illustrated for sorting production system below.In the operand that sorting production system will generate in production process
During according in storage to database, the MQ message about the operation data asynchronous can be sent out.
Sorting produced on-site carries out operation usually as unit of case, includes multiple packages in each case, is needed during examining goods
Operation of unpacking is carried out, is examined goods to each package.Since same package may be multiple by multiple sortation hubs acquisition operations
Sortation hubs correspond to package record operating time, and the package each can not be judged according only to package and operating time
Operation note is recorded by which sortation hubs.It therefore, can be by majority according to elements correlation for example " in package+sorting
The mode of heart number+operating time " to carry out unique encodings to each package operation note, is related to the packet to record one by one
The operation each time wrapped up in.When same sortation hubs are to the package repetitive operation, can using time for operating for the last time as
The operating time of this operation.
From fig. 2 it can be seen that for a production system, need to be associated with boxing_d tables (storage boxcode and
Packagecode), send_d tables (storage boxcode and sendcode) and send_m tables (storage sendcode and
Sitecode, operate_time) data just can determine that sitecode and packagecode, operate_time are determined only
One record.
In order to ensure the record uniqueness of wide table, the data by above three tables is needed to keep in Redis cachings, pending data
The uniqueness of record is confirmed after completion.The case number (CN) boxcode and package packagecode of wherein boxing_d tables storage are one
To more relationships, need to store set more in a pair, to be associated operation to case number (CN) and multiple packages.
For complete logistics system, each usual production system can preserve above-mentioned three tables, so for
Each production system can be determined by obtaining above-mentioned three tables to carry out data uniqueness.
In addition, due to produced on-site in order to keep processing speed that operation data can be respectively stored in different tables, it is raw
The time that production system generates operation data is different, in order to obtain data object institute data element in need, needs to operate
Data are kept in together, wait for after all data objects all completions needed for the data object again to the data of the data object into
Row operation.
Above procedure solve the problems, such as to ensure data record is unique and Supplementing Data after, can continuously by
Complete that there are the sort operation data uniquely recorded to be written in the storage medium of rear end, the sorting for forming continuous updating is wide
Table.
By storing data in the form of wide table so that do not needed to sorting when each link is inquired using traditional
Across multilist correlation inquiry, performance bottleneck caused by solving the problems, such as multilist correlation inquiry, improves inquiry velocity.In the disclosure
In other embodiment, the wide table generating process of other production systems is similar to above-mentioned sorting width table generating process, and the disclosure is in this
It repeats no more.
Since the wide table generated in the above process over time can be excessive there are data storage capacity, so as to cause list
The problem of wide table query performance is poor, therefore point library may be used, the mode of table is divided to store above-mentioned wide table.
Point library divide table strategy can there are many, such as major key strategy, major key+business major key strategy, date strategy etc.,
Those skilled in the art can be set according to embodiment of the present disclosure spiritual freedom.Due to logistic industry to the requirement of real-time of information compared with
Height usually need to only inquire the data on the same day, therefore, can carry out a point library to wide table according to date of operation and table is divided to store.
It is possible, firstly, to a point library storage is carried out to wide table according to calendar month.The naming rule for dividing library for example can be " business name
Claim abbreviation+_+year+moon ".By taking the wide table of sorting as an example, the name for sorting each point of library of wide table can be dms_201601, dms_
201602 or dms_201603 etc..
Secondly, in each point of library, table can be divided to store each point of library according to consecutive days.Table naming rule is divided for example can be
" Business Name abbreviation+_+year+moon+day ".By taking the wide table of sorting as an example, that sorts wide each point of library of table divides table that can be named as
sorting_20160101、sorting_20160102、sorting_20160103。
Point library divides table storage mode to be stored by the way that mass data is divided into multiple small data blocks, avoids inquiry
Inquiry is carried out to mass data to waste time, and improves search efficiency, it is real-time to daily magnanimity so as to meet logistic industry
The quick search demand of data.
Corresponding to above method embodiment, the disclosure also provides a kind of data query arrangement, can be used for performing above-mentioned side
Method embodiment.
Fig. 2 schematically shows a kind of block diagram of data query arrangement in disclosure exemplary embodiment.With reference to figure 2, number
It can include data collection module 202, data temporary storage module 204, data add module 206 and data according to inquiry unit 200
Memory module 208.
Data collection module 202 can be used for continuing to receive the operation data from multiple databases, the operation data
Multiple data elements including multiple data objects.
Data temporary storage module 204 can be used for temporary and handle the operation data, make each in the operation data
Operation data value has unique encodings.
Data add module 206 can be used for after all data elements for getting a data object, to multiple wide tables
In one wide table add a data record about the data object.
Data memory module 208 can be used for storing the multiple wide table so that displaying is inquired.
In a kind of exemplary embodiment of the disclosure, the data object includes sending objects, the data element packet
Include dispatching case number (CN), package number, dispatching station name and operating time.
In a kind of exemplary embodiment of the disclosure, the data add module is additionally operable to according to the operation data
Source judges the wide table belonging to the data object.
In a kind of exemplary embodiment of the disclosure, each operation data value made in the operation data has
Unique encodings include：
When multiple operation data values in the operation data are the same data element of same data object,
Unique encodings are set, and the multiple operation data value are recorded as according to the unique encodings for the multiple operation data value
The data element of the data object.
In a kind of exemplary embodiment of the disclosure, the data memory module includes：It is stored in a manner that table is divided in a point library
Each width table.
In a kind of exemplary embodiment of the disclosure, including：By the addition month of the data record by the wide table
It is divided into multiple library storages.
In a kind of exemplary embodiment of the disclosure, in each library in the multiple library, by the data record
The addition date the wide table be divided into multiple sublists store.
Since each function of device 200 has been described in detail in its corresponding embodiment of the method, the disclosure in this not
It repeats again.
Those skilled in the art will readily occur to the disclosure its after considering specification and putting into practice invention disclosed herein
Its embodiment.This application is intended to cover any variations, uses, or adaptations of the disclosure, these modifications, purposes or
Person's adaptive change follows the general principle of the disclosure and including the undocumented common knowledge in the art of the disclosure
Or conventional techniques.Description and embodiments are considered only as illustratively, and the true scope and spirit of the disclosure are by appended
Claim is pointed out.
Claims (14)
- A kind of 1. data query method, which is characterized in that including：Lasting to receive the operation data from multiple databases, the operation data includes multiple data elements of multiple data objects Element；It keeps in and handles the operation data, make each operation data value in the operation data that there are unique encodings；After all data elements for getting a data object, the one wide table into multiple wide tables adds one about described The data record of data object；The multiple wide table is stored so that displaying is inquired.
- 2. data query method according to claim 1, which is characterized in that the data object includes sending objects, institute It states data element and includes dispatching case number (CN), package number, dispatching station name and operating time.
- 3. data query method according to claim 1, which is characterized in that further include：Wide table according to belonging to the source of the operation data judges the data object.
- 4. data query method according to claim 1, which is characterized in that each behaviour made in the operation data Make data value with unique encodings to include：When multiple operation data values in the operation data are the same data element of same data object, for institute State multiple operation data values setting unique encodings, and described according to the unique encodings the multiple operation data value is recorded as The data element of data object.
- 5. data query method according to claim 1, which is characterized in that the multiple wide table of storage includes：With Point library divides table mode to store each wide table.
- 6. data query method according to claim 5, which is characterized in that including：By the addition moon of the data record The wide table is divided into multiple library storages by part.
- 7. data query method according to claim 6, which is characterized in that in each library in the multiple library, press The wide table is divided into multiple sublists and stored by the addition date of the data record.
- 8. a kind of data query arrangement, which is characterized in that including：Data collection module, for persistently receiving the operation data from multiple databases, the operation data includes multiple numbers According to multiple data elements of object；Data temporary storage module for keeping in and handling the operation data, makes each operation data value in the operation data With unique encodings；Data add module, for when all data elements for getting a data object after, one into multiple wide tables to be wide Table adds a data record about the data object；Data memory module, for storing the multiple wide table so that displaying is inquired.
- 9. data query arrangement according to claim 8, which is characterized in that the data object includes sending objects, institute It states data element and includes dispatching case number (CN), package number, dispatching station name and operating time.
- 10. data query arrangement according to claim 8, which is characterized in that the data add module is additionally operable to basis The source of the operation data judges the wide table belonging to the data object.
- 11. data query arrangement according to claim 8, which is characterized in that it is described make it is each in the operation data Operation data value includes with unique encodings：When multiple operation data values in the operation data are the same data element of same data object, for institute State multiple operation data values setting unique encodings, and described according to the unique encodings the multiple operation data value is recorded as The data element of data object.
- 12. data query arrangement according to claim 8, which is characterized in that the data memory module includes：To divide library Table mode is divided to store each wide table.
- 13. data query arrangement according to claim 12, which is characterized in that including：By the addition of the data record The wide table is divided into multiple library storages by month.
- 14. data query arrangement according to claim 13, which is characterized in that in each library in the multiple library, The wide table is divided into multiple sublists by the addition date of the data record to store.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201611208000.6A CN108241934B (en) | 2016-12-23 | 2016-12-23 | Data query method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201611208000.6A CN108241934B (en) | 2016-12-23 | 2016-12-23 | Data query method and device |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN108241934A true CN108241934A (en) | 2018-07-03 |
| CN108241934B CN108241934B (en) | 2021-02-26 |
Family
ID=62704107
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201611208000.6A Active CN108241934B (en) | 2016-12-23 | 2016-12-23 | Data query method and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108241934B (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110544162A (en) * | 2019-09-05 | 2019-12-06 | 广州酷旅旅行社有限公司 | Financial data processing method and device, computer equipment and storage medium |
| CN112395293A (en) * | 2020-11-27 | 2021-02-23 | 浙江诺诺网络科技有限公司 | Warehouse and table dividing method, warehouse and table dividing device, warehouse and table dividing equipment and storage medium |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103678665A (en) * | 2013-12-24 | 2014-03-26 | 焦点科技股份有限公司 | Heterogeneous large data integration method and system based on data warehouses |
| US20160012094A1 (en) * | 2014-07-08 | 2016-01-14 | Gordon GAUMNITZ | Faster access for compressed time series data: the bock index |
| CN105608210A (en) * | 2015-12-29 | 2016-05-25 | 北京京东尚科信息技术有限公司 | Data storage method and device |
| CN106033473A (en) * | 2015-03-20 | 2016-10-19 | 阿里巴巴集团控股有限公司 | Data processing method and device |
-
2016
- 2016-12-23 CN CN201611208000.6A patent/CN108241934B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103678665A (en) * | 2013-12-24 | 2014-03-26 | 焦点科技股份有限公司 | Heterogeneous large data integration method and system based on data warehouses |
| US20160012094A1 (en) * | 2014-07-08 | 2016-01-14 | Gordon GAUMNITZ | Faster access for compressed time series data: the bock index |
| CN106033473A (en) * | 2015-03-20 | 2016-10-19 | 阿里巴巴集团控股有限公司 | Data processing method and device |
| CN105608210A (en) * | 2015-12-29 | 2016-05-25 | 北京京东尚科信息技术有限公司 | Data storage method and device |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110544162A (en) * | 2019-09-05 | 2019-12-06 | 广州酷旅旅行社有限公司 | Financial data processing method and device, computer equipment and storage medium |
| CN112395293A (en) * | 2020-11-27 | 2021-02-23 | 浙江诺诺网络科技有限公司 | Warehouse and table dividing method, warehouse and table dividing device, warehouse and table dividing equipment and storage medium |
| CN112395293B (en) * | 2020-11-27 | 2024-03-01 | 浙江诺诺网络科技有限公司 | Database and table dividing method, database and table dividing device, database and table dividing equipment and storage medium |
Also Published As
| Publication number | Publication date |
|---|---|
| CN108241934B (en) | 2021-02-26 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US7099891B2 (en) | Method for allowing simple interoperation between backend database systems | |
| US7895359B2 (en) | System and method for message processing and routing | |
| JP5290271B2 (en) | Method and apparatus for performing channel tree operations | |
| CN101065947B (en) | Web service registry and method of operation | |
| US5202977A (en) | Edi translation system using plurality of communication processes and de-enveloping procedure corresponding to transmitted communication process | |
| US7890955B2 (en) | Policy based message aggregation framework | |
| CN109254982A (en) | A kind of stream data processing method, system, device and computer readable storage medium | |
| CN108446335B (en) | Heterogeneous system data extraction and unified external data exchange method based on database | |
| CN109375992A (en) | A kind of resource regulating method and device | |
| US7444596B1 (en) | Use of template messages to optimize a software messaging system | |
| CN108769099A (en) | A kind of implementation method of the message duplicate removal of message-oriented middleware | |
| CN104429046A (en) | Scaling redundancy elimination middleboxes | |
| CN102724307A (en) | Information fusion engine and information fusion method for Internet of Things | |
| CN104615684B (en) | A kind of mass data communication concurrent processing method and system | |
| CN108241934A (en) | Data query method and apparatus | |
| CN101068237B (en) | Data access system and data access method | |
| CN107644017A (en) | The querying method and device of journal file | |
| CN114710571A (en) | Data packet processing system | |
| KR950001526A (en) | Document processing method | |
| CN109145092B (en) | Database updating and intelligent question and answer management method, device and equipment | |
| CN101510293A (en) | Method for transmitting securities market indent queue data | |
| CN102655480A (en) | Similar mail handling system and method | |
| CN112668969B (en) | User tag processing method, system, electronic device and storage medium | |
| CN101814071A (en) | Method and device for realizing data exchange between system and data source | |
| CN101382959A (en) | Multimedia resource acquisition method, apparatus and system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |