CN107609130A - A kind of method and server for selecting data query engine - Google Patents
A kind of method and server for selecting data query engine Download PDFInfo
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- CN107609130A CN107609130A CN201710840667.6A CN201710840667A CN107609130A CN 107609130 A CN107609130 A CN 107609130A CN 201710840667 A CN201710840667 A CN 201710840667A CN 107609130 A CN107609130 A CN 107609130A
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Abstract
The embodiment of the present invention provides a kind of method and server for selecting data query engine, and methods described includes：Obtain data inquiry request and perform the running state information of the apparatus assembly of User behavior；The data inquiry request is parsed, to obtain the data table information and User behavior information needed for inquiry；Obtain target data amount corresponding to each data query engine performing data inquiry；The running state information, the data table information, the User behavior information and the target data amount are subjected to vectorization, to obtain numerical value vector；Computation model is preset according to the numerical value vector sum, obtains score value corresponding to each data query engine, and target data query engine is determined according to the score value.The server performs the above method.The method and server of selection data query engine provided in an embodiment of the present invention, by reasonably selecting data query engine, so as to improve efficiency data query and stability.
Description
Technical field
The present embodiments relate to technical field of data processing, and in particular to it is a kind of select data query engine method and
Server.
Background technology
In big data field, usual enterprise has all established enterprise-level database.The mainstream data of sql like language is supported to look at present
Asking engine has Hive, and Hive inquiries are stable, but search efficiency is low.Presto, the distributed SQL query engine increased income, is carried
Efficiency is risen, but stability is not high, it is generally the case that enterprise-level database there are a variety of data query engines, by experienced
Engineer carries out data query according to a kind of different data query task choosing data query engines therein, but by artificial
Data query engine is selected highly dependent upon artificial experience, and often occurs to lead because the selection of data query engine is unreasonable
A series of problems of cause, such as：Search efficiency response speed is slow etc..
Therefore, how data query engine is reasonably selected, so as to improve efficiency data query and stability, turning into need
Solve the problems, such as.
The content of the invention
The problem of existing for prior art, the embodiment of the present invention provide a kind of method and clothes for selecting data query engine
Business device.
In a first aspect, the embodiment of the present invention provides a kind of method for selecting data query engine, methods described includes：
Obtain data inquiry request and perform the running state information of the apparatus assembly of User behavior；
The data inquiry request is parsed, to obtain the data table information and User behavior information needed for inquiry；
Obtain target data amount corresponding to each data query engine performing data inquiry；
The running state information, the data table information, the User behavior information and the target data amount are entered
Row vector, to obtain numerical value vector；
Computation model is preset according to the numerical value vector sum, obtains score value corresponding to each data query engine, and according to
The score value determines target data query engine, wherein, the response speed of the score value reflection data query.
Second aspect, the embodiment of the present invention provide a kind of server for selecting data query engine, and the server includes：
First acquisition module, the running status letter of the apparatus assembly for obtaining data inquiry request and execution User behavior
Breath；
Parsing module, for parsing the data inquiry request, gone with obtaining the data table information needed for inquiry and inquiring about
For information；
Second acquisition module, for obtaining target data amount corresponding to each data query engine performing data inquiry；
3rd acquisition module, for by the running state information, the data table information, the User behavior information and
The target data amount carries out vectorization, to obtain numerical value vector；
Determining module, for presetting computation model according to the numerical value vector sum, it is corresponding to obtain each data query engine
Score value, and target data query engine is determined according to the score value, wherein, the response speed of the score value reflection data query
Degree.
The third aspect, the embodiment of the present invention provide the server of another selection data query engine, including：Processor,
Memory and bus, wherein,
The processor and the memory complete mutual communication by the bus；
The memory storage has and by the programmed instruction of the computing device, the processor described program can be called to refer to
Order is able to carry out following method：
Obtain data inquiry request and perform the running state information of the apparatus assembly of User behavior；
The data inquiry request is parsed, to obtain the data table information and User behavior information needed for inquiry；
Obtain target data amount corresponding to each data query engine performing data inquiry；
The running state information, the data table information, the User behavior information and the target data amount are entered
Row vector, to obtain numerical value vector；
Computation model is preset according to the numerical value vector sum, obtains score value corresponding to each data query engine, and according to
The score value determines target data query engine, wherein, the response speed of the score value reflection data query.
Fourth aspect, the embodiment of the present invention provide a kind of non-transient computer readable storage medium storing program for executing, including：
The non-transient computer readable storage medium storing program for executing stores computer instruction, and the computer instruction makes the computer
Perform following method：
Obtain data inquiry request and perform the running state information of the apparatus assembly of User behavior；
The data inquiry request is parsed, to obtain the data table information and User behavior information needed for inquiry；
Obtain target data amount corresponding to each data query engine performing data inquiry；
The running state information, the data table information, the User behavior information and the target data amount are entered
Row vector, to obtain numerical value vector；
Computation model is preset according to the numerical value vector sum, obtains score value corresponding to each data query engine, and according to
The score value determines target data query engine, wherein, the response speed of the score value reflection data query.
The method and server of selection data query engine provided in an embodiment of the present invention, by reasonably selecting data to look into
Engine is ask, so as to improve efficiency data query and stability.
Brief description of the drawings
In order to illustrate more clearly about the embodiment of the present invention or technical scheme of the prior art, below will be to embodiment or existing
There is the required accompanying drawing used in technology description to be briefly described, it should be apparent that, drawings in the following description are this hairs
Some bright embodiments, for those of ordinary skill in the art, on the premise of not paying creative work, can be with root
Other accompanying drawings are obtained according to these accompanying drawings.
Fig. 1 is the method flow schematic diagram that the embodiment of the present invention selects data query engine；
Fig. 2 is the server architecture schematic diagram that the embodiment of the present invention selects data query engine；
Fig. 3 is server entity structural representation provided in an embodiment of the present invention.
Embodiment
To make the purpose, technical scheme and advantage of the embodiment of the present invention clearer, below in conjunction with the embodiment of the present invention
In accompanying drawing, the technical scheme in the embodiment of the present invention is clearly and completely described, it is clear that described embodiment is
Part of the embodiment of the present invention, rather than whole embodiments.Based on the embodiment in the present invention, those of ordinary skill in the art
The every other embodiment obtained under the premise of creative work is not made, belongs to the scope of protection of the invention.
Fig. 1 is the method flow schematic diagram that the embodiment of the present invention selects data query engine, as shown in figure 1, the present invention is real
The method for applying a kind of selection data query engine of example offer, comprises the following steps：
S1：Obtain data inquiry request and perform the running state information of the apparatus assembly of User behavior.
Specifically, server obtains data inquiry request and performs the running state information of the apparatus assembly of User behavior.
The equipment for performing User behavior can be the server, and apparatus assembly can include CPU, internal memory, the I/O of the server.I/O
(input/output), i.e. input/output end port, for handling input/output information.Running state information can include above-mentioned
CPU running state information, the running state information of internal memory, I/O running state information in equipment, above-mentioned set can also be included
Standby network load state, the network quality of equipment can be effectively reflected according to network load state.For above-mentioned equipment
The running state information of component and apparatus assembly is not especially limited.
S2：The data inquiry request is parsed, to obtain the data table information and User behavior information needed for inquiry.
Specifically, server parses the data inquiry request, gone with obtaining the data table information needed for inquiry and inquiry
For information.Parsing data inquiry request can include：Syntactic analysis is made to data inquiry request, to obtain the data needed for inquiry
Table information；Semantic analysis is made to data inquiry request, to obtain the User behavior information needed for inquiry.Data table information therein
The data row in data form and the data form can be included, but be not especially limited；User behavior information therein can be with
Including data connection (JOIN), packet (GROUP BY) and data sorting (ORDER BY), but it is not especially limited.
S3：Obtain target data amount corresponding to each data query engine performing data inquiry.
Specifically, server obtains target data amount corresponding to each data query engine performing data inquiry.Generally enterprise
Database in industry includes a variety of data query engines, and therein one is artificially specified when carrying out different data query tasks
Kind data query engine, the data query engine specified by this complete this data query task.Data query engine can wrap
Include Hive (Tool for Data Warehouse based on Hadoop), Presto (being the distributed SQL an increased income query engine) etc..
Target data amount can be the scan data volume needed for each data query engine execution User behavior；Generally for raising data
After the efficiency of inquiry can use index, above-mentioned target data amount to can also be the data rejected in scan data volume using index
Remaining scan data volume.It is illustrated below：The scan data volume that data query engine Hive performs needed for User behavior is 1
Ten thousand, then 10,000 data is target data amount, also a kind of situation：If there is the use of 4,000 datas in 10,000 data
Index is (i.e.：Data using index are 4,000), then target data amount (actual scanning data volume) is 10,000-4 thousand=6,000.
S4：By the running state information, the data table information, the User behavior information and the target data amount
Vectorization is carried out, to obtain numerical value vector.
Specifically, server is by the running state information, the data table information, the User behavior information and described
Target data amount carries out vectorization, to obtain numerical value vector.It is illustrated below：
Numerical value vector X={ 0.5；0.6；0.3；0.3；10002；10003；20005；1；3；010000}
First four therein correspond to CPU, internal memory, I/O running state information and network load state respectively, respectively
Represent that the resources that use of CPU account for the resource that the 50% of total resources, internal memory uses and account for the resource that the 60% of total resources, I/O is used to account for
Total resources 30%, network load account for the 30% of ultimate load；It is middle three 10002；10003；20005 can be by data
What the data row conversion in list and data form came, it is described as follows that (10003 and 20005 is similarly no longer superfluous exemplified by 10002
State)：The second column data row in data form 001 are designated as 001-002；10002 can be converted to, conversion method can be according to reality
Border situation independently defines." 1 (being predefined as data connection behavior) " corresponding to 8th and " 3 (are predefined as corresponding to the 9th
Data sorting behavior) " the above-mentioned data form of the 5th-the seven (including data row) can be corresponding in turn to, i.e., to the 5th
Position and the 6th advanced row data of data form (including data arrange) connect, then after data are connected data form (including
Data arrange) carry out data sorting with the data form of the 7th (including data arrange).First " 0 " in tenth " 010000 "
It can represent, using scan data volume as target data amount, can represent actual scanning data volume if first is " 1 "
As target data amount, " 010000 " is integrally represented using scan data volume as target data amount, and the target data amount is 1
Ten thousand.It should be noted that：Above-mentioned numerical value vector X part vector element can be exemplified below with default：
Numerical value vector X={ 0.5；[]；0.3；0.3；10002；10003；20005；1；3；010000}
I.e.：Deputy internal memory running state information is default.
S5：Computation model is preset according to the numerical value vector sum, obtains score value corresponding to each data query engine, and root
Target data query engine is determined according to the score value, wherein, the response speed of the score value reflection data query.
Specifically, server presets computation model according to the numerical value vector sum, it is corresponding to obtain each data query engine
Score value, and target data query engine is determined according to the score value, wherein, the response speed of the score value reflection data query
Degree.Default computation model can be logistic regression algorithm, and logistic regression algorithm is this area ripe algorithm, and no longer citing is discussed.
Here default computation model is after learning training, and specific learning training is this area maturation method, is no longer illustrated
Discuss.Determining the mode of target data query engine can be：Selected in score value corresponding to each data query engine maximum
Data query engine is as target data query engine corresponding to score value.
The method of selection data query engine provided in an embodiment of the present invention, by reasonably selecting data query engine,
So as to improve efficiency data query and stability.
On the basis of above-described embodiment, the target data amount includes：
Each data query engine performs the scan data volume needed for User behavior.
Specifically, the target data amount in server includes：Each data query engine is performed needed for User behavior
Scan data volume.Above-described embodiment is can refer to, is repeated no more.
And/or
Each data query engine performs the actual scanning data volume needed for User behavior, wherein, the actual scanning number
It is to be rejected in scan data volume using remaining scan data volume after the data indexed according to amount.
Specifically, the target data amount in server includes：Each data query engine is performed needed for User behavior
Actual scanning data volume, wherein, the actual scanning data volume in scan data volume reject using index data after
Remaining scan data volume.Above-described embodiment is can refer to, is repeated no more.
The method of selection data query engine provided in an embodiment of the present invention, by reasonably determining target data amount, has
Help preferably select data query engine, so as to improve efficiency data query and stability.
It is described and target data query engine is determined according to the score value on the basis of above-described embodiment, including：
Data query engine corresponding to maximum score value is selected in the score value as target data query engine.
Specifically, server data query engine corresponding to maximum score value is selected in the score value as number of targets it is investigated that
Ask engine.Above-described embodiment is can refer to, is repeated no more.
The method of selection data query engine provided in an embodiment of the present invention, by selecting data corresponding to maximum score value to look into
Engine is ask as target data query engine, so as to reasonably select data query engine, further improves efficiency data query
And stability.
On the basis of above-described embodiment, the default computation model is logistic regression algorithm.
Specifically, the default computation model in server is logistic regression algorithm.Above-described embodiment is can refer to, no longer
Repeat.
The method of selection data query engine provided in an embodiment of the present invention, is returned by electing default computation model as logic
Reduction method, so as to reasonably select data query engine, further improve efficiency data query and stability.
On the basis of above-described embodiment, the apparatus assembly includes：
CPU, internal memory, I/O, correspondingly；The running state information includes the CPU, the internal memory, I/O difference
Corresponding running state information and network load state.
Specifically, the apparatus assembly in server includes：
CPU, internal memory, I/O, correspondingly；The running state information includes the CPU, the internal memory, I/O difference
Corresponding running state information and network load state.Above-described embodiment is can refer to, is repeated no more.
The method of selection data query engine provided in an embodiment of the present invention, by the operation for obtaining CPU, internal memory, I/O etc.
Status information, can be from more fully angle selection data query engine, so as to improve efficiency data query and stability.
On the basis of above-described embodiment, the User behavior information includes：
Data connection, packet and data sorting.
Specifically, the User behavior information in server includes：
Data connection, packet and data sorting.Above-described embodiment is can refer to, is repeated no more.
It is provided in an embodiment of the present invention selection data query engine method, by obtain data connect, packet and
The User behavior information such as data sorting, can be from more fully angle selection data query engine, so as to improve data query effect
Rate and stability.
On the basis of above-described embodiment, the data table information includes：
Data row in data form and the data form.
Specifically, the data table information in server includes：
Data row in data form and the data form.Above-described embodiment is can refer to, is repeated no more.
The method of selection data query engine provided in an embodiment of the present invention, includes data form and tables of data by obtaining
The data table informations such as the data row in list, can be from more fully angle selection data query engine, so as to improve data query
Efficiency and stability.
Fig. 2 is the server architecture schematic diagram that the embodiment of the present invention selects data query engine, as shown in Fig. 2 of the invention
Embodiment provides a kind of server for selecting data query engine, including the first acquisition module 1, parsing module 2, second obtain
Module 3, the 3rd acquisition module 4 and determining module 5, wherein：
First acquisition module 1 is used for the running status letter for the apparatus assembly for obtaining data inquiry request and performing User behavior
Breath；Parsing module 2 is used to parse the data inquiry request, to obtain the data table information and User behavior letter needed for inquiry
Breath；Second acquisition module 3 is used to obtain target data amount corresponding to each data query engine performing data inquiry；3rd obtains
Module 4 is used to enter the running state information, the data table information, the User behavior information and the target data amount
Row vector, to obtain numerical value vector；Determining module 5 is used to preset computation model according to the numerical value vector sum, obtains each
Score value corresponding to data query engine, and target data query engine is determined according to the score value, wherein, the score value reflects number
It is investigated that the response speed ask.
Specifically, the first acquisition module 1 is used for the fortune for the apparatus assembly for obtaining data inquiry request and performing User behavior
Row status information；Parsing module 2 is used to parse the data inquiry request, to obtain data table information and the inquiry needed for inquiry
Behavioural information；Second acquisition module 3 is used to obtain target data amount corresponding to each data query engine performing data inquiry；The
Three acquisition modules 4 are used for the running state information, the data table information, the User behavior information and the number of targets
Vectorization is carried out according to amount, to obtain numerical value vector；Determining module 5 is used to preset computation model according to the numerical value vector sum, obtains
Score value corresponding to each data query engine is taken, and target data query engine is determined according to the score value, wherein, the score value
Reflect the response speed of data query.
The server of selection data query engine provided in an embodiment of the present invention, by reasonably selecting data query to draw
Hold up, so as to improve efficiency data query and stability.
The service implement body of selection data query engine provided in an embodiment of the present invention can be used for performing above-mentioned each method
The handling process of embodiment, its function will not be repeated here, and be referred to the detailed description of above method embodiment.
Fig. 3 is server entity structural representation provided in an embodiment of the present invention, as shown in figure 3, the server includes：
Processor (processor) 301, memory (memory) 302 and bus 303；
Wherein, the processor 301, memory 302 complete mutual communication by bus 303；
The processor 301 is used to call the programmed instruction in the memory 302, to perform above-mentioned each method embodiment
The method provided, such as including：Obtain data inquiry request and perform the running state information of the apparatus assembly of User behavior；
The data inquiry request is parsed, to obtain the data table information and User behavior information needed for inquiry；Each data are obtained to look into
Ask target data amount corresponding to engine performing data inquiry；By the running state information, the data table information, the inquiry
Behavioural information and the target data amount carry out vectorization, to obtain numerical value vector；Calculated according to the numerical value vector sum is default
Model, score value corresponding to each data query engine is obtained, and target data query engine is determined according to the score value, wherein,
The response speed of the score value reflection data query.
The present embodiment discloses a kind of computer program product, and the computer program product includes being stored in non-transient calculating
Computer program on machine readable storage medium storing program for executing, the computer program include programmed instruction, when described program instruction is calculated
When machine performs, computer is able to carry out the method that above-mentioned each method embodiment is provided, such as including：Obtain data inquiry request
With the running state information of the apparatus assembly of execution User behavior；The data inquiry request is parsed, to obtain needed for inquiry
Data table information and User behavior information；Obtain target data amount corresponding to each data query engine performing data inquiry；Will
The running state information, the data table information, the User behavior information and the target data amount carry out vectorization, with
Obtain numerical value vector；Computation model is preset according to the numerical value vector sum, obtains score value corresponding to each data query engine, and
Target data query engine is determined according to the score value, wherein, the response speed of the score value reflection data query.
The present embodiment provides a kind of non-transient computer readable storage medium storing program for executing, the non-transient computer readable storage medium storing program for executing
Computer instruction is stored, the computer instruction makes the computer perform the method that above-mentioned each method embodiment is provided, example
Such as include：Obtain data inquiry request and perform the running state information of the apparatus assembly of User behavior；The data are parsed to look into
Request is ask, to obtain the data table information and User behavior information needed for inquiry；Obtain each data query engine performing data
Target data amount corresponding to inquiry；By the running state information, the data table information, the User behavior information and described
Target data amount carries out vectorization, to obtain numerical value vector；Computation model is preset according to the numerical value vector sum, obtained per number
Target data query engine is determined according to score value corresponding to query engine, and according to the score value, wherein, the score value reflects data
The response speed of inquiry.
One of ordinary skill in the art will appreciate that：Realizing all or part of step of above method embodiment can pass through
Programmed instruction related hardware is completed, and foregoing program can be stored in a computer read/write memory medium, the program
Upon execution, the step of execution includes above method embodiment；And foregoing storage medium includes：ROM, RAM, magnetic disc or light
Disk etc. is various can be with the medium of store program codes.
The embodiments such as server described above are only schematical, wherein the list illustrated as separating component
Member can be or may not be physically separate, can be as the part that unit is shown or may not be physics
Unit, you can with positioned at a place, or can also be distributed on multiple NEs.It can select according to the actual needs
Some or all of module therein realizes the purpose of this embodiment scheme.Those of ordinary skill in the art are not paying creation
In the case of the work of property, you can to understand and implement.
Through the above description of the embodiments, those skilled in the art can be understood that each embodiment can
Realized by the mode of software plus required general hardware platform, naturally it is also possible to pass through hardware.Based on such understanding, on
The part that technical scheme substantially in other words contributes to prior art is stated to embody in the form of software product, should
Computer software product can store in a computer-readable storage medium, such as ROM/RAM, magnetic disc, CD, including some fingers
Make to cause a computer equipment (can be personal computer, server, or network equipment etc.) to perform each implementation
Method described in some parts of example or embodiment.
Finally it should be noted that：Various embodiments above is rather than right only illustrating the technical scheme of embodiments of the invention
It is limited；Although embodiments of the invention are described in detail with reference to foregoing embodiments, the ordinary skill of this area
Personnel should be understood：It can still modify to the technical scheme described in foregoing embodiments, or to which part
Or all technical characteristic carries out equivalent substitution；And these modifications or replacement, do not make the essence disengaging of appropriate technical solution
The scope of each embodiment technical scheme of embodiments of the invention.
Claims (10)
- A kind of 1. method for selecting data query engine, it is characterised in that including：Obtain data inquiry request and perform the running state information of the apparatus assembly of User behavior；The data inquiry request is parsed, to obtain the data table information and User behavior information needed for inquiry；Obtain target data amount corresponding to each data query engine performing data inquiry；By the running state information, the data table information, the User behavior information and the target data amount carry out to Quantify, to obtain numerical value vector；Computation model is preset according to the numerical value vector sum, obtains score value corresponding to each data query engine, and according to described Score value determines target data query engine, wherein, the response speed of the score value reflection data query.
- 2. according to the method for claim 1, it is characterised in that the target data amount includes：Each data query engine performs the scan data volume needed for User behavior；And/orEach data query engine performs the actual scanning data volume needed for User behavior, wherein, the actual scanning data volume To reject remaining scan data volume after the data using index in scan data volume.
- 3. method according to claim 1 or 2, it is characterised in that it is described and number of targets is determined according to the score value it is investigated that Engine is ask, including：Data query engine corresponding to maximum score value is selected in the score value as target data query engine.
- 4. method according to claim 1 or 2, it is characterised in that the default computation model is logistic regression algorithm.
- 5. method according to claim 1 or 2, it is characterised in that the apparatus assembly includes：CPU, internal memory, I/O, correspondingly；The running state information includes the CPU, the internal memory, the I/O and corresponded to respectively Running state information and network load state.
- 6. method according to claim 1 or 2, it is characterised in that the User behavior information includes：Data connection, packet and data sorting.
- 7. method according to claim 1 or 2, it is characterised in that the data table information includes：Data row in data form and the data form.
- A kind of 8. server for selecting data query engine, it is characterised in that including：First acquisition module, the running state information of the apparatus assembly for obtaining data inquiry request and execution User behavior；Parsing module, for parsing the data inquiry request, to obtain the data table information and User behavior letter needed for inquiry Breath；Second acquisition module, for obtaining target data amount corresponding to each data query engine performing data inquiry；3rd acquisition module, for by the running state information, the data table information, the User behavior information and described Target data amount carries out vectorization, to obtain numerical value vector；Determining module, for presetting computation model according to the numerical value vector sum, obtain and divide corresponding to each data query engine Value, and target data query engine is determined according to the score value, wherein, the response speed of the score value reflection data query.
- A kind of 9. server for selecting data query engine, it is characterised in that including：Processor, memory and bus, wherein,The processor and the memory complete mutual communication by the bus；The memory storage has can be by the programmed instruction of the computing device, and the processor calls described program instruction energy Enough perform the method as described in claim 1 to 7 is any.
- 10. a kind of non-transient computer readable storage medium storing program for executing, it is characterised in that the non-transient computer readable storage medium storing program for executing is deposited Computer instruction is stored up, the computer instruction makes the computer perform the method as described in claim 1 to 7 is any.
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| CN108363819A (en) * | 2018-03-23 | 2018-08-03 | 联想(北京)有限公司 | Query engine matching method, device, server group and readable storage medium storing program for executing |
| CN108549683A (en) * | 2018-04-03 | 2018-09-18 | 联想(北京)有限公司 | data query method and system |
| CN109033123A (en) * | 2018-05-31 | 2018-12-18 | 康键信息技术（深圳）有限公司 | Querying method, device, computer equipment and storage medium based on big data |
| CN109783498A (en) * | 2019-01-17 | 2019-05-21 | 北京三快在线科技有限公司 | Data processing method and device, electronic equipment, storage medium |
| CN110163460A (en) * | 2018-03-30 | 2019-08-23 | 腾讯科技（深圳）有限公司 | A kind of method and apparatus determined using score value |
| CN110807145A (en) * | 2018-07-20 | 2020-02-18 | 中兴通讯股份有限公司 | Query engine acquisition method, device and computer-readable storage medium |
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| CN111159229A (en) * | 2019-12-31 | 2020-05-15 | 北京奇艺世纪科技有限公司 | Data query method and device |
| CN111639078A (en) * | 2020-05-25 | 2020-09-08 | 北京百度网讯科技有限公司 | Data query method and device, electronic equipment and readable storage medium |
| CN111709647A (en) * | 2020-06-18 | 2020-09-25 | 辽宁振兴银行股份有限公司 | Data source dynamic management method based on policy engine control |
| CN111723112A (en) * | 2020-06-11 | 2020-09-29 | 咪咕文化科技有限公司 | Data task execution method and device, electronic equipment and storage medium |
| WO2020199832A1 (en) * | 2019-04-01 | 2020-10-08 | 跬云(上海)信息科技有限公司 | Dynamic routing method and apparatus for query engine in pre-computation system |
| CN111159229B (en) * | 2019-12-31 | 2024-04-26 | 北京奇艺世纪科技有限公司 | Data query method and device |
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| CN108363819A (en) * | 2018-03-23 | 2018-08-03 | 联想(北京)有限公司 | Query engine matching method, device, server group and readable storage medium storing program for executing |
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| US11397734B2 (en) * | 2019-04-01 | 2022-07-26 | Kuyun (Shanghai) Information Technology Co., Ltd. | Dynamic routing method and apparatus for query engine in pre-computing system |
| CN111104419A (en) * | 2019-12-24 | 2020-05-05 | 上海众源网络有限公司 | Data query method and device |
| CN111159229A (en) * | 2019-12-31 | 2020-05-15 | 北京奇艺世纪科技有限公司 | Data query method and device |
| CN111159229B (en) * | 2019-12-31 | 2024-04-26 | 北京奇艺世纪科技有限公司 | Data query method and device |
| CN111639078A (en) * | 2020-05-25 | 2020-09-08 | 北京百度网讯科技有限公司 | Data query method and device, electronic equipment and readable storage medium |
| CN111723112A (en) * | 2020-06-11 | 2020-09-29 | 咪咕文化科技有限公司 | Data task execution method and device, electronic equipment and storage medium |
| CN111723112B (en) * | 2020-06-11 | 2023-07-07 | 咪咕文化科技有限公司 | Data task execution method and device, electronic equipment and storage medium |
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