CN105786992A - Data query method and device used for online transaction - Google Patents
Data query method and device used for online transaction Download PDFInfo
- Publication number
- CN105786992A CN105786992A CN201610090224.5A CN201610090224A CN105786992A CN 105786992 A CN105786992 A CN 105786992A CN 201610090224 A CN201610090224 A CN 201610090224A CN 105786992 A CN105786992 A CN 105786992A
- Authority
- CN
- China
- Prior art keywords
- complexity
- inquiry request
- data
- tables
- line transaction
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- 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
- G06F16/25—Integrating or interfacing systems involving database management systems
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/46—Multiprogramming arrangements
- G06F9/48—Program initiating; Program switching, e.g. by interrupt
- G06F9/4806—Task transfer initiation or dispatching
- G06F9/4843—Task transfer initiation or dispatching by program, e.g. task dispatcher, supervisor, operating system
- G06F9/4881—Scheduling strategies for dispatcher, e.g. round robin, multi-level priority queues
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2209/00—Indexing scheme relating to G06F9/00
- G06F2209/48—Indexing scheme relating to G06F9/48
- G06F2209/486—Scheduler internals
Abstract
The invention provides a data query method and device used for online transaction.The method comprises the steps that a query request in the online transaction time frame, and the complexity of the query request is determined according to query data involved in the query request, wherein the complexity can be the first complexity and the second complexity; when the complexity of the query request is the first complexity, the query request is placed into a task queue, and the task queue is configured to be executed in the preset time frame except for the online transaction time frame.According to the data query method and device, it can be ensured that the query request is processed, and it can also be ensured that an online transaction system normally and stably runs.
Description
Technical field
The present invention relates to data processing field, specifically, relate to a kind of data query method and apparatus for on-line transaction.
Background technology
Along with constantly expanding and people's improving constantly the attention rate of ecommerce of ecommerce correlation function, needed for electricity business's platform, data volume to be processed increases rapidly.Electricity business's platform is in the daytime except the data process tackling daily on-line transaction, in addition it is also necessary to provide the Data Analysis Services such as inquiry.But, in the Data Analysis Services such as inquiry, online non-inquiry class data are inevitably occurred to process, its occupying system resources, affecting the normal process of on-line transaction, particularly in the ever-increasing situation of data volume, the result of inquiry often derives time-out, it is likely to after running a period of time need to restart system because RAM leakage is serious, influential system stability.
Summary of the invention
For solving above-mentioned technical problem, the invention provides a kind of data query method and apparatus for on-line transaction, according to the complexity of inquiry, inquiry can be classified, and the execution time period of the execution time period of inquiry higher for complexity with on-line transaction is isolated, thus query processing can either be performed, ensure that again online transaction system safety and stability.
First aspect according to embodiment of the present invention, provide a kind of data query method for on-line transaction, the method includes: in the period carrying out on-line transaction, receive inquiry request, the inquiry data related to according to described inquiry request determine the complexity of described inquiry request, and described complexity includes the first complexity and the second complexity less than described first complexity；When the complexity of described inquiry request is the first complexity, described inquiry request being put into task queue, described task queue is configured to the scheduled time slot outside the period of described on-line transaction and performs.
In certain embodiments of the present invention, the described inquiry data related to according to described inquiry request determine that the complexity of described inquiry request includes: the tables of data related to according to described inquiry request and the attribute information of described tables of data determine the complexity of described inquiry request, wherein, described attribute information includes size and/or update cycle.
In certain embodiments of the present invention, the attribute information of the described tables of data related to according to described inquiry request and described tables of data determines that the complexity of described inquiry request includes: when the size of the tables of data that described inquiry request relates to and update cycle meet following condition, the complexity of described inquiry request is defined as described first complexity, otherwise, the complexity of described inquiry request is defined as described second complexity, wherein, described condition is: the size of described tables of data is more than or equal to the first predetermined threshold, and/or, update cycle is less than or equal to the second predetermined threshold.
In certain embodiments of the present invention, described task queue is additionally configured to timing execution.
In certain embodiments of the present invention, the task in described task queue performs according to the time sequencing put into.
In certain embodiments of the present invention, described method also includes: after each inquiry request of described task queue is finished, and the Query Result of described each inquiry request is generated data file, and described data file is saved in predefined paths.
Second aspect according to embodiment of the present invention, provide a kind of data query arrangement for on-line transaction, this device comprises the steps that request processing module, for in the period carrying out on-line transaction, receive inquiry request, the inquiry data related to according to described inquiry request determine the complexity of described inquiry request, described complexity includes the first complexity and the second complexity less than described first complexity, it is additionally operable to, when the complexity of described inquiry request is the first complexity, described inquiry request be put into task queue；Task processing module, performs the task in described task queue for the scheduled time slot outside the period of described on-line transaction.
In certain embodiments of the present invention, according to the inquiry data that described inquiry request relates to, described request processing module determines that the complexity of described inquiry request includes: the tables of data related to according to described inquiry request and the attribute information of described tables of data determine the complexity of described inquiry request, wherein, described attribute information includes size and/or update cycle.
In certain embodiments of the present invention, tables of data and the attribute information of described tables of data that described request processing module relates to according to described inquiry request determine that the complexity of described inquiry request includes: when the size of the tables of data that described inquiry request relates to and update cycle meet following condition, the complexity of described inquiry request is defined as described first complexity, otherwise, the complexity of described inquiry request is defined as described second complexity, wherein, described condition is: the size of described tables of data is more than or equal to the first predetermined threshold, and/or, update cycle is less than or equal to the second predetermined threshold.
In certain embodiments of the present invention, the timing of described task processing module performs the task in described task queue.
In certain embodiments of the present invention, described task processing module performs according to the time sequencing putting into described task queue.
In certain embodiments of the present invention, described task processing module, it is additionally operable to after each inquiry request of described task queue is finished, the Query Result of described each inquiry request is generated data file, and described data file is saved in predefined paths.
The data query method and apparatus for on-line transaction that embodiment of the present invention provides, can process based on the inquiry request differentiation that the on-line transaction period is received by the complexity of inquiry request, inquiry request higher for complexity is placed on the scheduled time slot outside the on-line transaction period perform, from the time of execution, inquiry request higher for complexity and on-line transaction are isolated, thus the process of inquiry request can be realized, it is capable of again normal, the stable operation of online transaction system；And, from the angle of large-scale data analysis, it is provided that determine the critical parameter of inquiry request complexity；And, after each inquiry request of task queue is finished, corresponding Query Result is saved in predefined paths, facilitates user's download and check and carry out corresponding data analysis.
Accompanying drawing explanation
Fig. 1 is the schematic flow sheet of the data query method for on-line transaction according to one embodiment of the present invention.
Fig. 2 is the structural representation of the data query arrangement for on-line transaction according to one embodiment of the present invention.
Detailed description of the invention
It is described in detail to various aspects of the present invention below in conjunction with the drawings and specific embodiments.Wherein, it is thus well known that module, unit and connection each other, link, communication or operation are shown without or do not elaborate.Further, described feature, framework or function can combine by any way in one or more embodiments.It will be appreciated by those skilled in the art that following various embodiments are served only for illustrating, not for limiting the scope of the invention.Can also be easy to understand, module in each embodiment described herein and shown in the drawings or unit or processing mode can be combined by various different configurations and design.
The concept below embodiment of the present invention related to illustrates.
On-line transaction, being primarily referred to as in the way of online transaction to process the work data of general real-time, the feature that its data process includes: quickly response, overtime interrupt and intensive concurrently, be generally adopted synchronization mechanism, requirement of real-time is higher, generally processes with the form of group system.
E-commerce platform, financial institution can be included (such as, banking institution etc.) ecommerce financial service platform, this platform can provide E-business service and finance support service by To enterprises with individual, such as, it may include enterprise store (BusinesstoBusiness, B2B), individual store (BusinesstoCustomer, B2C), the sub-platform such as store account and community, belong to online transaction system.This platform can include main website platform, is mainly for enterprise or individual etc. and enters member's use, may also include operation backstage, and the operation personnel being mainly for system carries out data analysis etc..
It follows that be described in conjunction with the accompanying the detailed description of the invention of the data query method for on-line transaction of the present invention.
Fig. 1 is the schematic flow sheet of the data query method for on-line transaction according to one embodiment of the present invention.
As it is shown in figure 1, in step s 11, in the period carrying out on-line transaction, receive inquiry request, the inquiry data related to according to this inquiry request determine the complexity of inquiry request, and wherein, described complexity can include the first complexity and the second complexity less than this first complexity.In certain embodiments of the present invention, the period of on-line transaction can include the time period providing on-line transaction to service enterprise or personal user of e-commerce platform regulation, for instance, working time section in the daytime.What the inquiry request of the present invention referred mainly to generation is for data analysis but not the inquiry request of on-line transaction.In the period carrying out on-line transaction, the inquiry request received can have different complexities, interrogation zone divisional processing to different complexities, for the inquiry that complexity is higher, put into task queue, period outside the on-line transaction period performs, for the inquiry that complexity is relatively low, directly perform within the on-line transaction period, such mode can advantageously ensure that the properly functioning of on-line transaction, because while on-line transaction processes, performs the query processing that complexity is higher, the a large amount of occupying system resources of meeting, affect the stability of on-line transaction Correlation method for data processing.
The inquiry data related to according to inquiry request of the present invention are (such as, tables of data etc.) determine that the complexity of inquiry request comprises the steps that the attribute information of tables of data and this tables of data related to according to inquiry request determines the complexity of inquiry request, wherein, the attribute information of tables of data can include size (such as, shared space) and/or the update cycle of this tables of data.Specifically, the tables of data related to according to inquiry request and the attribute information of this tables of data determine that the step of the complexity of inquiry request comprises the steps that when the tables of data that inquiry request relates to and update cycle meet predetermined condition, the complexity of inquiry request is defined as the first complexity, if being unsatisfactory for this predetermined condition, then the complexity of inquiry request is defined as the second complexity, wherein, this predetermined condition may is that the size volume of described tables of data is more than or equal to the first predetermined threshold TH1, and/or, update cycle update-time is less than or equal to the second predetermined threshold TH2.That is, if the tables of data that inquiry request relates to meets volume >=TH1 and/or update-time≤TH2, volume can be included >=TH1, or, update-time≤TH2, or, volume >=TH1 and update-time≤TH2, then the complexity of this inquiry request is defined as the first complexity, if being unsatisfactory for volume >=TH1 and/or update-time≤TH2, then the complexity of this inquiry request is defined as the second complexity, wherein, first complexity is more than the second complexity, that is, first complexity is higher complexity, second complexity is relatively low complexity.
First threshold TH1 can according to the resource of online transaction system (such as, internal memory, CPU and memory space etc.) etc. be determined, when the resource of system is comparatively well-to-do, TH1 could be arranged to bigger, when the resource of system is relatively limited, TH1 could be arranged to less, thus the on-line transaction that system resource priority treatment real-time is higher can be ensured.
Second Threshold TH2 can be set according to application needs.Such as, for the tables of data that the update cycle is shorter, can be higher with the correlation degree of on-line transaction, in the period of on-line transaction, such tables of data is read out, it is likely that the carrying out of on-line transaction can be affected.From the angle of data analysis, it is primarily upon the variation tendency etc. of the related data of certain period of time, compared with processing with the data of on-line transaction, the requirement of real-time of data is relatively low.Therefore, for the inquiry of the tables of data of update cycle shorter (such as, update more frequent), the period outside the on-line transaction period performs, and is conducive to improving the stability that online transaction system runs.
Then, in step s 12, when the complexity of inquiry request is the first complexity, inquiry request being put into task queue, this task queue can be configured to the scheduled time slot outside the period of on-line transaction and performs.When the complexity of inquiry request is the second complexity, it is possible to process according to the form of common real-time query.In certain embodiments of the present invention, task queue can be configured to timing execution, say, that these inquiry request that complexity is the first complexity (such as, high complexity) can perform in the scheduled time slot timing outside the period of on-line transaction.The period of on-line transaction be every day in the daytime when, this scheduled time slot can be the night of every day, for instance, morning 0:00 to 3:00.In other embodiment, task queue can also be without timing and performs, then these inquiry request can also irregularly perform by the scheduled time slot outside the period of on-line transaction, for instance, need irregular execution according to application.
In certain embodiments of the present invention, the task queue preserving inquiry request can also put into the time sequencing execution task of task queue according to inquiry request, such as, in the process that timed task performs, the inquiry request first putting into task queue first carries out, after put into the inquiry request of task queue after perform.
The data query method for on-line transaction of the present invention can also include: after each inquiry request of described task queue is finished, the Query Result of each inquiry request can be generated data file, and the data file of generation is saved in the predefined paths of file server, such as, predefined paths can be saved in by after data file compression, facilitate operation personnel to carry out data analysis from predefined paths download and inquiry result.
Although superincumbent embodiment being the complexity of inquiry request is divided into the first complexity and two kinds of complexities of the second complexity, but in other embodiments, the complexity of inquiry request can be divided into three kinds of complexities, first complexity > the second complexity > the 3rd complexity, the inquiry request of the first complexity can perform by the scheduled time slot outside the on-line transaction period, the inquiry request of the 3rd complexity can perform in real time in the on-line transaction period, the inquiry request of the second complexity can perform within the period that the comparison of on-line transaction period is idle, may be considered a kind of processing procedure quasi real time.
Describe the detailed description of the invention of the data query method for on-line transaction of the present invention above in conjunction with accompanying drawing, describe the device corresponding with said method below in conjunction with accompanying drawing.
The data query arrangement for on-line transaction that embodiment of the present invention provides can as online transaction system a module, use with other block combiner of existing online transaction system, for example, it is possible to increase the data query arrangement for on-line transaction of the present invention in the query processing module of existing online transaction system.
The data query arrangement for on-line transaction of the present invention is described below in conjunction with accompanying drawing.
Fig. 2 is the structural representation of the data query arrangement for on-line transaction according to one embodiment of the present invention.
As shown in Figure 2, data query arrangement 1 for on-line transaction can include request processing module 11 and task processing module 12, the two can carry out data communication, it also is able to other processing modules with online transaction system and carries out data communication, for example, it is possible to the respective handling module calling online transaction system carries out data process.
It follows that the request processing module 11 of the present invention and the concrete data of task processing module 12 are processed and illustrate.
Request processing module 11 can in the period carrying out on-line transaction, receive inquiry request, the inquiry data related to according to described inquiry request determine the complexity of described inquiry request, described complexity includes the first complexity and the second complexity less than described first complexity, when the complexity of described inquiry request is the first complexity, described inquiry request is put into task queue, when the complexity of inquiry request is the second complexity, can process according to the form of common real-time query, such as, existing query processing module can be called and carry out inquiry request process.
In certain embodiments of the present invention, the period of on-line transaction can include the time period providing on-line transaction to service enterprise or personal user of e-commerce platform regulation, for instance, working time section in the daytime.What the inquiry request of the present invention referred mainly to generation is for data analysis but not the inquiry request of on-line transaction.In the period carrying out on-line transaction, the inquiry request received can have different complexities, interrogation zone divisional processing to different complexities, for the inquiry that complexity is higher, period outside the on-line transaction period performs, for the inquiry that complexity is relatively low, directly perform within the on-line transaction period, such mode can advantageously ensure that the properly functioning of on-line transaction, because while on-line transaction processes, perform the query processing that complexity is higher, a large amount of occupying system resources of meeting, affect the stability of on-line transaction Correlation method for data processing.
The inquiry data that request processing module 11 relates to according to inquiry request are (such as, tables of data etc.) determine that the complexity of inquiry request comprises the steps that the attribute information of tables of data and this tables of data related to according to inquiry request determines the complexity of inquiry request, wherein, the attribute information of tables of data can include size (such as, shared space) and/or the update cycle of this tables of data.Specifically, the tables of data related to according to inquiry request and the attribute information of this tables of data determine that the complexity of inquiry request comprises the steps that when the tables of data that inquiry request relates to and update cycle meet predetermined condition, the complexity of inquiry request is defined as the first complexity, if being unsatisfactory for this predetermined condition, then the complexity of inquiry request is defined as the second complexity, wherein, this predetermined condition may is that the size volume of described tables of data is more than or equal to the first predetermined threshold TH1, and/or, update cycle update-time is less than or equal to the second predetermined threshold TH2.That is, if the tables of data that inquiry request relates to meets volume >=TH1 and/or update-time≤TH2, volume can be included >=TH1, or, update-time≤TH2, or, volume >=TH1 and update-time≤TH2, then the complexity of this inquiry request is defined as the first complexity, if being unsatisfactory for volume >=TH1 and/or update-time≤TH2, then the complexity of this inquiry request is defined as the second complexity, wherein, first complexity is more than the second complexity, that is, first complexity is higher complexity, second complexity is relatively low complexity.
First threshold TH1 can according to the resource of online transaction system (such as, internal memory, CPU and memory space etc.) etc. be determined, when the resource of system is comparatively well-to-do, TH1 could be arranged to bigger, when the resource of system is relatively limited, TH1 could be arranged to less, thus system resource priority treatment on-line transaction can be ensured.
Second Threshold TH2 can be set according to application needs.Such as, for the tables of data that the update cycle is shorter, can be higher with the correlation degree of on-line transaction, in the period of on-line transaction, such tables of data is read out, it is likely that the carrying out of on-line transaction can be affected.From the angle of data analysis, it is primarily upon the variation tendency etc. of the related data of certain period of time, compared with processing with the data of on-line transaction, the requirement of real-time of data is relatively low.Therefore, for the inquiry of the tables of data of update cycle shorter (such as, update more frequent), the period outside the on-line transaction period performs, and is conducive to improving the stability that online transaction system runs.
Task processing module 12 can perform the task in task queue at the scheduled time slot of the period of on-line transaction.In certain embodiments of the present invention, task queue can be configured to timing execution, say, that these inquiry request that complexity is the first complexity (such as, high complexity) can perform in the scheduled time slot timing outside the period of on-line transaction.The period of on-line transaction be every day in the daytime when, this scheduled time slot can be the night of every day, for instance, morning 0:00 to 3:00.In other embodiment, task queue can also be without timing and performs, then these inquiry request can also irregularly perform by the scheduled time slot outside the period of on-line transaction, for instance, need irregular execution according to application.
In certain embodiments of the present invention, task processing module 12 can also put into the time sequencing execution task of task queue according to inquiry request, for instance, in the process that timed task performs, the inquiry request first putting into task queue first carries out, after put into the inquiry request of task queue after perform.
Task processing module 12 can also after being finished in each inquiry request of described task queue, the Query Result of each inquiry request is generated data file, and the data file of generation is saved in the predefined paths of file server, such as, predefined paths can be saved in by after data file compression, facilitate operation personnel to carry out data analysis from predefined paths download and inquiry result.
Through the above description of the embodiments, those skilled in the art is it can be understood that can realize by the mode of software combined with hardware platform to the present invention.Based on such understanding, what background technology was contributed by technical scheme can embody with the form of software product in whole or in part, this computer software product can be stored in storage medium, such as ROM/RAM, magnetic disc, CD etc., including some instructions with so that a computer equipment (can be personal computer, server, smart mobile phone or the network equipment etc.) perform the method described in some part of each embodiment of the present invention or embodiment.
Terminology used herein of the present invention and wording, just to illustrating, are not intended to constitute restriction.It will be appreciated by those skilled in the art that under the premise of the ultimate principle without departing from disclosed embodiment, each details in above-mentioned embodiment can be carried out various change.Therefore, the scope of the present invention is only determined by claim, and in the claims, except as otherwise noted, all of term should be understood by the broadest rational meaning.
Claims (12)
1. the data query method for on-line transaction, it is characterised in that described method includes:
In the period carrying out on-line transaction, receiving inquiry request, the inquiry data related to according to described inquiry request determine the complexity of described inquiry request, and described complexity includes the first complexity and the second complexity less than described first complexity；
When the complexity of described inquiry request is the first complexity, described inquiry request being put into task queue, described task queue is configured to the scheduled time slot outside the period of described on-line transaction and performs.
2. method according to claim 1, it is characterised in that the described inquiry data related to according to described inquiry request determine that the complexity of described inquiry request includes:
The tables of data related to according to described inquiry request and the attribute information of described tables of data determine the complexity of described inquiry request, and wherein, described attribute information includes size and/or update cycle.
3. method according to claim 2, it is characterised in that the attribute information of the described tables of data related to according to described inquiry request and described tables of data determines that the complexity of described inquiry request includes:
When the size of the tables of data that described inquiry request relates to and update cycle meet following condition, the complexity of described inquiry request is defined as described first complexity, otherwise, the complexity of described inquiry request is defined as described second complexity,
Wherein, described condition is: the size of described tables of data more than or equal to the first predetermined threshold, and/or, the update cycle is less than or equal to the second predetermined threshold.
4. method according to claim 1, it is characterised in that described task queue is additionally configured to timing and performs.
5. method according to claim 4, it is characterised in that the task in described task queue performs according to the time sequencing put into.
6. method according to claim 1, it is characterised in that described method also includes:
After each inquiry request of described task queue is finished, the Query Result of described each inquiry request is generated data file, and described data file is saved in predefined paths.
7. the data query arrangement for on-line transaction, it is characterised in that described device includes:
Request processing module, for in the period carrying out on-line transaction, receiving inquiry request, the inquiry data related to according to described inquiry request determine the complexity of described inquiry request, described complexity includes the first complexity and the second complexity less than described first complexity
It is additionally operable to, when the complexity of described inquiry request is the first complexity, described inquiry request be put into task queue；
Task processing module, performs the task in described task queue for the scheduled time slot outside the period of described on-line transaction.
8. device according to claim 7, it is characterised in that according to the inquiry data that described inquiry request relates to, described request processing module determines that the complexity of described inquiry request includes:
The tables of data related to according to described inquiry request and the attribute information of described tables of data determine the complexity of described inquiry request, and wherein, described attribute information includes size and/or update cycle.
9. device according to claim 8, it is characterized in that, tables of data and the attribute information of described tables of data that described request processing module relates to according to described inquiry request determine that the complexity of described inquiry request includes: when the size of the tables of data that described inquiry request relates to and update cycle meet following condition, the complexity of described inquiry request is defined as described first complexity, otherwise, the complexity of described inquiry request is defined as described second complexity
Wherein, described condition is: the size of described tables of data more than or equal to the first predetermined threshold, and/or, the update cycle is less than or equal to the second predetermined threshold.
10. device according to claim 7, it is characterised in that the timing of described task processing module performs the task in described task queue.
11. device according to claim 10, it is characterised in that described task processing module performs task according to the time sequencing putting into described task queue.
12. device according to claim 7, it is characterized in that, described task processing module, be additionally operable to after each inquiry request of described task queue is finished, the Query Result of described each inquiry request is generated data file, and described data file is saved in predefined paths.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610090224.5A CN105786992A (en) | 2016-02-17 | 2016-02-17 | Data query method and device used for online transaction |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610090224.5A CN105786992A (en) | 2016-02-17 | 2016-02-17 | Data query method and device used for online transaction |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN105786992A true CN105786992A (en) | 2016-07-20 |
Family
ID=56402802
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610090224.5A Pending CN105786992A (en) | 2016-02-17 | 2016-02-17 | Data query method and device used for online transaction |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN105786992A (en) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106970837A (en) * | 2017-03-29 | 2017-07-21 | 联想(北京)有限公司 | A kind of information processing method and electronic equipment |
| CN107330096A (en) * | 2017-07-05 | 2017-11-07 | 恒生电子股份有限公司 | Document handling method and device, computer-readable recording medium and electronic equipment |
| CN108170860A (en) * | 2018-01-22 | 2018-06-15 | 北京小度信息科技有限公司 | Data query method, apparatus, electronic equipment and computer readable storage medium |
| CN110955469A (en) * | 2019-11-25 | 2020-04-03 | 中国银行股份有限公司 | Method and device for online transaction by X86 platform distributed batch call |
| WO2022084784A1 (en) * | 2020-10-23 | 2022-04-28 | International Business Machines Corporation | Auto-scaling a query engine for enterprise-level big data workloads |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1934566A (en) * | 2004-02-26 | 2007-03-21 | 国际商业机器公司 | Dynamic query optimization method, device and computer program |
| US7555282B2 (en) * | 1994-11-21 | 2009-06-30 | Bgc Partners, Inc. | Methods and systems for retrieving data stored in a database |
| CN103731498A (en) * | 2013-12-31 | 2014-04-16 | 浙江鸿程计算机系统有限公司 | Big data real-time enquiry system load balancing method based on copy selection |
| CN103729246A (en) * | 2013-12-31 | 2014-04-16 | 浪潮(北京)电子信息产业有限公司 | Method and device for dispatching tasks |
-
2016
- 2016-02-17 CN CN201610090224.5A patent/CN105786992A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7555282B2 (en) * | 1994-11-21 | 2009-06-30 | Bgc Partners, Inc. | Methods and systems for retrieving data stored in a database |
| CN1934566A (en) * | 2004-02-26 | 2007-03-21 | 国际商业机器公司 | Dynamic query optimization method, device and computer program |
| CN103731498A (en) * | 2013-12-31 | 2014-04-16 | 浙江鸿程计算机系统有限公司 | Big data real-time enquiry system load balancing method based on copy selection |
| CN103729246A (en) * | 2013-12-31 | 2014-04-16 | 浪潮(北京)电子信息产业有限公司 | Method and device for dispatching tasks |
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106970837A (en) * | 2017-03-29 | 2017-07-21 | 联想(北京)有限公司 | A kind of information processing method and electronic equipment |
| CN106970837B (en) * | 2017-03-29 | 2020-05-26 | 联想(北京)有限公司 | Information processing method and electronic equipment |
| CN107330096A (en) * | 2017-07-05 | 2017-11-07 | 恒生电子股份有限公司 | Document handling method and device, computer-readable recording medium and electronic equipment |
| CN108170860A (en) * | 2018-01-22 | 2018-06-15 | 北京小度信息科技有限公司 | Data query method, apparatus, electronic equipment and computer readable storage medium |
| CN110955469A (en) * | 2019-11-25 | 2020-04-03 | 中国银行股份有限公司 | Method and device for online transaction by X86 platform distributed batch call |
| CN110955469B (en) * | 2019-11-25 | 2023-09-26 | 中国银行股份有限公司 | Method and device for online transaction of distributed batch call of X86 platform |
| WO2022084784A1 (en) * | 2020-10-23 | 2022-04-28 | International Business Machines Corporation | Auto-scaling a query engine for enterprise-level big data workloads |
| GB2615466A (en) * | 2020-10-23 | 2023-08-09 | Ibm | Auto-scaling a query engine for enterprise-level big data workloads |
| US11809424B2 (en) | 2020-10-23 | 2023-11-07 | International Business Machines Corporation | Auto-scaling a query engine for enterprise-level big data workloads |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN105786992A (en) | Data query method and device used for online transaction | |
| WO2021068607A1 (en) | Multi-system multi-store order integrating method and apparatus, computer device and storage medium | |
| CN102521712A (en) | Process instance data processing method and device | |
| CN102662993A (en) | A method for providing page data | |
| TW200825704A (en) | Dynamic voltage scheduling method, system thereof and record medium | |
| US20140089397A1 (en) | Method, server, and client for pushing and displaying splash screen | |
| WO2021244639A1 (en) | Auxiliary implementation method and apparatus for online prediction using machine learning model | |
| WO2018085027A1 (en) | Systems and methods for database management | |
| CN111078980A (en) | Management method, device, equipment and storage medium based on credit investigation big data | |
| CN110428240B (en) | Automatic suspicious transaction identification and processing method, terminal and server | |
| CN102446172B (en) | Data service processing method and device adopting same | |
| US9754319B2 (en) | Source document framework for accounting systems | |
| CN110347653A (en) | Data processing method and device, electronic equipment and readable storage medium storing program for executing | |
| US11157690B2 (en) | Techniques for asynchronous execution of computationally expensive local spreadsheet tasks | |
| CN109165554A (en) | A kind of face characteristic comparison method based on cuda technology | |
| CN202041990U (en) | Personal loan transaction platform for bank | |
| CN106708869B (en) | Group data processing method and device | |
| CN109375998B (en) | Processing method in high-concurrency request environment | |
| CN102968714A (en) | Bookkeeping and financial management system and method based on consumption data of integrated circuit (IC) card | |
| CN115208893B (en) | Resource scheduling method and device | |
| CN110908983A (en) | Intelligent marketing system based on user portrait recognition | |
| CN106933873A (en) | A kind of cross-platform data querying method and equipment | |
| CN106648874B (en) | Processing method and device for batch tasks | |
| CN103150171A (en) | Product combination engine device and system and service method | |
| WO2018130164A1 (en) | Communication method and system for cloud computing mobile terminal |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20160720 |
|
| RJ01 | Rejection of invention patent application after publication |