CN105573892A - Business data batch processing method and system - Google Patents
Business data batch processing method and system Download PDFInfo
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- CN105573892A CN105573892A CN201510966813.0A CN201510966813A CN105573892A CN 105573892 A CN105573892 A CN 105573892A CN 201510966813 A CN201510966813 A CN 201510966813A CN 105573892 A CN105573892 A CN 105573892A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/3065—Monitoring arrangements determined by the means or processing involved in reporting the monitored data
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/32—Monitoring with visual or acoustical indication of the functioning of the machine
- G06F11/324—Display of status information
- G06F11/327—Alarm or error message display
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Abstract
The invention relates to a business data batch processing method and system. The method comprises a data extracting process and an extraction and monitoring feedback process, wherein the extraction and monitoring feedback process comprises steps as follows: in the data extraction process, daily trading volume in an extracted business statement is recorded; whether the data extraction process is abnormal is judged according to the daily trading volume and historical trading volume, if yes, whether a corresponding processing method exists in a pre-established abnormal condition processing method base is judged according to a data extraction log, if yes, the data extraction process is amended with the corresponding processing method, and the daily trading volume in re-extracted business statement after amendment is recorded. In the data batch processing method, automatic analysis can be performed after a problem happens, and the workload of an operation and maintenance worker is greatly reduced. Meanwhile, the data batch processing schedule and efficiency are greatly improved due to the autonomous problem-solving ability.
Description
Technical field
The present invention relates to bank data processing technology field, particularly relate to a kind of business datum and run batch method and system.
Background technology
The computer system of bank all once to be run batch every day, all branches are also had the Data Enter of agency in total computing machine by so-called Pao Pishi bank, carry out processing, computing, then need the thing done to release by second day, such as printed card letter, promises bill etc.At present, as shown in Figure 1, the data of bank are run batch method and are generally comprised three processes: data extraction process, data mart modeling process and data display process.These data run batch method owing to lacking necessary automatic analysis, once go wrong, operation maintenance personnel needs to pay a large amount of work and pinpoints the problems and deal with problems.
Summary of the invention
Technical matters to be solved by this invention is: existing data are run batch method and lacked automatic analysis ability, once go wrong, operation maintenance personnel needs to pay very large workload and solves problem.
For solving the problems of the technologies described above, the present invention proposes a kind of data and running batch method and system.
First aspect, data declaration method provided by the invention comprises data extraction process and extracts monitoring feedback procedure, and described extraction monitoring feedback procedure comprises:
When described data extraction process, the daily trading volume in the Business Stream water meter that record extracts;
According to described daily trading volume and historical trading volume, judge whether described data extraction process occurs exception,
If so, then judge in the abnormal conditions disposal route storehouse set up in advance, whether have corresponding disposal route according to data pick-up daily record,
If so, the disposal route of this correspondence is then utilized to revise described data extraction process, and the daily trading volume in the Business Stream water meter again extracted after being recorded in correction.
Optionally, described extraction monitoring feedback procedure also comprises:
When judging the disposal route without correspondence in described abnormal conditions disposal route storehouse, then record described data extraction process and occur the abnormal date, and send warning message by internal gateway.
Optionally, the method also comprises data mart modeling process and processing monitoring feedback procedure, and described processing monitoring feedback procedure comprises:
Judge whether the trading volume in described data mart modeling process exceeds corresponding preset range process time,
If so, then determine that described data mart modeling process occurs abnormal, and judge in the abnormal conditions disposal route storehouse set up in advance, whether have corresponding disposal route according to data mart modeling daily record,
If so, the disposal route of this correspondence is then utilized to revise described data mart modeling process;
Wherein, described data mart modeling process performs after judging the daily trading volume in described data extraction process Business Stream water meter that is normal or that again extract after record is revised.
Optionally, described processing monitoring feedback procedure also comprises:
When judging the disposal route without correspondence in described abnormal conditions disposal route storehouse, then record the abnormal information that described data mart modeling process occurs, and send warning message by internal gateway.
Optionally, described processing monitoring feedback procedure also comprises:
When judging that the trading volume in described data mart modeling process does not exceed corresponding preset range process time, then determine that described data mart modeling process is normal, and be recorded in process in described data mart modeling process trading volume, beginning and ending time of process, the load of CPU, the computed EMS memory occupation ratio of institute and/or computed disk load.
Optionally, the method also comprises data display process and shows monitoring feedback procedure, and wherein said displaying monitoring feedback procedure comprises:
Judge in the tables of data adopting different report style to show in described data display process whether gather trading volume consistent, if not, then send warning message by internal gateway;
Wherein, described data display process normally or after the revised data mart modeling process of execution performs in the described data mart modeling process of judgement.
Second aspect, data provided by the invention are run batch system and are comprised the data extraction module for performing data extraction process and perform the extraction monitoring feedback module extracting monitoring feedback procedure, and described extraction monitoring feedback module specifically comprises:
Record cell, for described data extraction module at data extraction process time, record extract Business Stream water meter in daily trading volume;
First judging unit, for according to described daily trading volume and historical trading volume, judges whether described data extraction process occurs exception;
Second judging unit, for when judging that described data extraction process is abnormal, judges in the abnormal conditions disposal route storehouse set up in advance, whether have corresponding disposal route according to data pick-up daily record;
First amending unit, for when judging there is corresponding disposal route in described abnormal conditions disposal route storehouse, the disposal route of this correspondence is utilized to revise described data extraction process, and the daily trading volume in the Business Stream water meter again extracted after being recorded in correction.
Optionally, described extraction monitoring feedback module also comprises:
Alarm unit, for when judging the disposal route without correspondence in described abnormal conditions disposal route storehouse, then records described data extraction process and occurs the abnormal date, and send warning message by internal gateway.
Optionally, this system also comprises the data mart modeling module for performing data process and performs the processing monitoring feedback module of processing monitoring feedback procedure, and described processing monitoring feedback module specifically comprises:
3rd judging unit, for judging whether the trading volume in described data mart modeling process exceeds corresponding preset range process time;
4th judging unit, for when judging that described trading volume exceeds corresponding preset range process time, determine that described data mart modeling process occurs abnormal, and judge in the abnormal conditions disposal route storehouse set up in advance, whether have corresponding disposal route according to data mart modeling daily record;
Second amending unit, during for there being the disposal route of this correspondence in described abnormal conditions disposal route storehouse, utilizes the disposal route of this correspondence to revise described data mart modeling process;
Wherein, described data mart modeling module performs described data mart modeling process described extraction after monitoring feedback module judges the daily trading volume of described data extraction process normally or in the Business Stream water meter again extracted after being recorded in correction.
Optionally, this system also comprises data display module for performing data display process and for performing the displaying monitoring feedback module showing monitoring feedback procedure, wherein said displaying monitoring feedback module specifically for:
Judge in the tables of data adopting different report style to show in described data display process whether gather trading volume consistent, if not, then send warning message by internal gateway;
Wherein, described data display module judges to perform described data display process after the normal or described data mart modeling module of described data mart modeling process performs revised data mart modeling process at described processing monitoring feedback module.
Data provided by the invention are run in batch method and system, by the daily trading volume on the same day and the comparison of historical trading volume, judge that whether the daily trading volume on the same day is abnormal.When appearance is abnormal, utilize disposal route correction extraction process corresponding in the abnormal conditions disposal route storehouse set up in advance, and the daily trading volume in the Business Stream water meter again extracted after record correction, and then utilize this daily trading volume to perform follow-up program.Visible, data provided by the invention run batch method, independently can pinpoint the problems, can carry out certain automatic process, greatly reducing the workload of operation maintenance personnel when pinpointing the problems.
Accompanying drawing explanation
Can understanding characteristic information of the present invention clearly and advantage by reference to accompanying drawing, accompanying drawing is schematic and should not be construed as and carry out any restriction to the present invention, in the accompanying drawings:
Fig. 1 shows the schematic flow sheet that available data runs batch method;
Fig. 2 shows the schematic flow sheet running batch method one embodiment according to data of the present invention;
Fig. 3 shows the schematic flow sheet running batch another embodiment of method according to data of the present invention;
Fig. 4 shows the structured flowchart running batch system one embodiment according to data of the present invention.
Embodiment
In order to more clearly understand above-mentioned purpose of the present invention, feature and advantage, below in conjunction with the drawings and specific embodiments, the present invention is further described in detail.It should be noted that, when not conflicting, the feature in the embodiment of the application and embodiment can combine mutually.
Set forth a lot of detail in the following description so that fully understand the present invention; but; the present invention can also adopt other to be different from other modes described here and implement, and therefore, protection scope of the present invention is not by the restriction of following public specific embodiment.
The invention provides a kind of data and run batch method, as shown in Figure 2,3, the method comprises data extraction process and extracts monitoring feedback procedure, and described extraction monitoring feedback procedure comprises:
S1, when described data extraction process, record extract Business Stream water meter in daily trading volume;
S2, according to described daily trading volume and historical trading volume, judge whether described data extraction process occurs exception;
S3, when judging that described data extraction process occurs abnormal, judge according to data pick-up daily record the disposal route whether having correspondence in the abnormal conditions disposal route storehouse set up in advance;
S4, when judging there is corresponding disposal route in described abnormal conditions disposal route storehouse, the disposal route of this correspondence is utilized to revise described data extraction process, and the daily trading volume in the Business Stream water meter again extracted after being recorded in correction.
Those skilled in the art it should be known that the data of bank are run batch list and performed once every day, and therefore the daily trading volume of above-mentioned record is the daily trading volume on the same day.
So-called abnormal conditions disposal route storehouse, be the method base set up according to the abnormal conditions disposal route of the daily accumulation of staff, different abnormal conditions adopt different disposal routes, and the type of abnormal conditions judges according to data pick-up daily record.
Data provided by the invention are run in batch method, by the daily trading volume on the same day and the comparison of historical trading volume, judge that whether the daily trading volume on the same day is abnormal.When appearance is abnormal, utilize disposal route correction extraction process corresponding in the abnormal conditions disposal route storehouse set up in advance, and the daily trading volume in the Business Stream water meter again extracted after record correction, and then utilize this daily trading volume to perform follow-up program.Visible, data provided by the invention run batch method, when going wrong, can carry out certain automatic analysis, greatly reduce the workload of operation maintenance personnel.Meanwhile, owing to having certain autonomous problem-solving ability, therefore greatly accelerate data and run the progress and efficiency criticized.
In addition, data provided by the invention run the function that batch method also has configuration automatically, such as when increase member's row, the daily trading volume of record certainly increased to some extent before this member's row of increase, can judge that the increase of daily trading volume causes owing to increasing member's row by abnormality eliminating method, then can call configuration option table, the correlation parameter of this member's row is configured automatically.Therefore data provided by the invention run batch method can realize configuration automatically function in member's row system update, switching or business increase or deletion etc.
In actual applications, the daily trading volume of nearest a week can be adopted as historical trading volume, the daily trading volume of nearest month also can be adopted as historical trading volume.Suppose that the same day is all N, the daily trading volume of N weekly in nearest a period of time can also be adopted as historical trading volume.Suppose that the same day is No. N, can also to adopt in nearest a period of time monthly the daily trading volume of No. N as historical trading volume.If the same day is technical dates, such as two 11, two 12, Spring Festival etc., can also using the annual daily trading volume in this technical dates as historical trading volume.
Understandablely be, when judging whether data extraction process occurs abnormal, can be analyzed by the situation of change of certain data model according to historical trading volume, see whether the daily trading volume on the same day meets the variation tendency of historical trading volume, if the variation tendency of the daily trading volume on the same day and historical trading volume is inconsistent or have larger gap, then assert that data extraction process occurs abnormal.
Certainly, disposal route in abnormal conditions disposal route storehouse is limited, when the abnormal conditions occurred do not have corresponding disposal route in the party Faku County, namely beyond its autonomous processing power, now can record data extraction process and occur the abnormal date, and send warning message by internal gateway.Notify operation maintenance personnel in this way, the data that operation maintenance personnel stops this time according to actual conditions are run batch flow process or are ignored abnormal conditions continuation operation.Visible, the invention provides certain alarm mechanism, once there is the timely operation maintenance personnel simultaneously of problem that cannot independently solve, make it learn in time, thus timely handling failure.
When judge according to the daily trading volume on the same day and historical trading volume data extraction process do not occur exception and data extraction process normal, or after again recording daily trading volume after the data extraction process correction of exception, need to continue to perform follow-up data mart modeling process.As shown in Figure 3, in order to realize the monitoring to data process, data provided by the invention run batch method can also comprise processing monitoring feedback procedure, and this processing monitoring feedback procedure can specifically comprise:
Judge whether the trading volume in described data mart modeling process exceeds corresponding preset range process time,
If so, then determine that described data mart modeling process occurs abnormal, and judge in the abnormal conditions disposal route storehouse set up in advance, whether have corresponding disposal route according to data mart modeling daily record,
If so, then utilize the disposal route of this correspondence to revise described data mart modeling process, and perform revised data mart modeling process.
Those skilled in the art it should be known that data mart modeling process refers to the process storing the relevant procedure script of daily trading volume or database, gather.Data mart modeling process does not have network traffics (impact of cluster situation 10,000,000,000 broadband is also negligible) substantially.
Generally, when obviously not decaying in mechanical propertys such as CPU processing power, disk read-write abilities, when trading volume does not obviously fluctuate, the data mart modeling time should fluctuate in a less preset range.If the data mart modeling time exceeds preset range, then think that data mart modeling process occurs abnormal.Such as, process that 10min terminates should be performed and this time perform 10s and just terminate, or process that 10s terminates should be performed this time perform 10min and just terminate, all think that process occurs extremely.For different abnormal conditions, different disposal routes is adopted to process.Such as, this time perform for process that 10min terminates should be performed the abnormal conditions that 10s just terminates, be likely that Parameter transfer mistake or relevant configuration table mistake cause, then determine concrete reason according to data mart modeling daily record, and then process.Again such as, this time perform for process that 10s terminates should be performed the abnormal conditions that 10min just terminates, be likely that generation lock table or machine are fully loaded with, then determine concrete reason according to data mart modeling daily record, and then process.
Visible, achieve further analyzing and processing ability by processing monitoring feedback procedure, further reduce the workload of operation maintenance personnel.
Judging in described abnormal conditions disposal route storehouse without corresponding disposal route, when can not process abnormal conditions, then record the abnormal information that described data mart modeling process occurs, and send warning message by internal gateway, the operation maintenance personnel while of timely, it is made to learn in time, thus timely handling failure.
Understandable, when judging that the trading volume in described data mart modeling process does not exceed corresponding preset range process time, then described data mart modeling process is normal.Carry out follow-up further optimization to provide reference to run batch method to data, can be recorded in process in described data mart modeling process trading volume, the beginning and ending time of process, the information such as load, the computed disk load of the computed EMS memory occupation ratio of institute and/or institute of CPU.
Normal or after performing the data mart modeling process revised in decision data process, follow-up data display process can be performed.As shown in Figure 3, in order to realize the monitoring to data display process, data run batch method also can comprise displaying monitoring feedback procedure, and this displaying monitoring feedback procedure can comprise:
Judge in the tables of data adopting different report style to show in described data display process whether gather trading volume consistent, if not, then send warning message by internal gateway.
Those skilled in the art it should be known that so-called data display process refers to the process that the data after to processing display with the tables of data of report style (such as column diagram).The data of financial circles, feature is obvious, statistical indicator can be completely out exhaustive, same number is according to different report style can be adopted to show, but for each statistical indicator, be consistent in the trading volume that gathers of the tables of data of each report style (such as column diagram), otherwise be exactly occurred problem, need to send warning message, make operation maintenance personnel learn mistake in time.
Based on identical inventive concept, the present invention also provides a kind of data to run batch system, as shown in Figure 4, this system 100 comprises the data extraction module 101 for performing data extraction process and performs the extraction monitoring feedback module 102 extracting monitoring feedback procedure, and described extraction monitoring feedback module specifically comprises:
Record cell, for described data extraction module at data extraction process time, record extract Business Stream water meter in daily trading volume;
First judging unit, for according to described daily trading volume and historical trading volume, judges whether described data extraction process occurs exception;
Second judging unit, for when judging that described data extraction process is abnormal, judges in the abnormal conditions disposal route storehouse set up in advance, whether have corresponding disposal route according to data pick-up daily record;
First amending unit, for when judging there is corresponding disposal route in described abnormal conditions disposal route storehouse, the disposal route of this correspondence is utilized to revise described data extraction process, and the daily trading volume in the Business Stream water meter again extracted after being recorded in correction.
Optionally, described extraction monitoring feedback module also comprises:
Alarm unit, for when judging the disposal route without correspondence in described abnormal conditions disposal route storehouse, then records described data extraction process and occurs the abnormal date, and send warning message by internal gateway.
Optionally, as shown in Figure 4, this system also comprises the data mart modeling module 103 for performing data process and performs the processing monitoring feedback module 104 of processing monitoring feedback procedure, and described processing monitoring feedback module specifically comprises:
3rd judging unit, for judging whether the trading volume in described data mart modeling process exceeds corresponding preset range process time;
4th judging unit, for when judging that described trading volume exceeds corresponding preset range process time, determine that described data mart modeling process occurs abnormal, and judge in the abnormal conditions disposal route storehouse set up in advance, whether have corresponding disposal route according to data mart modeling daily record;
Second amending unit, during for there being the disposal route of this correspondence in described abnormal conditions disposal route storehouse, utilizes the disposal route of this correspondence to revise described data mart modeling process;
Wherein, described data mart modeling module performs described data mart modeling process described extraction after monitoring feedback module judges the daily trading volume of described data extraction process normally or in the Business Stream water meter again extracted after being recorded in correction.
Optionally, as shown in Figure 4, native system also comprises data display module 105 for performing data display process and for performing the displaying monitoring feedback module 106 showing monitoring feedback procedure, wherein said displayings monitor feedback module specifically for:
Judge in the tables of data adopting different report style to show in described data display process whether gather trading volume consistent, if not, then send warning message by internal gateway;
Wherein, described data display module judges to perform described data display process after the normal or described data mart modeling module of described data mart modeling process performs revised data mart modeling process at described processing monitoring feedback module.
It is the function structure module of running batch method with data provided by the invention that data provided by the invention run batch system, and the explanation of its relative section, explanation and beneficial effect refer to data of the present invention and run appropriate section in the method for criticizing, repeat no more here.
Although describe embodiments of the present invention by reference to the accompanying drawings, but those skilled in the art can make various modifications and variations without departing from the spirit and scope of the present invention, such amendment and modification all fall into by within claims limited range.
Claims (10)
1. data run a batch method, it is characterized in that, comprise data extraction process and extract monitoring feedback procedure, and described extraction monitoring feedback procedure comprises:
When described data extraction process, the daily trading volume in the Business Stream water meter that record extracts;
According to described daily trading volume and historical trading volume, judge whether described data extraction process occurs exception,
If so, then judge in the abnormal conditions disposal route storehouse set up in advance, whether have corresponding disposal route according to data pick-up daily record,
If so, the disposal route of this correspondence is then utilized to revise described data extraction process, and the daily trading volume in the Business Stream water meter again extracted after being recorded in correction.
2. method according to claim 1, is characterized in that, described extraction monitoring feedback procedure also comprises:
When judging the disposal route without correspondence in described abnormal conditions disposal route storehouse, then record described data extraction process and occur the abnormal date, and send warning message by internal gateway.
3. method according to claim 1, is characterized in that, also comprises data mart modeling process and processing monitoring feedback procedure, and described processing monitoring feedback procedure comprises:
Judge whether the trading volume in described data mart modeling process exceeds corresponding preset range process time,
If so, then determine that described data mart modeling process occurs abnormal, and judge in the abnormal conditions disposal route storehouse set up in advance, whether have corresponding disposal route according to data mart modeling daily record,
If so, the disposal route of this correspondence is then utilized to revise described data mart modeling process;
Wherein, described data mart modeling process performs after judging the daily trading volume in described data extraction process Business Stream water meter that is normal or that again extract after record is revised.
4. method according to claim 3, is characterized in that, described processing monitoring feedback procedure also comprises:
When judging the disposal route without correspondence in described abnormal conditions disposal route storehouse, then record the abnormal information that described data mart modeling process occurs, and send warning message by internal gateway.
5. method according to claim 3, is characterized in that, described processing monitoring feedback procedure also comprises:
When judging that the trading volume in described data mart modeling process does not exceed corresponding preset range process time, then determine that described data mart modeling process is normal, and be recorded in process in described data mart modeling process trading volume, beginning and ending time of process, the load of CPU, the computed EMS memory occupation ratio of institute and/or computed disk load.
6. according to the arbitrary described method of claim 3-5, it is characterized in that, also comprise data display process and show monitoring feedback procedure, wherein said displaying monitoring feedback procedure comprises:
Judge in the tables of data adopting different report style to show in described data display process whether gather trading volume consistent, if not, then send warning message by internal gateway;
Wherein, described data display process normally or after the revised data mart modeling process of execution performs in the described data mart modeling process of judgement.
7. data run a batch system, it is characterized in that, comprise the data extraction module for performing data extraction process and perform the extraction monitoring feedback module extracting monitoring feedback procedure, described extraction monitoring feedback module specifically comprises:
Record cell, for described data extraction module at data extraction process time, record extract Business Stream water meter in daily trading volume;
First judging unit, for according to described daily trading volume and historical trading volume, judges whether described data extraction process occurs exception;
Second judging unit, for when judging that described data extraction process is abnormal, judges in the abnormal conditions disposal route storehouse set up in advance, whether have corresponding disposal route according to data pick-up daily record;
First amending unit, for when judging there is corresponding disposal route in described abnormal conditions disposal route storehouse, the disposal route of this correspondence is utilized to revise described data extraction process, and the daily trading volume in the Business Stream water meter again extracted after being recorded in correction.
8. system according to claim 7, is characterized in that, described extraction monitoring feedback module also comprises:
Alarm unit, for when judging the disposal route without correspondence in described abnormal conditions disposal route storehouse, then records described data extraction process and occurs the abnormal date, and send warning message by internal gateway.
9. system according to claim 7, is characterized in that, also comprise the data mart modeling module for performing data process and perform the processing monitoring feedback module that feedback procedure is monitored in processing, described processing monitoring feedback module specifically comprises:
3rd judging unit, for judging whether the trading volume in described data mart modeling process exceeds corresponding preset range process time;
4th judging unit, for when judging that described trading volume exceeds corresponding preset range process time, determine that described data mart modeling process occurs abnormal, and judge in the abnormal conditions disposal route storehouse set up in advance, whether have corresponding disposal route according to data mart modeling daily record;
Second amending unit, during for there being the disposal route of this correspondence in described abnormal conditions disposal route storehouse, utilizes the disposal route of this correspondence to revise described data mart modeling process;
Wherein, described data mart modeling module performs described data mart modeling process described extraction after monitoring feedback module judges the daily trading volume of described data extraction process normally or in the Business Stream water meter again extracted after being recorded in correction.
10. system according to claim 9, is characterized in that, also comprises data display module for performing data display process and for performing the displaying monitoring feedback module showing monitoring feedback procedure, wherein said displaying monitoring feedback module specifically for:
Judge in the tables of data adopting different report style to show in described data display process whether gather trading volume consistent, if not, then send warning message by internal gateway;
Wherein, described data display module judges to perform described data display process after the normal or described data mart modeling module of described data mart modeling process performs revised data mart modeling process at described processing monitoring feedback module.
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106202527A (en) * | 2016-07-22 | 2016-12-07 | 浪潮电子信息产业股份有限公司 | General data warehouse construction method for mobile APP big data analysis |
| CN108694179A (en) * | 2017-04-06 | 2018-10-23 | 北京宸瑞科技股份有限公司 | Personage's view analysis system based on attribute extraction and method |
| CN109766370A (en) * | 2018-12-27 | 2019-05-17 | 口碑(上海)信息技术有限公司 | Data processing method, data service system and equipment |
| CN111078506A (en) * | 2019-12-27 | 2020-04-28 | 中国银行股份有限公司 | Business data batch running task monitoring method and device |
| CN112463541A (en) * | 2020-12-14 | 2021-03-09 | 上海金仕达软件科技有限公司 | Data monitoring method and system |
| CN112819349A (en) * | 2021-02-06 | 2021-05-18 | 建信金融科技有限责任公司 | Monitoring method, device, equipment and medium applied to data processing |
| CN114240109A (en) * | 2021-12-06 | 2022-03-25 | 中电金信软件有限公司 | Method, device and system for cross-region processing batch running task |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8145812B1 (en) * | 2008-07-25 | 2012-03-27 | Gaurang Kavaiya | Line driving and receiving system |
| CN103049321A (en) * | 2012-12-27 | 2013-04-17 | 中国建设银行股份有限公司 | Intelligentized task processing device and intelligentized task processing method |
| CN104615526A (en) * | 2014-12-05 | 2015-05-13 | 北京航空航天大学 | Monitoring system of large data platform |
-
2015
- 2015-12-21 CN CN201510966813.0A patent/CN105573892B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8145812B1 (en) * | 2008-07-25 | 2012-03-27 | Gaurang Kavaiya | Line driving and receiving system |
| CN103049321A (en) * | 2012-12-27 | 2013-04-17 | 中国建设银行股份有限公司 | Intelligentized task processing device and intelligentized task processing method |
| CN104615526A (en) * | 2014-12-05 | 2015-05-13 | 北京航空航天大学 | Monitoring system of large data platform |
Non-Patent Citations (1)
| Title |
|---|
| 孙熙麟: "商业银行经营管理数据仓库系统的设计与实现", 《中国优秀硕士学位论文全文数据库》 * |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106202527A (en) * | 2016-07-22 | 2016-12-07 | 浪潮电子信息产业股份有限公司 | General data warehouse construction method for mobile APP big data analysis |
| CN108694179A (en) * | 2017-04-06 | 2018-10-23 | 北京宸瑞科技股份有限公司 | Personage's view analysis system based on attribute extraction and method |
| CN109766370A (en) * | 2018-12-27 | 2019-05-17 | 口碑(上海)信息技术有限公司 | Data processing method, data service system and equipment |
| CN111078506A (en) * | 2019-12-27 | 2020-04-28 | 中国银行股份有限公司 | Business data batch running task monitoring method and device |
| CN112463541A (en) * | 2020-12-14 | 2021-03-09 | 上海金仕达软件科技有限公司 | Data monitoring method and system |
| CN112819349A (en) * | 2021-02-06 | 2021-05-18 | 建信金融科技有限责任公司 | Monitoring method, device, equipment and medium applied to data processing |
| CN114240109A (en) * | 2021-12-06 | 2022-03-25 | 中电金信软件有限公司 | Method, device and system for cross-region processing batch running task |
| CN114240109B (en) * | 2021-12-06 | 2024-08-20 | 中电金信软件有限公司 | Method, device and system for cross-regional processing of batch running task |
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