CN109993439A - A kind of quality determining method based on government data - Google Patents
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- 238000000034 method Methods 0.000 title claims abstract description 27
- 238000012372 quality testing Methods 0.000 claims abstract description 44
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- 238000004519 manufacturing process Methods 0.000 claims abstract description 4
- 238000012544 monitoring process Methods 0.000 claims description 12
- 238000007689 inspection Methods 0.000 claims description 3
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Abstract
The present invention is more particularly directed to a kind of quality determining methods based on government data.The quality determining method based on government data, quality detected rule is defined in the database, create rule model and distributed mass Detection task, statistical quality testing result after completion quality testing task, alert notification is sent simultaneously to problem owner and superintendent, it scores detection data, and quality of production examining report.The quality determining method based on government data, pass through the detection to data, analysis, alarm, supervise and examine, the efficient works such as scoring and is effectively guaranteed the exact specifications of data, not only can the fast and accurately position of orientation problem data and the reason of problem, the interface operation quickly handled can also be provided, to better understand data, providing support using data, mining data value.
Description
Technical field
The present invention relates to data quality checking technical field, in particular to a kind of quality testing side based on government data
Method.
Background technique
Government data covers the every aspect of social management and public service, and authority with higher.Political affairs at different levels
Mansion knows the data of society 80%, is the largest data owner, and a large amount of data resource is badly in need of government and Society Open, is total to
It enjoys and utilizes.
Government data itself is used as a kind of information resources, and there is the behaviour such as acquisition, processing, analysis, preservation, transmission in the process
Make, wherein the abnormal even mistake of data may be will lead to, and government data must have authoritative and accuracy, and deposit
In industry multiplicity, the feature that data volume is big, variation is fast.Therefore, to the efficient, logical of a large amount of, multifarious government data
Quality testing, problem visualization processing faster, more intuitively recognize data to help government and society, understand data, benefit
It is particularly important with data.
Based on the above situation, the invention proposes a kind of quality determining method based on government data, to data problem into
Row effectively detects, and makes it possible on guaranteeing government data accuracy and normalization, so that government and society are quickly, intuitively
Ground data of finding the problem are possibly realized；Patterned problem data is provided to show and handle, so that in express statistic problem data,
Processing problem data and Monitor Problems disposition are possibly realized.
Summary of the invention
In order to compensate for the shortcomings of the prior art, the present invention provides a kind of quality inspections based on government data being simple and efficient
Survey method.
The present invention is achieved through the following technical solutions:
A kind of quality determining method based on government data, it is characterised in that: in the database to quality detected rule into
Row definition, creates rule model and distributed mass Detection task, completes statistical quality testing result after quality testing task, to
Problem owner and superintendent send alert notification simultaneously, score detection data, and quality of production examining report.
The present invention is based on the quality determining methods of government data to monitor Druid using Druid Database Connection Pool
Database connection pool connects pond and SQL executive condition, and the connection and release called every time guarantee the reasonable utilization of resources；Meanwhile it building
A vertical big database SQL generates factory, selects corresponding factory according to the type of data source in quality testing task execution,
Guarantee normally to execute under different databases.
To avoid repeating monitoring, setting time pointer offset and maximum monitoring in data monitoring, to be rapidly completed
Quality testing task.
The quality testing rule includes data meta-rule and general rule, and the data meta-rule needs corresponding government
The support of platform data standards service；The general rule defines the type of SQL type and regular expression, passes through SQL type
It realizes the support to multiple data sources, the rule of multiple data sources is configured and is managed collectively；It is selected in quality testing
The quality testing rule of respective type is handled, and then dynamically realizes the configuration of data source, for later extension provides branch
It holds.
The quality testing task uses lightweight distributed task management scheme, to realize the load balancing of multitask；
After the quality testing task is assigned to actuator, quality testing task is executed by control centre's triggering actuator；The scheduling
Center is based on cluster Quartz and realizes and support clustered deploy(ment), and the actuator supports clustered deploy(ment)；When having on new actuator
Line or it is offline when, redistribute task；The lightweight distributed task management scheme can reduce single server hardware
The pressure of demand and server, while can go wrong to avoid some server and influence the detection of the quality of data.
The quality testing task is distributed to each actuator according to the routing mode of each self-configuring respectively；The actuator
Clustered deploy(ment), is periodically automatically registered to control centre, and control centre finds the quality testing task of registration automatically and triggers
It executes.
It supports to be manually entered actuator address in the control centre.
The routing mode includes selection first, the last one, poll or failure transfer, each quality testing task are matched
Set a kind of routing mode.
The beneficial effects of the present invention are: being somebody's turn to do the quality determining method based on government data, by the detection to data, divide
Analysis alerts, supervise and examine, and the efficient works such as scoring and the exact specification that data are effectively guaranteed not only can fast and accurately be determined
The reason of position of position problem data and problem, moreover it is possible to the interface operation quickly handled is provided, to better understand data, benefit
Support is provided with data, mining data value.
Specific embodiment
In order to which technical problems, technical solutions and advantages to be solved are more clearly understood, tie below
Embodiment is closed, the present invention will be described in detail.It should be noted that specific embodiment described herein is only to explain
The present invention is not intended to limit the present invention.
Due to consuming in memory, resource is big and execution speed is slow, the quality determining method based on government data, in number
Quality detected rule is defined according in library, creates rule model and distributed mass Detection task, quality testing is completed and appoints
Statistical quality testing result after business sends alert notification simultaneously to problem owner and superintendent, scores detection data,
And quality of production examining report.
The quality determining method based on government data monitors Druid data using Druid Database Connection Pool
Library connection pool connects pond and SQL (Structured Query Language, structured query language) executive condition, calls every time
Connection and release, guarantee the reasonable utilization of resources；Meanwhile establishing a big database SQL and generating factory, in quality testing
Corresponding factory is selected according to the type of data source when task execution, guarantees normally to execute under different databases.
Druid database connection pool replaces DBCP and C3P0, provides that one efficient, powerful, scalability is good
Database connection pool has the function of:
(1) a powerful StatFilter plug-in unit is provided built in Druid database connection pool, can be united in detail
The execution performance for counting SQL, can be helpful for on-line analysis database access performance with monitoring data library access performance.
(2) DruidDruiver and DruidDataSource supports PasswordCallback, supports database password
Encryption, can ensure data safety.
(3) SQL execution journal is supported, Druid database connection pool provides different LogFilter, can support
Common-Logging, Log4j and JdkLog, user select corresponding LogFilter as needed, and the database for monitoring application is visited
Ask situation.
(4) extension JDBC is supported, when (Java Data Base Connectivity, java database connects user to JDBC
Connecing) layer when having requirement of programming, can easily write by the Filter filter mechanism that Druid database connection pool provides
JDBC layers of expansion plugin.
To avoid repeating monitoring, setting time pointer offset and maximum monitoring in data monitoring, to be rapidly completed
Quality testing task.
The quality testing rule includes data meta-rule and general rule, and the data meta-rule needs corresponding government
The support of platform data standards service；The general rule defines the type of SQL type and regular expression, passes through SQL type
It realizes the support to multiple data sources, the rule of multiple data sources is configured and is managed collectively；It is selected in quality testing
The quality testing rule of respective type is handled, and then dynamically realizes the configuration of data source, for later extension provides branch
It holds.
The correctness of detection data member, whether data are accurate, specification, are completely the important contents of quality of data monitoring.Number
It is several for being also known as data type by a series of data cell of attribute descriptions such as definition, mark, expression and permissible value according to member
According to not subdivisible minimum data unit.
All there is some specific data elements for all trades and professions in government data.Such as: " student's classification " is exactly a number
According to member, in store proprietary educational information in government, data volume is very big, depends merely on people to examine being unpractical.At this point it is possible to
To the data meta-rule of data selection " student's classification ", then all data are screened, when student's classification letter in data
Breath does not meet the standard of " student's classification " data element, will be screened out.
The quality testing task uses lightweight distributed task management scheme, to realize the load balancing of multitask；
After the quality testing task is assigned to actuator, quality testing task is executed by control centre's triggering actuator；The scheduling
Center is based on cluster Quartz and realizes and support clustered deploy(ment), and the actuator supports clustered deploy(ment)；When having on new actuator
Line or it is offline when, redistribute task；The lightweight distributed task management scheme can reduce single server hardware
The pressure of demand and server, while can go wrong to avoid some server and influence the detection of the quality of data.
In design and exploitation, extended in line with easy, decoupling and pluggable thinking, when adding a kind of database, no
Big variation can be carried out to code.
The quality testing task is distributed to each actuator according to the routing mode of each self-configuring respectively；The actuator
Clustered deploy(ment), is periodically automatically registered to control centre, and control centre finds the quality testing task of registration automatically and triggers
It executes.
It supports to be manually entered actuator address in the control centre.
The routing mode includes selection first, the last one, poll or failure transfer, each quality testing task are matched
Set a kind of routing mode.
The quality determining method based on government data provides a kind of problem number based on the information of government's catalogue data
It is investigated that data are carried out multi-faceted effective detection, including data element detection, specification at a station interface by the method looked for
Property, consistency, the detection of accuracy.It is specific comprising regular definition, quality model, quality checks, problem alerts, quality analysis,
A series of complete treatment processes such as quality supervise and examine, quality report.In face of the open data of a large amount of, multifarious government, lead to
Quality testing scheme is faster more intuitively recognized help government data with society, understands data, provided using data
Guidance, not only can the fast and accurately position of orientation problem data and the reason of problem, moreover it is possible to which the boundary quickly handled is provided
Face operation.
Meanwhile it being somebody's turn to do the quality determining method based on government data, more increased based on processing in the database than in memory
Effect, while current general all data source types have been compatible with, it is more convenient to use extensive；And in order to which fast and stable is efficient
Statistics, we use the technology of distributed task scheduling, reduce the pressure of server end and ensure that when server needs
It can also guarantee the normal execution of other server tasks when safeguarding or paralysing.
Complete quality testing task, filtering out problem data is the first step, user it should be understood that data overall condition,
And handle in time, it is necessary to the classified statistic of various dimensions be presented to problem data；Such as the type of rule criterion, it is currently used
Rule, the department to go wrong, the trend etc. of problem；To problem owner and superintendent be simultaneously emitted by problem alarm can and
When notification data author timely handled, the quality supervise and examine personnel of specified permission can carry out tracking to problem and examine
It looks into, guarantees that data are timely handled；Quality testing report may be implemented to summarize data, facilitate storage and access, from
And realize the closed loop to issue handling.
Claims (8)
1. a kind of quality determining method based on government data, it is characterised in that: carried out in the database to quality detected rule
Definition creates rule model and distributed mass Detection task, completes statistical quality testing result after quality testing task, Xiang Wen
Topic person liable and superintendent send alert notification simultaneously, score detection data, and quality of production examining report.
2. the quality determining method according to claim 1 based on government data, it is characterised in that: use Druid data
Library connection pool realizes that monitoring Druid database connection pool connects pond and SQL executive condition, and the connection and release called every time guarantee
The reasonable utilization of resources；Meanwhile establishing a big database SQL and generating factory, in quality testing task execution according to number
Corresponding factory is selected according to the type in source, guarantees normally to execute under different databases.
3. the quality determining method according to claim 2 based on government data, it is characterised in that: to avoid repeating supervising
It surveys, setting time pointer offset and maximum monitoring in data monitoring, so that a quality testing task is rapidly completed.
4. the quality determining method according to claim 1 or 3 based on government data, it is characterised in that: the quality inspection
Gauge then includes data meta-rule and general rule, and the data meta-rule needs corresponding government's platform data standards service
It supports；The general rule defines the type of SQL type and regular expression, is realized by SQL type to multiple data sources
It supports, the rule of multiple data sources is configured and is managed collectively；The quality testing of respective type is selected in quality testing
Rule is handled, and then dynamically realizes the configuration of data source, for later extension provides support.
5. the quality determining method according to claim 1 or 3 based on government data, it is characterised in that: the quality inspection
Survey task uses lightweight distributed task management scheme, to realize the load balancing of multitask；The quality testing task point
After being fitted on actuator, quality testing task is executed by control centre's triggering actuator；The control centre is based on cluster Quartz
Realize and support clustered deploy(ment), the actuator supports clustered deploy(ment)；When there is new actuator online or offline, divide again
With task；The lightweight distributed task management scheme can reduce the pressure of single server hsrdware requirements and server,
Can go wrong simultaneously to avoid some server influences the detection of the quality of data.
6. the quality determining method according to claim 5 based on government data, it is characterised in that: the quality testing is appointed
Business is distributed to each actuator according to the routing mode of each self-configuring respectively；The actuator clustered deploy(ment), it is periodically automatic
It is registered to control centre, control centre finds the quality testing task of registration automatically and triggers execution.
7. the quality determining method according to claim 6 based on government data, it is characterised in that: control centre's branch
It holds and is manually entered actuator address.
8. the quality determining method according to claim 6 based on government data, it is characterised in that: the routing mode packet
Containing selection first, the last one, poll or failure transfer, each quality testing task configures a kind of routing mode.
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110597798A (en) * | 2019-09-17 | 2019-12-20 | 山东爱城市网信息技术有限公司 | Data detection method based on Thrift |
| CN110704502A (en) * | 2019-11-20 | 2020-01-17 | 中电万维信息技术有限责任公司 | Componentized data quality checking method |
| CN111563074A (en) * | 2020-04-28 | 2020-08-21 | 厦门市美亚柏科信息股份有限公司 | Data quality detection method and system based on multi-dimensional label |
| CN112948365A (en) * | 2021-03-04 | 2021-06-11 | 浪潮云信息技术股份公司 | Data quality detection method based on intelligent data element matching |
| CN114066170A (en) * | 2021-10-22 | 2022-02-18 | 广西贵港市中科曙光云计算有限公司 | Government data open sharing-oriented problem feedback processing system and method |
| CN115941563A (en) * | 2023-03-14 | 2023-04-07 | 湖南智芯微科技有限公司 | Task monitoring method and device integrating information of multiple command platforms |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP1894151A2 (en) * | 2005-06-20 | 2008-03-05 | Future Route Limited | Analytical system for discovery and generation of rules to predict and detect anomalies in data and financial fraud |
| CN106201694A (en) * | 2016-07-13 | 2016-12-07 | 北京农信互联科技有限公司 | Configuration method and system for executing timing task under distributed system |
| CN107038162A (en) * | 2016-02-03 | 2017-08-11 | 滴滴（中国）科技有限公司 | Real time data querying method and system based on database journal |
| CN107958049A (en) * | 2017-11-28 | 2018-04-24 | 航天科工智慧产业发展有限公司 | A kind of quality of data checking and administration system |
| CN109491990A (en) * | 2018-09-17 | 2019-03-19 | 武汉达梦数据库有限公司 | A kind of method of detection data quality and the device of detection data quality |
-
2019
- 2019-04-02 CN CN201910261220.2A patent/CN109993439A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP1894151A2 (en) * | 2005-06-20 | 2008-03-05 | Future Route Limited | Analytical system for discovery and generation of rules to predict and detect anomalies in data and financial fraud |
| CN107038162A (en) * | 2016-02-03 | 2017-08-11 | 滴滴（中国）科技有限公司 | Real time data querying method and system based on database journal |
| CN106201694A (en) * | 2016-07-13 | 2016-12-07 | 北京农信互联科技有限公司 | Configuration method and system for executing timing task under distributed system |
| CN107958049A (en) * | 2017-11-28 | 2018-04-24 | 航天科工智慧产业发展有限公司 | A kind of quality of data checking and administration system |
| CN109491990A (en) * | 2018-09-17 | 2019-03-19 | 武汉达梦数据库有限公司 | A kind of method of detection data quality and the device of detection data quality |
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110597798A (en) * | 2019-09-17 | 2019-12-20 | 山东爱城市网信息技术有限公司 | Data detection method based on Thrift |
| CN110597798B (en) * | 2019-09-17 | 2023-08-25 | 浪潮卓数大数据产业发展有限公司 | Data detection method based on thread |
| CN110704502A (en) * | 2019-11-20 | 2020-01-17 | 中电万维信息技术有限责任公司 | Componentized data quality checking method |
| CN111563074A (en) * | 2020-04-28 | 2020-08-21 | 厦门市美亚柏科信息股份有限公司 | Data quality detection method and system based on multi-dimensional label |
| CN111563074B (en) * | 2020-04-28 | 2022-05-31 | 厦门市美亚柏科信息股份有限公司 | Data quality detection method and system based on multi-dimensional label |
| CN112948365A (en) * | 2021-03-04 | 2021-06-11 | 浪潮云信息技术股份公司 | Data quality detection method based on intelligent data element matching |
| CN114066170A (en) * | 2021-10-22 | 2022-02-18 | 广西贵港市中科曙光云计算有限公司 | Government data open sharing-oriented problem feedback processing system and method |
| CN115941563A (en) * | 2023-03-14 | 2023-04-07 | 湖南智芯微科技有限公司 | Task monitoring method and device integrating information of multiple command platforms |
| CN115941563B (en) * | 2023-03-14 | 2023-05-02 | 湖南智芯微科技有限公司 | Task monitoring method and device integrating multi-command platform information |
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Application publication date: 20190709 |