CN102722582B - System and method for integrating data on basis of reverse clearing - Google Patents
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Abstract
The invention provides a system and a method for integrating data on the basis of reverse clearing. The system for integrating data on the basis of reverse clearing comprises a data integrating module and a reverse clearing module, wherein the data integrating module is used for extracting, clearing source data from data sources, transforming and loading the source data into effective data for being called by an application platform, and the reverse clearing module is used for modifying errors and updating the source data according to the effective data. The method includes two main steps: data integrating and reverse clearing. The data integrating step includes extracting, clearing the source data from the data sources, transforming and loading the source data into effective data for being called by the application platform. The reverse clearing step includes modifying errors and updating the source data according to the effective data. By the aid of the system and the method for integrating the data on the basis of reverse clearing, reverse modification of the source data can be realized while integrating the data.
Description
Technical field
The present invention relates to Data Integration field, particularly a kind of integration system of multi-source heterogeneous data and method.
Background technology
One of implementation of current the integrating technology of heterogeneous digital resources is data warehousing pattern.Data warehousing pattern is extracted data from one or more data source, and carries out necessary process to data, and data are stored in target data warehouse the most at last.Data model storage generally adopts the form of ETL (Extract, Transform, Load) and data warehouse.ETL process comprises data pick-up, data conversion and Data import.ETL be responsible for by distribution, data pick-up in heterogeneous data source carries out cleaning and changing behind interim middle layer, be finally loaded in data warehouse or Data Mart.Although the at present research at home and abroad of ETL process belongs to relative maturity period, still there is following weak point in isomeric data integration process:
(1) traditional the integrating technology of heterogeneous digital resources be based on ETL process, data are extracted, integrated, cleaning and load.Data be updated to regular periodicity, user must set a time interval value in a program and specify every how long once reading, and its cycle longer real-time is lower, which results in the non real-time problem of data.
(2) if source data derives from enterprises, so the quality of data other application to enterprise of source data are also considerable.The quality of data is important field of research during isomeric data is integrated, and can its height affect user and formulate correct decision-making, and when data have high-quality, the effective information resource produced enterprise also can be high-quality.But traditional ETL process only has the use to source data, does not oppositely revise source data, can not improve and ensure the quality of source data, this is unfavorable for data call between enterprises different platform, shares, data are unified and Data Update.At present, the ripe effective model of neither one is gone back to the feedback of data source misdata and amendment.
Summary of the invention
The object of the invention is to provide a kind of data integrated system based on reverse cleaning and the method that can carry out reverse correction to source data, to solve in traditional ETL process the technical matters of Quality advance and the correction lacked source data.
For achieving the above object, the invention provides a kind of data integrated system based on reverse cleaning, it is characterized in that, comprising:
Data Integration module, for being undertaken source data extracting, clean, change and being loaded as valid data for application platform invoke from data source;
Reverse cleaning module, for according to described valid data, carries out error correction and renewal to described source data.
Further, described Data Integration module comprises:
Adaptation unit, for carrying out adaptation according to adaptation rule to the source data of having resolved in internal memory, is left ephemeral data by the source data meeting adaptation rule;
Temporary storage cell, for extracting the described ephemeral data from described adaptation unit;
Cleaning rule unit, for cleaning according to the cleaning rule of design the ephemeral data in described temporary storage cell and change;
Valid data storage unit, for storing the valid data after described cleaning rule unit cleaning and conversion;
History data store unit, preserves the described ephemeral data in described temporary storage cell for timing and empties described temporary storage cell.
Further:
Described adaptation unit and described data source one_to_one corresponding, the quantity of described data source is multiple, and the data structure of multiple data source is different.
Described adaptation unit place is provided with monitoring thread, and described monitoring thread monitors the timestamp of the source data from described data source in real time, and vicissitudinous for update time source data is resolved to internal memory;
Be provided with in described cleaning rule unit and clean thread in real time, when described real-time cleaning thread finds that the described ephemeral data in described temporary storage cell increases, continue to clean the described ephemeral data in temporary storage cell and change from the end position that last time reads data, the valid data real-time storage obtained is in described valid data storage unit.
Present invention also offers a kind of data integration method based on reverse cleaning, comprise the following steps:
Data Integration: source data carried out extracting from data source, clean, change and be loaded as valid data for application platform invoke;
Reverse cleaning: according to described valid data, carries out error correction and renewal to described source data.
In above-mentioned method, described Data Integration specifically comprises the following steps:
101, according to adaptation rule, adaptation is carried out to the source data of having resolved in internal memory, the source data meeting adaptation rule is left ephemeral data and stores;
102, clean according to the cleaning rule of design described ephemeral data and change, the valid data after being cleaned and changing also are preserved;
103, timing using ephemeral data as storage of history data P.
In above-mentioned method, before described step 101, monitoring is from the timestamp of the source data of data source in real time, and vicissitudinous for update time source data is resolved to internal memory.
In above-mentioned method, in described step 102, also comprise step: when described ephemeral data increases, continue to clean ephemeral data and change, the valid data real-time storage obtained from the end position that last time reads data.
In above-mentioned method, described reverse cleaning specifically comprises the following steps:
201, set up Data Source tree: read source data and mark, set up Data Source tree according to data cleansing process;
202, data query source: after platform data is modified, obtains relevant Data Source tree, reverse primary source and the source data finding the data be modified;
203, source data is cleared up: according to the platform data after being modified or target data described source data revised and upgrade.
The present invention has following beneficial effect:
1, the data integrated system based on reverse cleaning of the present invention, realize the Data Integration of different platform by Data Integration module and call, and while Data Integration, reverse cleaning module is adopted to carry out error correction and renewal according to platform data to source data, can mate automatically the mistake in source data and repair, ensure and improve the quality of source data, perfect ETL process.
2, the data integrated system based on reverse cleaning of the present invention, the renewal of the real-time monitor source data of energy and change, and the data of these renewals and change are cleaned in real time and preserved, real-time update and the loading of valid data can be completed.
3, the data integration method based on reverse cleaning of the present invention, can carry out renewal and the loading of valid data in real time according to the timestamp change of source data; Utilize band mark Data Source tree structure, the primary source of platform data can be searched out fast, than direct inquire about in the source data of magnanimity more efficient; And can mate automatically the mistake in source data and repair, perfect ETL process.
Except object described above, feature and advantage, the present invention also has other object, feature and advantage.Below with reference to figure, the present invention is further detailed explanation.
Accompanying drawing explanation
The accompanying drawing forming a application's part is used to provide a further understanding of the present invention, and schematic description and description of the present invention, for explaining the present invention, does not form inappropriate limitation of the present invention.In the accompanying drawings:
Fig. 1 is the data integrated system structural representation based on reverse cleaning of the preferred embodiment of the present invention;
Fig. 2 is the reverse cleanup step schematic flow sheet of the preferred embodiment of the present invention.
Embodiment
Below in conjunction with accompanying drawing, embodiments of the invention are described in detail, but the multitude of different ways that the present invention can be defined by the claims and cover is implemented.
See Fig. 1, the data integrated system based on reverse cleaning of the present invention, comprises following two large modules:
1, Data Integration module, for being undertaken source data extracting, clean, change and being loaded as valid data for application platform invoke from data source;
2, reverse cleaning module, for according to valid data, carries out error correction and renewal to source data.
In this preferred implementation, see Fig. 1, Data Integration module comprises:
(1) adaptation unit, for carrying out adaptation according to adaptation rule to the source data of having resolved in internal memory, is left ephemeral data by the source data meeting adaptation rule.As shown in Figure 1, different (as: the database such as structurized MySql, Oracle of data structure of multiple data source, semi-structured Html, Xml and non-structured text, Excel etc.), each data source one_to_one corresponding has an adaptation unit, adaptation unit place is provided with monitoring thread (I/O for data source and adaptation unit place flows), monitoring thread monitors the timestamp of the source data from data source in real time, and vicissitudinous for update time source data is resolved to internal memory, after adaptation, write temporary storage cell.Such design ensure that the real-time update of data in temporary storage cell, decreases source data change to the impact returning user's result set.
(2) temporary storage cell, for extracting the ephemeral data from adaptation unit.Because adaptation unit constantly checks Data Update, so the data in temporary storage cell are also constantly update.
(3) cleaning rule unit, for cleaning according to the cleaning rule of design the ephemeral data in temporary storage cell and change.Cleaning rule formulates according to concrete business rule, plays the effects such as the coupling to data, cleaning, filtration and conversion.Mate the rule in cleaning rule table one by one by the data in temporary storage cell, the data of imperfect, mistake, redundancy are after the screening cleaning of rule, and quality can be improved.The efficiency of Data Integration and the quality of data depend on the design of cleaning rule to a great extent.
Be provided with in cleaning rule unit and clean thread in real time, when real-time cleaning thread finds that the ephemeral data in temporary storage cell increases, continue to clean the ephemeral data in temporary storage cell and change from the end position that last time reads data, the valid data real-time storage obtained is in valid data storage unit.
(4) valid data storage unit, for storing the valid data after the cleaning of cleaning rule unit and conversion, the quality data namely finally obtained.When application platform transmitting system request access, request results can be returned to application platform (in application layer according to request content with the form of Xml by valid data storage unit, comprise various application platform system, target platform can be integrated in the heart in calling data by Web after valid data), result set returns to user the most at last.
(5) history data store unit, preserves the ephemeral data in temporary storage cell for timing and empties temporary storage cell.So, newer data are always stored in temporary storage cell.
In above-mentioned steps, monitoring thread and in real time cleaning thread match, real-time data data source upgraded can be realized through extracting, cleaning and be carried in valid data storage unit, this ensure that the real-time update of data in temporary storage cell, and decrease source data change to the impact returning user's result set; Meanwhile, incremental data, once change, just can be passed through the real-time effective data storage cell of write of cleaning, for the data base call of application platform by data in data source.
After above-mentioned steps, source data (comprises existing DB database, Xml, Txt, Excel etc., also the data directly obtained from network are had) be kept in valid data storage unit after integrating, when user is with web service form request application platform, application platform is immediately to data center's transmitting system request, valid data storage unit is called in xml schema mode, the result of inquiry is returned application platform with xml document form by valid data storage unit, result set is returned user by the database of last application platform, meets consumers' demand.
The above-mentioned data integrated system based on reverse cleaning can realize the data integration method based on reverse cleaning of the present invention, comprises the following steps:
(1) Data Integration: source data carried out extracting from data source, clean, change and be loaded as valid data for application platform invoke.Its concrete steps are as follows:
(101) monitoring is in real time from the timestamp of the source data of data source, and vicissitudinous for update time source data is resolved to internal memory.According to adaptation rule, adaptation is carried out to the source data of having resolved in internal memory, the source data meeting adaptation rule is left ephemeral data and stores.
(102) to clean ephemeral data according to the cleaning rule of design and change, the valid data after being cleaned and changing also are preserved; When ephemeral data increases, continue to clean ephemeral data and change, the valid data real-time storage obtained from the end position that last time reads data.
(103) timing using ephemeral data as storage of history data P.
(2) reverse cleaning: according to valid data, carries out error correction and renewal to source data, realizes referring to the quality data after according to cleaning, to the process that imperfect, the misdata in source data corrects.As shown in Figure 2, its concrete steps are as follows:
(201) set up Data Source tree: read source data and mark, set up Data Source tree according to data cleansing process.Data Source sets the whole history described data processing, comprises the origin of data and processes all follow-up process of these data.Its concrete process of establishing is as follows:
A. in temporary storage cell, add mark row, during ephemeral data write temporary storage cell, the position of data and data is stored in this row, as the bottom leaf node for tree.Each leaf node have recorded two, the position key element of data and data.
B. when effective storage unit produces new data, record these valid data and by which leaf node produced, the position of these data and data is considered as node and is kept in the last layer of leaf node;
C. when data carry out incremental update, if the data in effective storage unit change, then the position of new Data Data and data is continued to be considered as last layer node and be kept in tree;
D., after data are by platform invoke, this platform data is kept at (being generally top mode) in tree as the last layer node set;
E. the rest may be inferred, until data are no longer updated or call, terminates the foundation to tree node, thinks that this Data Source number has been set up.
(202) data query source: after platform data is modified (amended data are designated as " data set A "), obtain relevant Data Source tree, reverse primary source and the source data finding the data be modified fast.
(203) source data is cleared up: according to the platform data after being modified or target data source data revised and upgrade.Be specially:
A. the platform data on Match Tree summit and the source data of the bottom;
If b. inconsistent, then upgrade by the source data of platform data to the bottom on summit and save as the source data after reparation.
To sum up, this preferred implementation has following three important features:
(1) utilize adaptation unit, monitoring thread to judge that the mode of timestamp realizes the real-time update of data, and the ephemeral data of increase is carried out in real time clean and conversion process by cleaning thread in real time, make the real-time of valid data and platform data better.
(2) structure utilizing Data Source to set finds the primary source of data fast, is beneficial to the unification realizing data, convenient and efficient.
(3) utilize the mistake in reverse scale removal process reparation source data, improve the quality of source data, make ETL process more perfect.
The foregoing is only the preferred embodiments of the present invention, be not limited to the present invention, for a person skilled in the art, the present invention can have various modifications and variations.Within the spirit and principles in the present invention all, any amendment done, equivalent replacement, improvement etc., all should be included within protection scope of the present invention.
Claims (5)
1. based on a data integrated system for reverse cleaning, it is characterized in that, for the integration of multi-source heterogeneous data, comprising:
Data Integration module, for being undertaken source data extracting, clean, change and being loaded as valid data for application platform invoke from data source;
Reverse cleaning module, for according to described valid data, carries out error correction and renewal to described source data;
Described reverse cleaning module comprises:
Set up Data Source tree unit: read source data and mark, set up Data Source tree according to data cleansing process;
Data query carrys out source unit: after platform data is modified, and obtains relevant Data Source tree, reverse primary source and the source data finding the data be modified;
Cleaning source data units: according to the platform data after being modified or target data described source data revised and upgrade, being specially: the platform data on Match Tree summit and the source data of the bottom; If inconsistent, then upgrade by the source data of platform data to the bottom of treetop point and save as the source data after reparation;
Described Data Integration module comprises:
Adaptation unit, for carrying out adaptation according to adaptation rule to the source data of having resolved in internal memory, is left ephemeral data by the source data meeting adaptation rule; Wherein, described adaptation unit and described source data one_to_one corresponding, the quantity of described source data is multiple, and the structure of multiple described source data is different;
Temporary storage cell, for extracting the described ephemeral data from described adaptation unit;
Cleaning rule unit, for cleaning according to the cleaning rule of design the described ephemeral data in described temporary storage cell and change;
Valid data storage unit, for storing the valid data after described cleaning rule unit cleaning and conversion;
History data store unit, preserves the described ephemeral data in described temporary storage cell for timing and empties described temporary storage cell.
2. the data integrated system based on reverse cleaning according to claim 1, it is characterized in that, described adaptation unit place is provided with monitoring thread, and described monitoring thread monitors the timestamp of the source data from described data source in real time, and vicissitudinous for update time source data is resolved to internal memory;
Be provided with in described cleaning rule unit and clean thread in real time, when described real-time cleaning thread finds that the described ephemeral data in described temporary storage cell increases, continue to clean the described ephemeral data in described temporary storage cell and change from the end position that last time reads data, the valid data real-time storage obtained is in described valid data storage unit.
3. based on a data integration method for reverse cleaning, it is characterized in that, for the integration of multi-source heterogeneous data, comprise the following steps:
Data Integration: source data carried out extracting from data source, clean, change and be loaded as valid data for application platform invoke;
Reverse cleaning: according to described valid data, carries out error correction and renewal to described source data;
Described reverse cleaning specifically comprises the following steps:
201, set up Data Source tree: read source data and mark, set up Data Source tree according to data cleansing process;
202, data query source: after platform data is modified, obtains relevant Data Source tree, reverse primary source and the source data finding the data be modified;
203, source data is cleared up: according to the platform data after being modified or target data described source data revised and upgrade, being specially: the platform data on Match Tree summit and the source data of the bottom; If inconsistent, then upgrade by the source data of platform data to the bottom of treetop point and save as the source data after reparation;
Described Data Integration specifically comprises the following steps:
101, according to adaptation rule, adaptation is carried out to the source data of having resolved in internal memory, the source data meeting adaptation rule is left ephemeral data and stores; Wherein, described source data is multiple, and the structure of multiple described source data is different;
102, clean according to the cleaning rule of design described ephemeral data and change, the valid data after being cleaned and changing also are preserved;
103, timing using described ephemeral data as storage of history data P.
4. the data integration method based on reverse cleaning according to claim 3, is characterized in that, before described step 101, monitoring is from the timestamp of the source data of data source in real time, and vicissitudinous for update time source data is resolved to internal memory.
5. the data integration method based on reverse cleaning according to claim 4, it is characterized in that, in described step 102, also comprise step: when described ephemeral data increases, continue to clean described ephemeral data and change, the valid data real-time storage obtained from the end position that last time reads data.
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| CN103036736B (en) * | 2012-11-30 | 2015-09-23 | 航天恒星科技有限公司 | A kind of configuration equipment monitoring system based on data source and method |
| CN103177094B (en) * | 2013-03-14 | 2017-02-22 | 成都康赛信息技术有限公司 | Cleaning method of data of internet of things |
| CN105183911A (en) * | 2015-10-12 | 2015-12-23 | 国家电网公司 | Data source binary tree based source tracing method for abnormal data of power system |
| CN105447083A (en) * | 2015-11-06 | 2016-03-30 | 深圳市中润四方信息技术有限公司 | Data convergence and divergence method and system for multi-source heterogeneous database |
| CN105488222A (en) * | 2015-12-24 | 2016-04-13 | 广州精点计算机科技有限公司 | Data source retrospective tracing method and device |
| CN108052574A (en) * | 2017-12-08 | 2018-05-18 | 南京中新赛克科技有限责任公司 | Slave ftp server based on Kafka technologies imports the ETL system and implementation method of mass data |
| CN108062387A (en) * | 2017-12-14 | 2018-05-22 | 国网陕西省电力公司电力科学研究院 | A kind of real time data cleaning and conversion method towards TAS systems |
| CN110019477A (en) * | 2017-12-27 | 2019-07-16 | 航天信息股份有限公司 | A kind of method and system carrying out big data processing using HIVE backup table |
| CN108628931B (en) * | 2018-03-15 | 2022-08-30 | 创新先进技术有限公司 | Method, device and equipment for data driving service |
| CN109614205A (en) * | 2018-10-18 | 2019-04-12 | 阿里巴巴集团控股有限公司 | A kind of method for processing business, device, equipment and system |
| CN110348647B (en) * | 2019-01-21 | 2020-11-03 | 罗斌 | Global trade big data intelligent analysis system and method |
| CN110569238B (en) * | 2019-09-12 | 2023-03-24 | 成都中科大旗软件股份有限公司 | Data management method, system, storage medium and server based on big data |
| CN112667615B (en) * | 2020-12-25 | 2022-02-15 | 广东电网有限责任公司电力科学研究院 | Data cleaning system and method |
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