CN101799807A - Heterogeneous data table merging method and system thereof - Google Patents
Heterogeneous data table merging method and system thereof Download PDFInfo
- Publication number
- CN101799807A CN101799807A CN200910077659A CN200910077659A CN101799807A CN 101799807 A CN101799807 A CN 101799807A CN 200910077659 A CN200910077659 A CN 200910077659A CN 200910077659 A CN200910077659 A CN 200910077659A CN 101799807 A CN101799807 A CN 101799807A
- Authority
- CN
- China
- Prior art keywords
- data
- data recording
- map
- key
- value
- 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
Images
Landscapes
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
The invention discloses a heterogeneous data table merging method and a system thereof. The method comprises the following steps: respectively allocating table marks for a plurality of heterogeneous data tables; adding the table marks into all data records in the corresponding data tables; merging the data records with the same keyword field values and different table marks into a novel data record according to the set keyword fields; deleting the table marks in the novel data record; and storing the data record with the deleted table mark into a novel data table. The invention can be used for realizing the data merging processing of the heterogeneous data table, and can improve the efficiency of the data merging operation.
Description
Technical field
The present invention relates to the data mining technology in the communications field, relate in particular to a kind of merging method and system thereof of heterogeneous data table.
Background technology
Data mining from real application data a large amount of, incomplete, noisy, fuzzy, at random, extract lie in wherein, people do not know in advance but be the information of potentially useful and the process of knowledge.
Existing data digging flow comprises: data pre-service (ETL), data mining algorithm are realized, the result shows three key steps.Wherein, by the ETL step, can carry out pre-service to obtain data to be excavated to source data; By the data mining algorithm performing step, can realize that the data mining algorithm that satisfies service needed draws analysis result; Show step by the result, the result of data mining algorithm can be showed the user.
ETL operation comprises heterogeneous data table is merged processing.Because data may derive from different Database Systems, and existing Map/Reduce (mapping/simplification) mechanism can not adopt the data merging mode of traditional heterogeneous database system to carry out the data merging, therefore, press for a kind of data merging method of the Map/Reduce of being applicable to mechanism.
Summary of the invention
The embodiment of the invention provides a kind of merging method and system thereof of heterogeneous data table, to realize the merging of the heterogeneous data table under the Map/Reduce mechanism.
The merging method of the isomeric data that the embodiment of the invention provides comprises:
Be a plurality of heterogeneous data tables difference allocation table signs, and table is identified all data recording of adding in the corresponding data table;
According to the key field that is provided with, will have the same keyword field value but data recording with different table marks is merged into new data recording, and the table sign in will the be described new data recording is deleted;
The data recording of having deleted the table sign is stored in the new tables of data.
The heterogeneous data table combination system that the embodiment of the invention provides comprises:
Table identification distribution unit is used to a plurality of heterogeneous data tables allocation table sign respectively, and table is identified all data recording of adding in the corresponding data table;
The data merge cells, be used for according to the key field that is provided with, the data recording that will have the same keyword field value but have a different table marks is merged into new data recording, with the deletion of the sign of the table in the described new data recording, and the data recording that will delete the table sign stores in the new tables of data.
The above embodiment of the present invention, by distribute different table signs for heterogeneous data table, and the data recording of adding in the tables of data will be shown to identify, make and when the data record is carried out the data merging, can identify the data recording that will derive from the different pieces of information table according to the table in this data recording and merge.
Description of drawings
Fig. 1 is that the tables of data in the embodiment of the invention merges schematic flow sheet;
Fig. 2 is that the tables of data that adopts Map/Reduce mechanism to realize in the embodiment of the invention merges schematic flow sheet;
Fig. 3 is the structural representation of the tables of data combination system in the embodiment of the invention.
Embodiment
Below in conjunction with accompanying drawing the embodiment of the invention is described in detail.
Referring to Fig. 1, the tables of data that provides for the embodiment of the invention merges the synoptic diagram of flow process, and this flow process comprises step:
In this step, with 2 heterogeneous data tables (table 1 and table 2) is example, and the table that distributes for table 1 is designated flag1, and the table that distributes for table 2 is designated flag2, and flag1 added in all data recording in the table 1, flag2 is added in all data recording in the table 2.The operation of adding the table sign can be by increasing the table identification field in tables of data, and write respective table in the table identification field and identify and realize.
Above-mentioned flow process can adopt Map/Reduce mechanism to realize.Map/Reduce is the programming mode of a distributed treatment mass data collection, can allow Automatic Program be distributed to concurrent execution on the super large cluster of being made up of common machines by this mechanism.The embodiment of the invention can be by calling map function processing＜key, value〉(key/value) right, by calling the value part that the reduce function merges all middle key assignments centerings with identical key value.When adopting Map/Reduce mechanism, above-mentioned flow process can be as shown in Figure 2:
Step 202, generate a plurality of Map tasks (as calling a plurality of Map tasks by the mode that starts job (work)) by calling the Map function, the data recording in the tables of data to be combined is converted to＜key value by a plurality of parallel Map tasks right.
In this step, the Map function can generate a plurality of Map tasks and specify the data of needs processing for each Map task according to wherein default parameter.The Map function parameters can comprise the quantity of Map task, the data volume that each Map task is handled.Because tables of data is normally with data recording (also can be described as data line) line mode tissue, therefore, the data volume parameter of each Map task processing can be the line displacement amount.
Each Map task is according to the line displacement amount data recording in the reading of data table line by line that is its appointment, and each data recording that will read is converted to＜key, value〉right, wherein, key is the value of key field in the data recording, and value is the value of all non-keyword fields in the data recording.The Map task can promptly be carried out conversion operations after reading data record, and will be converted to＜key, value〉to exporting, as output in the temporary file of DFS.Before outputing to temporary file, the key field in the table can be moved to first row of data, so that follow-up tables of data when splicing, the faster and easier key field that navigates to of carrying out.The data recording of each tables of data can write identical temporary file, also the data recording of different table can be write different temporary files, if the latter can be stored in each temporary file under the same catalogue, so that the follow-up data that read temporary file.Key field can be specified by the user, is the foundation of carrying out data splicing;
Step 203, call the Reduce function and generate the Reduce task, by the Reduce task to all Map tasks outputs＜key, value〉to carrying out union operation.
In this step, the Reduce task obtain the output of all Map tasks＜key, value〉right, as from temporary file, obtaining＜key value〉right, and own＜key value to what have an identical key value to merging, obtain new data recording.
The Reduce task will have the same keyword field value but the non-keyword field and this key field that have in all data recording of different table marks are spliced into new data recording when carrying out union operation.The merging mode can comprise: connection naturally, a left side connect, the right side connects etc.Wherein, connect naturally and be meant that all fields in the data recording that has same key field value in the tables of data that all are to be combined splice; A left side connects and to be meant the key field of first table in the tables of data to be combined key field for the tables of data after merging, with the tables of data that has in other tables of data after other fields in the data recording of corresponding key field value write this merging, fill with NULL for the null value field; The right connection is connected similarly with a left side, just be to serve as the merging foundation with last tables of data in the tables of data to be combined.For example, for following table 1, table 2 and table 3, the result that various merging modes obtain is:
Table 1
| Sign (key field) | Name |
| ??1 | ??Zhang |
| ??2 | ??Li |
| ??3 | ??Wang |
| ??5 | ??Liu |
Table 2
| Sign (key field) | Expense |
| ??1 | ??1000 |
| ??3 | ??400 |
| ??4 | ??300 |
Table 3
| Sign (key field) | Company | Department |
| ??2 | ??A | ??a |
| Sign (key field) | Company | Department |
| ??3 | ??B | ??b |
| ??4 | ??C | ??b |
| ??5 | ??C | ??d |
Naturally the result of Lian Jieing is:
| Sign (key field) | Name | Expense | Company | Department |
| ??3 | ??wang | ??400 | ??B | ??b |
The result that a left side connects is:
| Sign (key field) | Name | Expense | Company | Department |
| ??1 | ??Zhang | ??1000 | ??NULL | ??NULL |
| ??2 | ??Li | ??NULL | ??A | ??a |
| ??3 | ??Wang | ??400 | ??B | ??b |
| ??5 | ??Liu | ??NULL | ??C | ??d |
The right result who connects is:
| Sign (key field) | Name | Expense | Company | Department |
| ??2 | ??Li | ??NULL | ??A | ??a |
| ??3 | ??Wang | ??400 | ??B | ??b |
| ??4 | ??NULL | ??300 | ??C | ??b |
| ??5 | ??Liu | ??NULL | ??C | ??d |
Step 201 among Fig. 2 also can be carried out by a plurality of parallel Map tasks,, generates a plurality of parallel Map tasks by calling the Map function that is, and respectively table is identified all data recording of adding in the corresponding data table by the Map task of a plurality of executed in parallel.Can generate corresponding one or more Map tasks for each tables of data by starting job, be responsible for the table sign of corresponding data table by the Map task and add operation.Each Map task is according to the capable pairing data recording of corresponding data that reads line by line for its data designated row in the corresponding data table, and after reading a data record, in this data recording, add the table sign, be all data recording of its appointment up to having read.Need to prove that the Map task of interpolation table sign belongs to different job with the Map task of carrying out data processing.For needing to start a plurality of different job, a plurality of tables of data interpolation table signs handle respectively.
Each Map task in the flow process shown in Figure 2 can be carried out by each XM, wherein, the Map task that each XM is carried out can for one also can be for a plurality of, and each Map tasks in parallel is carried out.
Based on identical technical characterictic, the embodiment of the invention also provides the heterogeneous data table combination system.
Referring to Fig. 3, the structural representation of the heterogeneous data table combination system 1 that provides for the embodiment of the invention, this system comprises: table identification distribution unit 11, data merge cells 12, wherein:
Table identification distribution unit 11 is used to a plurality of heterogeneous data tables allocation table sign respectively, and table is identified all data recording of adding in the corresponding data table;
Data merge cells 12, be used for according to the key field that is provided with, the data recording that will have the same keyword field value but have a different table marks is merged into new data recording, table sign deletion in the data recording that this is new, and will delete the data recording of showing sign and store in the new tables of data.
Data merge cells 12 can comprise:
The Map task of calling with calling module 121 is Map task execution module 122 (only illustrating 3 among the figure) one to one, be used to carry out the Map task, comprise: obtain the segment data record in all data recording of having added the table sign, and the data recording that gets access to is converted to respectively＜key, value〉right, wherein, key is the key field value in the data recording, and value is the non-keyword field value in this data recording;
Reduce task execution module 123 is used to carry out the Reduce task, comprising: with obtain after all Map Task Switching＜key, value〉centering have identical key value but different table marks＜key, value〉to merging.Invoked Reduce task can be for a plurality of, and at this moment, Reduce task execution module 123 is a plurality of accordingly also, and Reduce task execution module 123 is corresponding one by one with invoked Reduce task.
Table identification distribution unit 11 can further start with described heterogeneous data table works one to one, each executed in parallel of working, comprise one or more parallel Map tasks in each work, each Map task is shown sign to the data recording of appropriate section in the corresponding data table and is added operation.
Above-mentioned Map task execution module 122 can be distributed in a plurality of XM, and wherein, an XM can comprise one or more Map task execution module 122.
Need to prove that the tables of data merging method that the embodiment of the invention provides not only can be used for data digging system, also can be used for the tables of data merging process in other data handling systems.It also can be a plurality of that the tables of data number that merges can be 2.
In sum, in the embodiment of the invention, by for heterogeneous data table allocation table sign showing its Data Source, thereby carrying out tables of data when merging, the data recording that can will derive from the different pieces of information table but have a same keyword segment value merges, thereby realizes the data integration of heterogeneous data table.The embodiment of the invention also can adopt Map/Reduce mechanism, when carrying out the tables of data merging, by a plurality of parallel Map tasks data to be combined are converted to＜key, value〉right, wherein key is crucial son field value, then by the Reduce task to having identical key value but different table marks＜key, value〉to merging processing, like this, understand Data Source by adding the table label table on the one hand, so that carry out the tables of data union operation, one side utilizes the parallel processing mode of Map/Reduce mechanism to improve the efficient of data union operations.
Obviously, those skilled in the art can carry out various changes and modification to the present invention and not break away from the spirit and scope of the present invention.Like this, if of the present invention these are revised and modification belongs within the scope of claim of the present invention and equivalent technologies thereof, then the present invention also is intended to comprise these changes and modification interior.
Claims (12)
1. the merging method of a heterogeneous data table is applied to adopt the data mining preprocessing process of Map/Reduce mechanism, it is characterized in that, comprising:
Be a plurality of heterogeneous data tables difference allocation table signs, and table is identified all data recording of adding in the corresponding data table;
Adopt mapping Map/ to simplify Reduce mechanism,, will have the same keyword field value but data recording with different table marks is merged into new data recording, and the table sign in will the be described new data recording is deleted according to the key field that is provided with;
The data recording of having deleted the table sign is stored in the new tables of data.
2. the method for claim 1 is characterized in that, table is identified all data recording of adding in the corresponding data table, comprising:
Start with described heterogeneous data table and work one to one, each executed in parallel of working comprises one or more parallel Map tasks in each work, and each Map task is shown sign to the data recording of appropriate section in the corresponding data table and added operation.
3. method as claimed in claim 2 is characterized in that, the Map task is shown sign to the data recording of appropriate section in the corresponding data table and added operation, is specially:
Map task basis is that its data designated row reads the capable pairing data recording of corresponding data in the corresponding data table line by line, and after reading a data record, in this data recording, add the table sign, be all data recording of its appointment up to having read.
4. the method for claim 1 is characterized in that, adopts mapping Map/ to simplify Reduce mechanism, according to the key field that is provided with, will have the same keyword field value but data recording with different table marks is merged into new data recording, comprising:
Carry out a plurality of parallel Map tasks, each Map task is obtained the data recording of appropriate section in all data recording of having added the table sign, and the data recording that gets access to is converted to respectively＜key, value〉right, wherein, key is the key field value in the data recording, and value is the non-keyword field value in this data recording;
Carry out the Reduce task, described Reduce task obtains after with all Map Task Switching＜key, value〉centering have identical key value but different table marks＜key, value〉to merging.
5. method as claimed in claim 4 is characterized in that, described Reduce task is one or more.
6. method as claimed in claim 4 is characterized in that, obtains before the data recording of appropriate section in all data recording of having added the table sign, also comprises: store all data recording of having added the table sign into temporary file;
Obtain the data recording of appropriate section in all data recording of having added the table sign, be specially: each Map task is according to being its data designated row capable pairing data recording of corresponding data in the reads data log from described temporary file line by line.
7. as each described method of claim 2 to 6, it is characterized in that described a plurality of Map tasks are assigned on one or more XM to be carried out.
8. as each described method of claim 1 to 6, it is characterized in that the mode of merging into new data line comprises: connection naturally, a left side connect or right the connection.
9. heterogeneous data table combination system is applied to adopt the data mining preprocessing process of Map/Reduce mechanism, it is characterized in that, comprising:
Table identification distribution unit is used to a plurality of heterogeneous data tables allocation table sign respectively, and table is identified all data recording of adding in the corresponding data table;
The data merge cells, be used to adopt Map/Reduce mechanism, according to the key field that is provided with, the data recording that will have the same keyword field value but have a different table marks is merged into new data recording, with the deletion of the sign of the table in the described new data recording, and the data recording that will delete the table sign stores in the new tables of data.
10. system as claimed in claim 9 is characterized in that, described data merge cells comprises:
Calling module is used to call a plurality of parallel Map tasks, and calls the Reduce task after described a plurality of parallel Map tasks are complete;
The Map task of calling with described calling module is the Map task execution module one to one, be used to carry out the Map task, comprise: obtain the segment data record in all data recording of having added the table sign, and the data recording that gets access to is converted to respectively＜key, value〉right, wherein, key is the key field value in the data recording, and value is the non-keyword field value in this data recording;
The Reduce task execution module is used to carry out the Reduce task, comprising: with obtain after all Map Task Switching＜key, value〉centering have identical key value but different table marks＜key, value〉to merging.
11. system as claimed in claim 10, it is characterized in that, described table identification distribution unit is further used for, start with described heterogeneous data table and work one to one, each executed in parallel of working, comprise one or more parallel Map tasks in each work, each Map task is shown sign to the data recording of appropriate section in the corresponding data table and is added operation.
12., it is characterized in that described Reduce task execution module is one or more as claim 10 or 11 described systems, and described Reduce task execution module is corresponding one by one with invoked one or more Reduce tasks.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN200910077659A CN101799807A (en) | 2009-02-10 | 2009-02-10 | Heterogeneous data table merging method and system thereof |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN200910077659A CN101799807A (en) | 2009-02-10 | 2009-02-10 | Heterogeneous data table merging method and system thereof |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN101799807A true CN101799807A (en) | 2010-08-11 |
Family
ID=42595485
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN200910077659A Pending CN101799807A (en) | 2009-02-10 | 2009-02-10 | Heterogeneous data table merging method and system thereof |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN101799807A (en) |
Cited By (34)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102402555A (en) * | 2010-09-19 | 2012-04-04 | 上海众融信息技术有限公司 | Dynamic data reading and storing information processing method based on remote database |
| CN103150401A (en) * | 2013-03-27 | 2013-06-12 | 领航动力信息系统有限公司 | MapReduce-based field integral substitution method |
| CN103597473A (en) * | 2011-06-30 | 2014-02-19 | 惠普发展公司，有限责任合伙企业 | Systems and methods for merging partially aggregated query results |
| CN103838574A (en) * | 2014-02-20 | 2014-06-04 | 浪潮集团山东通用软件有限公司 | General method for grouped summarizing of data tables |
| CN103970790A (en) * | 2013-02-01 | 2014-08-06 | 华为技术有限公司 | Report combination method and equipment |
| CN104239320A (en) * | 2013-06-14 | 2014-12-24 | 深圳中兴网信科技有限公司 | Data merging method and system |
| CN104424190A (en) * | 2013-08-20 | 2015-03-18 | 富士通株式会社 | Method and device for integrating a plurality of databases |
| CN104866562A (en) * | 2015-05-20 | 2015-08-26 | 东华大学 | Method for parallelly processing facts based on Hadoop platform |
| CN105046401A (en) * | 2015-06-19 | 2015-11-11 | 国家电网公司 | Material statistic method and device for power projects |
| CN106372219A (en) * | 2016-09-07 | 2017-02-01 | 大地风景（武汉）信息技术有限公司 | User behavior data association method and system based on heterogeneous platform |
| CN106528575A (en) * | 2015-09-14 | 2017-03-22 | 北京国双科技有限公司 | Data connection method and device |
| CN106611024A (en) * | 2015-10-27 | 2017-05-03 | 北京国双科技有限公司 | File combining method and device |
| CN106708873A (en) * | 2015-11-16 | 2017-05-24 | 北京国双科技有限公司 | Data integration method data integration device |
| CN106777106A (en) * | 2016-12-15 | 2017-05-31 | 四川长虹电器股份有限公司 | The method for exhibiting data of the financial statement based on excel |
| CN106874335A (en) * | 2016-08-19 | 2017-06-20 | 阿里巴巴集团控股有限公司 | Behavioral data processing method, device and server |
| CN106933919A (en) * | 2015-12-31 | 2017-07-07 | 北京国双科技有限公司 | The connection method of tables of data and device |
| CN107038202A (en) * | 2016-12-28 | 2017-08-11 | 阿里巴巴集团控股有限公司 | Data processing method, device and equipment, computer-readable recording medium |
| CN107169278A (en) * | 2017-05-10 | 2017-09-15 | 成都智信电子技术有限公司 | A kind of data administering method and medical information system |
| CN107784058A (en) * | 2017-04-11 | 2018-03-09 | 平安医疗健康管理股份有限公司 | Drug data processing method and processing device |
| CN107833638A (en) * | 2017-10-25 | 2018-03-23 | 天津开心生活科技有限公司 | Classifying drugs table construction method and device, storage medium, electronic equipment |
| CN107943988A (en) * | 2017-12-01 | 2018-04-20 | 中国银行股份有限公司 | A kind of data joining method and device |
| CN107944011A (en) * | 2017-12-08 | 2018-04-20 | 中国平安财产保险股份有限公司 | Processing method, device, server and the storage medium of group's declaration form data |
| CN108052601A (en) * | 2017-12-12 | 2018-05-18 | 福建中金在线信息科技有限公司 | Database building method, device and terminal |
| CN109144404A (en) * | 2017-06-27 | 2019-01-04 | 北京金山安全软件有限公司 | Data storage and query method and device based on multiple DMPs and electronic equipment |
| CN109325105A (en) * | 2018-11-23 | 2019-02-12 | 泰康保险集团股份有限公司 | Code matches method, apparatus and storage medium |
| CN109710611A (en) * | 2018-12-25 | 2019-05-03 | 北京三快在线科技有限公司 | The method of storage table data, the method, apparatus of lookup table data and storage medium |
| CN110069539A (en) * | 2019-05-05 | 2019-07-30 | 上海缤游网络科技有限公司 | A kind of data correlation method and system |
| CN110175197A (en) * | 2019-05-23 | 2019-08-27 | 长沙学院 | A kind of body constructing method and system based on semantic Internet of Things |
| CN110785749A (en) * | 2018-06-25 | 2020-02-11 | 北京嘀嘀无限科技发展有限公司 | System and method for generating wide tables |
| CN110795426A (en) * | 2018-08-03 | 2020-02-14 | 上海小渔数据科技有限公司 | Data generation method, device and computer readable storage medium |
| CN111125232A (en) * | 2019-12-31 | 2020-05-08 | 北京奇艺世纪科技有限公司 | Method and device for accessing public cloud asset information |
| CN111767277A (en) * | 2020-07-08 | 2020-10-13 | 深延科技(北京)有限公司 | Data processing method and device |
| CN112102099A (en) * | 2020-09-16 | 2020-12-18 | 泰康保险集团股份有限公司 | Policy data processing method and device, electronic equipment and storage medium |
| CN116089436A (en) * | 2022-11-29 | 2023-05-09 | 荣耀终端有限公司 | Data auditing method of large data volume and electronic equipment |
-
2009
- 2009-02-10 CN CN200910077659A patent/CN101799807A/en active Pending
Cited By (53)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102402555A (en) * | 2010-09-19 | 2012-04-04 | 上海众融信息技术有限公司 | Dynamic data reading and storing information processing method based on remote database |
| CN103597473A (en) * | 2011-06-30 | 2014-02-19 | 惠普发展公司，有限责任合伙企业 | Systems and methods for merging partially aggregated query results |
| CN103970790A (en) * | 2013-02-01 | 2014-08-06 | 华为技术有限公司 | Report combination method and equipment |
| CN103970790B (en) * | 2013-02-01 | 2018-11-30 | 华为技术有限公司 | Report combined method and equipment |
| CN103150401A (en) * | 2013-03-27 | 2013-06-12 | 领航动力信息系统有限公司 | MapReduce-based field integral substitution method |
| CN103150401B (en) * | 2013-03-27 | 2017-03-08 | 领航动力信息系统有限公司 | A kind of field entirety replacement method based on MapReduce |
| CN104239320A (en) * | 2013-06-14 | 2014-12-24 | 深圳中兴网信科技有限公司 | Data merging method and system |
| CN104239320B (en) * | 2013-06-14 | 2017-09-19 | 深圳中兴网信科技有限公司 | A kind of data merging method and system |
| CN104424190A (en) * | 2013-08-20 | 2015-03-18 | 富士通株式会社 | Method and device for integrating a plurality of databases |
| CN103838574A (en) * | 2014-02-20 | 2014-06-04 | 浪潮集团山东通用软件有限公司 | General method for grouped summarizing of data tables |
| CN104866562A (en) * | 2015-05-20 | 2015-08-26 | 东华大学 | Method for parallelly processing facts based on Hadoop platform |
| CN105046401A (en) * | 2015-06-19 | 2015-11-11 | 国家电网公司 | Material statistic method and device for power projects |
| CN106528575B (en) * | 2015-09-14 | 2019-08-20 | 北京国双科技有限公司 | Data interconnection method and device |
| CN106528575A (en) * | 2015-09-14 | 2017-03-22 | 北京国双科技有限公司 | Data connection method and device |
| CN106611024A (en) * | 2015-10-27 | 2017-05-03 | 北京国双科技有限公司 | File combining method and device |
| CN106611024B (en) * | 2015-10-27 | 2020-08-11 | 北京国双科技有限公司 | File merging method and device |
| CN106708873A (en) * | 2015-11-16 | 2017-05-24 | 北京国双科技有限公司 | Data integration method data integration device |
| CN106933919B (en) * | 2015-12-31 | 2020-03-03 | 北京国双科技有限公司 | Data table connection method and device |
| CN106933919A (en) * | 2015-12-31 | 2017-07-07 | 北京国双科技有限公司 | The connection method of tables of data and device |
| CN106874335A (en) * | 2016-08-19 | 2017-06-20 | 阿里巴巴集团控股有限公司 | Behavioral data processing method, device and server |
| CN106372219A (en) * | 2016-09-07 | 2017-02-01 | 大地风景（武汉）信息技术有限公司 | User behavior data association method and system based on heterogeneous platform |
| CN106777106A (en) * | 2016-12-15 | 2017-05-31 | 四川长虹电器股份有限公司 | The method for exhibiting data of the financial statement based on excel |
| CN107038202A (en) * | 2016-12-28 | 2017-08-11 | 阿里巴巴集团控股有限公司 | Data processing method, device and equipment, computer-readable recording medium |
| CN107038202B (en) * | 2016-12-28 | 2020-05-05 | 阿里巴巴集团控股有限公司 | Data processing method, device and equipment and readable medium |
| CN107784058A (en) * | 2017-04-11 | 2018-03-09 | 平安医疗健康管理股份有限公司 | Drug data processing method and processing device |
| CN107784058B (en) * | 2017-04-11 | 2020-11-13 | 平安医疗健康管理股份有限公司 | Medicine data processing method and device |
| CN107169278A (en) * | 2017-05-10 | 2017-09-15 | 成都智信电子技术有限公司 | A kind of data administering method and medical information system |
| CN109144404A (en) * | 2017-06-27 | 2019-01-04 | 北京金山安全软件有限公司 | Data storage and query method and device based on multiple DMPs and electronic equipment |
| CN107833638A (en) * | 2017-10-25 | 2018-03-23 | 天津开心生活科技有限公司 | Classifying drugs table construction method and device, storage medium, electronic equipment |
| CN107943988B (en) * | 2017-12-01 | 2021-10-19 | 中国银行股份有限公司 | Data splicing method and device |
| CN107943988A (en) * | 2017-12-01 | 2018-04-20 | 中国银行股份有限公司 | A kind of data joining method and device |
| CN107944011B (en) * | 2017-12-08 | 2020-08-21 | 中国平安财产保险股份有限公司 | Method, device, server and storage medium for processing group policy data |
| CN107944011A (en) * | 2017-12-08 | 2018-04-20 | 中国平安财产保险股份有限公司 | Processing method, device, server and the storage medium of group's declaration form data |
| CN108052601A (en) * | 2017-12-12 | 2018-05-18 | 福建中金在线信息科技有限公司 | Database building method, device and terminal |
| CN108052601B (en) * | 2017-12-12 | 2021-07-23 | 福建中金在线信息科技有限公司 | Database establishing method and device and terminal |
| US11061882B2 (en) | 2018-06-25 | 2021-07-13 | Beijing Didi Infinity Technology And Development Co., Ltd. | Systems and methods for generating a wide table |
| CN110785749A (en) * | 2018-06-25 | 2020-02-11 | 北京嘀嘀无限科技发展有限公司 | System and method for generating wide tables |
| CN110785749B (en) * | 2018-06-25 | 2020-08-21 | 北京嘀嘀无限科技发展有限公司 | System and method for generating wide tables |
| CN110795426B (en) * | 2018-08-03 | 2022-07-19 | 上海小渔数据科技有限公司 | Data generation method, device and computer readable storage medium |
| CN110795426A (en) * | 2018-08-03 | 2020-02-14 | 上海小渔数据科技有限公司 | Data generation method, device and computer readable storage medium |
| CN109325105B (en) * | 2018-11-23 | 2021-06-29 | 泰康保险集团股份有限公司 | Code matching method, device and storage medium |
| CN109325105A (en) * | 2018-11-23 | 2019-02-12 | 泰康保险集团股份有限公司 | Code matches method, apparatus and storage medium |
| CN109710611B (en) * | 2018-12-25 | 2019-09-17 | 北京三快在线科技有限公司 | The method of storage table data, the method, apparatus of lookup table data and storage medium |
| CN109710611A (en) * | 2018-12-25 | 2019-05-03 | 北京三快在线科技有限公司 | The method of storage table data, the method, apparatus of lookup table data and storage medium |
| CN110069539A (en) * | 2019-05-05 | 2019-07-30 | 上海缤游网络科技有限公司 | A kind of data correlation method and system |
| CN110175197B (en) * | 2019-05-23 | 2021-03-23 | 长沙学院 | Ontology construction method and system based on semantic Internet of things |
| CN110175197A (en) * | 2019-05-23 | 2019-08-27 | 长沙学院 | A kind of body constructing method and system based on semantic Internet of Things |
| CN111125232A (en) * | 2019-12-31 | 2020-05-08 | 北京奇艺世纪科技有限公司 | Method and device for accessing public cloud asset information |
| CN111767277A (en) * | 2020-07-08 | 2020-10-13 | 深延科技(北京)有限公司 | Data processing method and device |
| CN112102099A (en) * | 2020-09-16 | 2020-12-18 | 泰康保险集团股份有限公司 | Policy data processing method and device, electronic equipment and storage medium |
| CN112102099B (en) * | 2020-09-16 | 2023-11-24 | 泰康保险集团股份有限公司 | Policy data processing method and device, electronic equipment and storage medium |
| CN116089436A (en) * | 2022-11-29 | 2023-05-09 | 荣耀终端有限公司 | Data auditing method of large data volume and electronic equipment |
| CN116089436B (en) * | 2022-11-29 | 2023-11-07 | 荣耀终端有限公司 | Data auditing method of large data volume and electronic equipment |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN101799807A (en) | Heterogeneous data table merging method and system thereof | |
| CN101958987B (en) | Method and system for dynamically converting telecommunications service data | |
| CN100407200C (en) | Correlation inquiry system and its method | |
| CN102043682B (en) | Workflow exception handing method and system | |
| WO2016165321A1 (en) | Method and apparatus for establishing requirement meta model for high-speed train | |
| CN101799809A (en) | Data mining method and system | |
| CN101714231A (en) | Method and system for managing free workflow without being based on process models | |
| CN101777008A (en) | Method and device for realizing mobile terminal system thread pool | |
| CN102375837A (en) | Data acquiring system and method | |
| CN101960439A (en) | Client environment creation system, client environment creation method, client environment creation program, and storage medium | |
| CN101887410A (en) | File conversion device, document conversion method and file converter | |
| CN103577614A (en) | Data acquisition method and system oriented to SAP PI application integration platform | |
| CN110968579A (en) | Execution plan generation and execution method, database engine and storage medium | |
| CN101101651A (en) | Conversion processing method, system and conversion rule engine for electronic worksheet data | |
| CN102279951A (en) | Report information processing method and system | |
| CN102054001A (en) | Data preprocessing method, system and device in data mining system | |
| CN104123135A (en) | Method and device for unifying background interfaces | |
| CN115630057A (en) | Method for realizing automatic integration of multi-source heterogeneous data | |
| CN115729933A (en) | Structured bill of material management method, system and storage medium | |
| CN101452486A (en) | System data management method for [inscriptions on bones or tortoise shells and apparatus thereof | |
| CN104462189B (en) | Distributed system data management based on planar bar code technology and operation method | |
| CN112162951A (en) | Information retrieval method, server and storage medium | |
| CN104408543B (en) | The processing method and processing unit of the attribute status of Business Entity | |
| CN114443651B (en) | Method and device for processing buried point data to ODS layer | |
| CN115185614A (en) | Cross-platform processing method and device for bank self-service machine, electronic equipment and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C12 | Rejection of a patent application after its publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20100811 |