CN104794190A - Method and device for effectively storing big data - Google Patents
Method and device for effectively storing big data Download PDFInfo
- Publication number
- CN104794190A CN104794190A CN201510180853.2A CN201510180853A CN104794190A CN 104794190 A CN104794190 A CN 104794190A CN 201510180853 A CN201510180853 A CN 201510180853A CN 104794190 A CN104794190 A CN 104794190A
- Authority
- CN
- China
- Prior art keywords
- data
- object data
- synchronization
- synchronous
- attribute information
- 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.)
- Granted
Links
Landscapes
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
The invention provides a method and device for effectively storing big data. The method comprises the steps that S100, the data to be stored are preprocessed, the data to be stored are encapsulated to object data, attribute information of the object data is added to the object data, and the attribute information comprises data types of the object data; S200, the object data are received, and the data types of the object data are determined according to the attribute information of the object data; S300, the object data are stored in different storage units according to the data types of the object data. The data of different types are stored through the different storage units respectively, and therefore the storage advantages of the different storage units can be achieved.
Description
Technical field
The present invention relates to field of data storage, be specifically related to the method and apparatus that a kind of large data effectively store.
Background technology
Along with the develop rapidly of the application such as mobile Internet, Internet of Things, there is explosive growth in global metadata amount.The growth at full speed of data volume imply that and entered large data age now.
Data are divided into structural data, semi-structured data and unstructured data by type, and wherein structural data refers to a kind of data type that can represent with two-dimensional structure, by relational data library storage; Semi-structured data refers to have a fixed structure, but a kind of data type that semanteme is clear and definite not, as mail, html web page etc., their some fields are determined, also some field is uncertain; Unstructured data refers to a kind of data type that cannot represent with two-dimensional structure, mainly comprises office documents, text, picture, audio-video document etc., relevant database cannot be adopted to process.With the rise and development of social networks, create a large amount of UGC (User Generated Content, user-generated content), comprise the unstructured datas such as audio frequency, video, text and picture.In all data, structural data accounts for 20% of data total amount, and semi-structured data and unstructured data account for 80% of data total amount, and how scientific management seems with reasonable these data of application becomes more and more important.
Traditional relevant database has very excellent performance, but due to the rule constrain such as strong consistency and strong transactional, relational data is unwell to extending transversely on a large scale, thus there are problems when making relevant database be applied in the storage of semi-structured or non-structured data.The technological challenge that large data bring to traditional Data Analysis Services technology (such as parallel database, data warehouse).Conventional data analysis treatment technology cannot process high scalability and the massive demand of large data.For the user of hundreds of millions, data present multi-sourcing, isomerized trend, and the consistance, data interaction, transmission delay etc. of different application to data all have different demands.
In prior art, the platform based on Hadoop is adopted to the process of large data.Hadoop is a Distributed Computing Platform of increasing income, and its core comprises HDFS (Hadoop Distributed Files System, Hadoop distributed file system).The many merits (mainly comprising high fault tolerance, high scalability etc.) of HDFS allows user to be deployed on cheap hardware by Hadoop, builds distributed type assemblies, forms distributed system.HBase (Hadoop DataBase, Hadoop database) be the distributed data base system that the storage of high reliability, high-performance, row, scalable, real-time read-write are provided be based upon on distributed file system HDFS, be mainly used to store destructuring and semi-structured unstructured data.
How realizing effective storage of the data to different pieces of information structure, is the problem that large field of data storage faces.
Summary of the invention
For solving the above-mentioned technical matters existed in prior art, the present invention proposes the method and apparatus that a kind of large data effectively store.
The method that a kind of large data that the present invention proposes effectively store, comprising:
Step S100, carries out pre-service to data to be stored; Described data encapsulation to be stored is become object data, is added with the attribute information of object data in described object data, described attribute information comprises the data type of object data;
Step S200, receives object data, according to the data type of the attribute information determination object data of object data;
Step S300, object data is stored in different storage unit by the data type according to object data.
Wherein, the data type of the object data described in step S100 comprises structural data, semi-structured data and unstructured data; Different storage unit described in step S300 comprises HDFS distributed file system unit, HBase Database Unit and relation data library unit; Wherein, HDFS distributed file system unit is for storing unstructured data, and HBase Database Unit is for storing semi-structured data, and relational database is used for structured data.
Wherein, object data packed in step S100 has unified data operating interface, and described data operating interface receives the operation to object data;
Different storage unit has respective data manipulation resolution unit respectively, for the data manipulation that the data operating interface receiving object data sends, and described data manipulation is resolved, the data manipulation that data operating interface sends is converted to the operation that this storage unit can perform.
Wherein, adopt the incidence relation between tree conservation object data, on the one hand, each node of tree saves the link of a sensing object data, namely tree does not store actual object data, the node of tree and object data are relations one to one, and on the other hand, the relation between tree father and son node illustrates the corresponding relation between object data.
The method that the large data that the present invention proposes effectively store, comprises further:
Step S400, carries out synchronously to the object data in each storage unit, and described synchronously to refer between the object data of client and the object data of server end synchronous.
The method that the large data that the present invention proposes effectively store, comprises further:
Real-time synchronization mark is comprised at the attribute information of object data, when client is carried out synchronous, first Sampling network environment, if message transmission rate is greater than first threshold, then carry out real-time synchronization, if message transmission rate is not more than first threshold, the then real-time synchronization mark of detected object data, if real-time synchronization is masked as "Yes", then carry out real-time synchronization, if real-time synchronization is masked as "No", then temporarily do not carry out real-time synchronization, wait for that message transmission rate is greater than when specifying threshold value and carry out synchronous operation again.
The method that the large data that the present invention proposes effectively store, comprises further:
For the situation of non real-time synchronous, two kinds of synchronous processing modes are comprised when carrying out synchronous, one is whole methods of synchronization, namely need not consider that single object data is the need of synchronously, whole object data is carried out synchronously, another kind is increment synchronization mode, the object data that namely only synchronous needs are synchronous, i.e. vicissitudinous object data; When synchronous operation, judge to decide to adopt increment synchronization mode or whole method of synchronization by the method for synchronization, the described method of synchronization judges to comprise: the lock in time the earliest judging all object datas, when the difference of lock in time and current time is the earliest greater than Second Threshold, then adopt whole method of synchronization.
The invention allows for the device that a kind of large data effectively store, comprising:
Pretreatment module, for carrying out pre-service to data to be stored; Described data encapsulation to be stored is become object data, is added with the attribute information of object data in described object data, described attribute information comprises the data type of object data;
Receiver module, receives object data, according to the data type of the attribute information determination object data of object data;
Memory module, object data is stored in different storage unit by the data type according to object data.
The method and apparatus that a kind of large data that the present invention proposes effectively store, by the data utilizing different storage unit to store different types of data respectively, thus can play the storage advantage of different storage unit.By the mode of object data, the data of different types of data are encapsulated, and unified data operating interface is provided, the unified operation to the data in different storage unit can be realized.The object data in different storage unit is organized by tree, can the discrete object data of handled easily.
Accompanying drawing explanation
Fig. 1 is the process flow diagram of date storage method of the present invention;
Fig. 2 is the structural drawing of data storage device of the present invention.
Embodiment
Below in conjunction with accompanying drawing of the present invention, technical scheme of the present invention is clearly and completely described.Here will be described exemplary embodiment in detail, its sample table shows in the accompanying drawings.When description below relates to accompanying drawing, unless otherwise indicated, the same numbers in different accompanying drawing represents same or analogous key element.Embodiment described in following exemplary embodiment does not represent all embodiments consistent with the present invention.On the contrary, they only with as in appended claims describe in detail, the example of apparatus and method that aspects more of the present invention are consistent.
See Fig. 1, the method that a kind of large data that the present invention proposes effectively store, comprising:
Step S100, carries out pre-service to data to be stored; Described data encapsulation to be stored is become object data, is added with the attribute information of object data in described object data, described attribute information comprises the data type of object data;
Data to be stored can be various types of data, structural data, semi-structured data, unstructured data.The pre-service of data to be stored is comprised and analyzes and determine the data type of data to be stored.Data encapsulation to be stored is become object data, and the data type of data to be stored is added in the attribute information of object data, namely can be determined the data type of object data by the attribute information of object data.
Step S200, receives object data, according to the data type of the attribute information determination object data of object data;
According to the data type of the object data that the attribute information of object data comprises, can determine that the data type of object data is structural data, semi-structured data or unstructured data.
Step S300, object data is stored in different storage unit by the data type according to object data.
Further, the different storage unit described in step S300 comprises HDFS distributed file system unit, HBase Database Unit and relation data library unit; Wherein, HDFS distributed file system unit is for storing unstructured data, and HBase Database Unit is for storing semi-structured data, and relational database is used for structured data.
Further, object data packed in step S100 has unified data operating interface, and described data operating interface receives the operation to object data.Different storage unit has respective data manipulation resolution unit respectively, for the data manipulation that the data operating interface receiving object data sends, and described data manipulation is resolved, the data manipulation that data operating interface sends is converted to the operation that this storage unit can perform.
Due to the textural difference of different data types, the data of different types of data have different requirements in storage and query manipulation, if all use single storage and querying method to the data of different types of data, described single storage and querying method, may be unfavorable to the operation of the data of another kind of data type when the operation of the data to a kind of data type is favourable.The method that a kind of large data that the present invention proposes effectively store, to the data of different types of data, can both provide effective and store and querying method.
The method that a kind of large data provided by the invention effectively store, comprise further: adopt the incidence relation between tree conservation object data, on the one hand, each node of tree saves the link of a sensing object data, namely tree does not store actual object data, the node of tree and object data are relations one to one, and on the other hand, the relation between tree father and son node illustrates the corresponding relation between object data.Different cell stores be discrete data object, these object datas then associate by tree, the convenient application operating to data.
The method that a kind of large data provided by the invention effectively store, comprises further:
Step S400, carries out synchronously the object data in each storage unit.
In a large amount of internet, applications, server end safeguards a large data set, and each client safeguards a subset of large data sets respectively, carries out the synchronous of data like this with regard to needing at client and server end.Each storage unit in step S300 is positioned at server end, and client and server end can be safeguarded the object data in storage unit, such as increases, deletes, revises, by the operation of log recording data.Client and server all must be able to identify subsynchronous after (may success, also may failure), the data item changed, namely which data is modified, has increased which data newly and deleted which data.Here introduce the concept of synchronous anchor, synchronous anchor be exactly server end and client synchronization time a timestamp preserving, it indicates lastly synchronously whether to complete.
Initiate before synchronization request in client first time, will be this subsynchronous generation synchronous anchor, and be recorded in daily record, and be carried in synchronization request and send to client.After received server-side to message, this anchor is recorded to one with user-association, carry out buffer memory in the Hash table that take client id as key assignments, process synchronization request simultaneously, return corresponding data.This anchor value will be carried during return data.After client receives server end rreturn value, the anchor value in anchor value and daily record is compared, upgrade local data base, and be labeled as confirm changing daily record accordingly.Before upper once synchronization request, generate next anchor value, and carry respectively in synchronization request new anchor value with on confirmed anchor value (identifying with next and last respectively).After received server-side to new synchronization request, first confirm the last anchor in request and the anchor buoy in server buffer sensible same (namely client identifies using last and sends anchor information as the feedback to server end), mark is last to be synchronously identified, then according to previous step, synchronizing information is processed, cover old value with new anchor value after processing, thus complete new once synchronous.When server end finds that last mark is different from the anchor value in current cache, refusal performs new synchronization request, and returns notice client.Equally, client only completes a synchronization request, and obtains just sending synchronization request next time after service end confirms, thus ensures synchronous timing.
When data syn-chronization, relate to the real-time of data syn-chronization.At internet, applications environment, especially mobile Internet application, network environment varies, and than if any wifi network with do not have wifi network, message transmission rate may be mutually far short of what is expected, and the expense spent on Internet Transmission is also different.In order to namely meet the requirement of real-time of data syn-chronization, consider again the real network ambient conditions of user simultaneously.
The present invention comprises real-time synchronization mark at the attribute information of object data further, when client is carried out synchronous, first Sampling network environment, if message transmission rate is greater than appointment threshold value, then carry out real-time synchronization, if message transmission rate is not more than appointment threshold value, the then real-time synchronization mark of detected object data, if real-time synchronization is masked as "Yes", then carry out real-time synchronization, if real-time synchronization is masked as "No", then temporarily do not carry out real-time synchronization, wait for that message transmission rate is greater than when specifying threshold value and carry out synchronous operation again.
When data syn-chronization, also need to consider synchronous data volume.When network environment is poor, if synchronous data volume is more, then the increase of client device hydraulic performance decline and user's cost of use can be caused.For the situation of non real-time synchronous, multiple object data may be had to need when carrying out synchronous synchronous, at this moment two kinds of synchronous processing modes are had, one is whole methods of synchronization, namely need not consider that single object data is the need of synchronously, carried out by whole object data synchronously, another kind is increment synchronization mode, namely the object data that only synchronous needs are synchronous, i.e. vicissitudinous object data.Obviously, the volume of transmitted data of increment synchronization mode is less, can save the network bandwidth.But, the prerequisite of increment synchronization mode needs to judge which object data needs carries out synchronously one by one, and when vicissitudinous object data is more, the system overhead that this judgement spends also may be very high, generally speaking, sometimes this cost possibly higher than whole method of synchronization.
The present invention is when synchronous operation, judge to decide to adopt increment synchronization mode or whole method of synchronization by the method for synchronization, the described method of synchronization judges to comprise: the lock in time the earliest judging all object datas, when the difference of lock in time and current time is the earliest greater than appointment threshold value, then adopt whole method of synchronization.Comparatively early, show that the long period does not carry out synchronous operation lock in time the earliest, can think that to need to carry out synchronous object data more, at this moment directly take whole method of synchronization.Owing to only needing the lock in time the earliest judging object data, comparison other data the need of renewal, thus greatly calculated amount need not can be reduced one by one.
In addition, different Method of Data Organizations is also very large for synchronous impact.When carrying out Data Update to the father node of tree, corresponding needs upgrades all downstream sites belonging to described father node and their descendant node, and described downstream site comprises the child node of described father node and the downstream site of child node.If the downstream site that described father node comprises is a lot, the corresponding amount upgraded can be very large.In order to reduce this renewal be associated as far as possible, the present invention carries out Version Control to the node of tree, determine by the node of Version Control in tree, and by as root by Version Control and be not form a updating block by all downstream sites of Version Control with their descendant node.
By suitably determining the quantity of the node by Version Control, make to expect that the data that often will upgrade are in those and do not have or only have among the updating block of a small amount of downstream site.By being formed updating block in the mode of the node by Version Control, the data of updating block can be made to arrange as required, can prevent the renewal of certain node from developing into avalanche type by this way and upgrading.
See Fig. 2, the invention allows for the device that a kind of large data effectively store, comprising:
Pretreatment module, for carrying out pre-service to data to be stored; Described data encapsulation to be stored is become object data, is added with the attribute information of object data in described object data, described attribute information comprises the data type of object data;
Receiver module, receives object data, according to the data type of the attribute information determination object data of object data;
Memory module, object data is stored in different storage unit by the data type according to object data.
The method and apparatus that a kind of large data that the present invention proposes effectively store, by the data utilizing different storage unit to store different types of data respectively, thus can play the storage advantage of different storage unit.By the mode of object data, the data of different types of data are encapsulated, and unified data operating interface is provided, the unified operation to the data in different storage unit can be realized.The object data in different storage unit is organized by tree, can the discrete object data of handled easily.
Those skilled in the art, at consideration instructions and after putting into practice invention disclosed herein, will easily expect other embodiment of the present invention.The application is intended to contain any modification of the present invention, purposes or adaptations, and these modification, purposes or adaptations are followed general principle of the present invention and comprised the undocumented common practise in the art of the present invention or conventional techniques means.
Should be understood that, the present invention is not limited to precision architecture described above and illustrated in the accompanying drawings, and can carry out various amendment and change not departing from its scope.Scope of the present invention is only limited by appended claim.
Claims (8)
1. the method that effectively stores of large data, comprising:
Step S100, carries out pre-service to data to be stored; Described data encapsulation to be stored is become object data, is added with the attribute information of object data in described object data, described attribute information comprises the data type of object data;
Step S200, receives object data, according to the data type of the attribute information determination object data of object data;
Step S300, object data is stored in different storage unit by the data type according to object data.
2. the method that effectively stores of data as claimed in claim 1 large, wherein,
The data type of the object data described in step S100 comprises structural data, semi-structured data and unstructured data; Different storage unit described in step S300 comprises HDFS distributed file system unit, HBase Database Unit and relation data library unit; Wherein, HDFS distributed file system unit is for storing unstructured data, and HBase Database Unit is for storing semi-structured data, and relational database is used for structured data.
3. the method that effectively stores of data as claimed in claim 1 large, wherein,
Object data packed in step S100 has unified data operating interface, and described data operating interface receives the operation to object data;
Different storage unit has respective data manipulation resolution unit respectively, for the data manipulation that the data operating interface receiving object data sends, and described data manipulation is resolved, the data manipulation that data operating interface sends is converted to the operation that this storage unit can perform.
4. the method that effectively stores of data as claimed in claim 1 large, wherein,
Adopt the incidence relation between tree conservation object data, on the one hand, each node of tree saves the link of a sensing object data, namely tree does not store actual object data, the node of tree and object data are relations one to one, on the other hand, the relation between tree father and son node illustrates the corresponding relation between object data.
5. the method that effectively stores of data as claimed in claim 1 large, comprises further:
Step S400, carries out synchronously to the object data in each storage unit, and described synchronously to refer between the object data of client and the object data of server end synchronous.
6. the method that effectively stores of data as claimed in claim 5 large, comprises further:
Real-time synchronization mark is comprised at the attribute information of object data, when client is carried out synchronous, first Sampling network environment, if message transmission rate is greater than first threshold, then carry out real-time synchronization, if message transmission rate is not more than first threshold, the then real-time synchronization mark of detected object data, if real-time synchronization is masked as "Yes", then carry out real-time synchronization, if real-time synchronization is masked as "No", then temporarily do not carry out real-time synchronization, wait for that message transmission rate is greater than when specifying threshold value and carry out synchronous operation again.
7. the method that effectively stores of data as claimed in claim 6 large, comprises further:
For the situation of non real-time synchronous, two kinds of synchronous processing modes are comprised when carrying out synchronous, one is whole methods of synchronization, namely need not consider that single object data is the need of synchronously, whole object data is carried out synchronously, another kind is increment synchronization mode, the object data that namely only synchronous needs are synchronous, i.e. vicissitudinous object data; When synchronous operation, judge to decide to adopt increment synchronization mode or whole method of synchronization by the method for synchronization, the described method of synchronization judges to comprise: the lock in time the earliest judging all object datas, when the difference of lock in time and current time is the earliest greater than Second Threshold, then adopt whole method of synchronization.
8. the device that effectively stores of large data, comprising:
Pretreatment module, for carrying out pre-service to data to be stored; Described data encapsulation to be stored is become object data, is added with the attribute information of object data in described object data, described attribute information comprises the data type of object data;
Receiver module, receives object data, according to the data type of the attribute information determination object data of object data;
Memory module, object data is stored in different storage unit by the data type according to object data.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510180853.2A CN104794190B (en) | 2015-04-16 | 2015-04-16 | The method and apparatus that a kind of big data effectively stores |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510180853.2A CN104794190B (en) | 2015-04-16 | 2015-04-16 | The method and apparatus that a kind of big data effectively stores |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN104794190A true CN104794190A (en) | 2015-07-22 |
| CN104794190B CN104794190B (en) | 2017-11-24 |
Family
ID=53558982
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201510180853.2A Active CN104794190B (en) | 2015-04-16 | 2015-04-16 | The method and apparatus that a kind of big data effectively stores |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN104794190B (en) |
Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104750855A (en) * | 2015-04-16 | 2015-07-01 | 成都睿峰科技有限公司 | Method and device for optimizing big data storage |
| CN104765840A (en) * | 2015-04-16 | 2015-07-08 | 成都睿峰科技有限公司 | Big data distributed storage method and device |
| CN106469195A (en) * | 2016-08-31 | 2017-03-01 | 国信优易数据有限公司 | Based on conforming data file Valuation Method and system |
| CN106776709A (en) * | 2016-11-15 | 2017-05-31 | 山东浪潮云服务信息科技有限公司 | A kind of processing method and processing device of company information |
| CN107402982A (en) * | 2017-07-07 | 2017-11-28 | 阿里巴巴集团控股有限公司 | Data write-in, data matching method, device and computing device |
| CN109408518A (en) * | 2018-11-07 | 2019-03-01 | 郑州云海信息技术有限公司 | A kind of method and device of data storage |
| CN109638318A (en) * | 2018-12-04 | 2019-04-16 | 广东国鸿氢能科技有限公司 | Fuel cell remote monitoring system and method |
| CN110147348A (en) * | 2019-04-01 | 2019-08-20 | 贵州力创科技发展有限公司 | A kind of long data block structured storage method and system |
| CN110580255A (en) * | 2018-06-08 | 2019-12-17 | 深圳艾派网络科技股份有限公司 | method and system for storing and retrieving data |
| CN111597274A (en) * | 2020-07-23 | 2020-08-28 | 南京数科安金信息技术有限公司 | Data distributed encryption storage system |
-
2015
- 2015-04-16 CN CN201510180853.2A patent/CN104794190B/en active Active
Cited By (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104750855A (en) * | 2015-04-16 | 2015-07-01 | 成都睿峰科技有限公司 | Method and device for optimizing big data storage |
| CN104765840A (en) * | 2015-04-16 | 2015-07-08 | 成都睿峰科技有限公司 | Big data distributed storage method and device |
| CN104750855B (en) * | 2015-04-16 | 2017-11-24 | 成都睿峰科技有限公司 | A kind of big data storage optimization method and device |
| CN106469195A (en) * | 2016-08-31 | 2017-03-01 | 国信优易数据有限公司 | Based on conforming data file Valuation Method and system |
| CN106776709A (en) * | 2016-11-15 | 2017-05-31 | 山东浪潮云服务信息科技有限公司 | A kind of processing method and processing device of company information |
| CN107402982A (en) * | 2017-07-07 | 2017-11-28 | 阿里巴巴集团控股有限公司 | Data write-in, data matching method, device and computing device |
| CN110580255A (en) * | 2018-06-08 | 2019-12-17 | 深圳艾派网络科技股份有限公司 | method and system for storing and retrieving data |
| CN109408518A (en) * | 2018-11-07 | 2019-03-01 | 郑州云海信息技术有限公司 | A kind of method and device of data storage |
| CN109638318A (en) * | 2018-12-04 | 2019-04-16 | 广东国鸿氢能科技有限公司 | Fuel cell remote monitoring system and method |
| CN110147348A (en) * | 2019-04-01 | 2019-08-20 | 贵州力创科技发展有限公司 | A kind of long data block structured storage method and system |
| CN111597274A (en) * | 2020-07-23 | 2020-08-28 | 南京数科安金信息技术有限公司 | Data distributed encryption storage system |
Also Published As
| Publication number | Publication date |
|---|---|
| CN104794190B (en) | 2017-11-24 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN104765840A (en) | Big data distributed storage method and device | |
| CN104794190A (en) | Method and device for effectively storing big data | |
| CN104750855A (en) | Method and device for optimizing big data storage | |
| US10803016B2 (en) | Predictive models of file access patterns by application and file type | |
| CN109063196B (en) | Data processing method and device, electronic equipment and computer readable storage medium | |
| KR101963917B1 (en) | Automatic synchronization of most recently used document lists | |
| US8533296B2 (en) | Schema-based feed generation for media syndication | |
| US8495177B2 (en) | Dynamic application programming interface | |
| CN106776783B (en) | Unstructured data memory management method and system | |
| CN108536778B (en) | Data application sharing platform and method | |
| US20120072465A1 (en) | Dynamic schema-based api mapping for traversing inter-cloud application boundaries | |
| CN111026727A (en) | Table dimension retrieval data synchronization method, system and device based on log file | |
| CN105205154B (en) | Data migration method and device | |
| US20140025899A1 (en) | Efficiently Updating and Deleting Data in a Data Storage System | |
| CN104050276A (en) | Cache processing method and system of distributed database | |
| US10216556B2 (en) | Master database synchronization for multiple applications | |
| CN111858760B (en) | Data processing method and device for heterogeneous database | |
| CN111177159B (en) | Data processing system and method and data updating equipment | |
| WO2017174013A1 (en) | Data storage management method and apparatus, and data storage system | |
| US20220121652A1 (en) | Parallel Stream Processing of Change Data Capture | |
| CN103353901A (en) | Orderly table data management method and system based on Hadoop distributed file system (HDFS) | |
| US11210212B2 (en) | Conflict resolution and garbage collection in distributed databases | |
| US9092338B1 (en) | Multi-level caching event lookup | |
| CN111241044B (en) | Method, device, equipment and readable storage medium for constructing heterogeneous database | |
| CN113347052B (en) | Method and device for counting user access data through access log |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| EXSB | Decision made by sipo to initiate substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| TR01 | Transfer of patent right | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20190711 Address after: Room 208, 2nd floor, No. 599 Gaojing Road, Qingpu District, Shanghai 201700 Patentee after: SHANGHAI V&G INFORMATION TECHNOLOGY CO.,LTD. Address before: Room 1202, No. 19, 1168 Lane, Tongchuan Road, Putuo District, Shanghai, 2003 Patentee before: Wu Jia Effective date of registration: 20190711 Address after: Room 1202, No. 19, 1168 Lane, Tongchuan Road, Putuo District, Shanghai, 2003 Patentee after: Wu Jia Address before: 610041 East Building, Ladfans Building, 1480 Tianfu Avenue North Section, Chengdu High-tech Zone, Sichuan Province, 10 stories Patentee before: CHENGDU RIMI TECHNOLOGY CO.,LTD. |