CN108241627A - A kind of isomeric data storage querying method and system - Google Patents
A kind of isomeric data storage querying method and system Download PDFInfo
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- CN108241627A CN108241627A CN201611205958.XA CN201611205958A CN108241627A CN 108241627 A CN108241627 A CN 108241627A CN 201611205958 A CN201611205958 A CN 201611205958A CN 108241627 A CN108241627 A CN 108241627A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/903—Querying
- G06F16/90335—Query processing
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/28—Databases characterised by their database models, e.g. relational or object models
- G06F16/284—Relational databases
Abstract
The invention discloses a kind of isomeric data storage querying methods and system, this method to include:Isomeric data is decomposed into dictionary data and acquired original data, it will be in dictionary data storage to several relations type database, it will be in the storage to several NoSql databases of acquired original data, traditional Relational DataBase and NoSql databases is enabled preferably to play the advantages of respective and characteristic, solves the problems, such as that magnanimity isomeric data search efficiency is relatively low；When inquiring data, dictionary data and acquired original data are obtained respectively from each relevant database and each NoSql database parallel, it is more efficient compared to Series poll, quick；Parallel query result is subjected to convergence merging, the multidimensional consequence collection that all relevant databases and NoSql databases return is converted to the two-dimensional result collection of bivariate table structure, is exported as query result, so as to page presentation, query result is made to facilitate readability.
Description
Technical field
The present invention relates to field of computer technology, and in particular to a kind of isomeric data storage querying method and system.
Background technology
With the development of information technology, the data storage capacity of enterprise application system is in explosive growth, the hair of database
Exhibition gradually develops into " NoSql " type database so that the inquiry of mass data to be supported to store also from traditional relevant database.
" NoSql " refers to non-relational database, database, columnar database, Document image analysis, figure including key assignments storage
Database.The common NoSql databases of big data field have HBase, Mongodb, Redis, Membase,
Elasticsearch etc..
Application and development architecture is usually all comprising multitype database at present, both using traditional Relational DataBase, simultaneously
Also " NoSql " database is used.When the data of user's inquiry are very big, and come from the database of multiple and different types, how
As from traditional Relational DataBase, the efficient bivariate table that returns is the problem of being encountered under current isomeric data lab environment.
Existing software application designs the following several ways of generally use：
The first, only uses relational data or only uses NoSql databases, it is impossible to play conventional relationship well
Type database and NoSql respectively the advantages of.
Second, while relevant database and NoSql databases are used, but obtain data from isomeric data at the same time
When, be all that traditional Relational DataBase data are first imported into NoSql databases in advance, then inquire from NoSql databases or
Person returns.Since some identical data have both deposited portion on traditional Relational DataBase, also deposited on NoSql databases
Portion, causes the unnecessary redundancy of data, increases carrying cost and cost of labor, and efficiency is low, need third party
Middleware or manual dump.
The third, writes interface and inquires different relevant databases by multi-threaded parallel, obtain data.Due to it is this simultaneously
Row inquiry is all based on traditional Relational DataBase namely across relational database query, for mass data, if from TB grades upper
Data are inquired in data, it is very slow using relevant database inquiry velocity, it is not suitable for the high system of real-time query requirement, strictly according to the facts
When monitoring system.
Invention content
The present invention provides a kind of isomeric data storage querying method and systems, are looked into solving existing magnanimity isomeric data
Ask the problem of efficiency is low.
According to an aspect of the present invention, the present invention provides a kind of isomeric datas to store querying method, including：
Isomeric data is decomposed into dictionary data and acquired original data, by dictionary data storage to several relations type
It, will be in acquired original data storage to several NoSql databases in database；
When inquiring data, parallel from relevant database each described and each described NoSql database respectively
Obtain the dictionary data and the acquired original data；
Parallel query result is subjected to convergence merging, all relevant databases and NoSql databases are returned more
Dimension result set is converted to the two-dimensional result collection of bivariate table structure, is exported as query result.
According to another aspect of the present invention, the present invention provides a kind of isomeric datas to store inquiry system, including data
Resolving cell, data query unit, query result output unit, several relations type database and several NoSql databases；
The data resolving cell, for isomeric data to be decomposed into dictionary data and acquired original data, and by described in
It, will be in acquired original data storage to the NoSql databases in dictionary data storage to the relevant database；
The data query unit, for parallel from relevant database each described and each described NoSql number
According to the dictionary data and the acquired original data are obtained in library respectively；
The query result output unit, for parallel query result to be carried out convergence merging, by all relationship type numbers
The multidimensional consequence collection returned according to library and NoSql databases is converted to the two-dimensional result collection of bivariate table structure, defeated as query result
Go out.
The beneficial effects of the invention are as follows：Isomeric data anatomy is decomposed into dictionary data and acquired original by the embodiment of the present invention
Data by dictionary data storage to relevant database, acquired original data are stored into NoSql databases so that pass
System relevant database and NoSql databases can preferably play the advantages of respective and characteristic, solve magnanimity isomeric data and look into
Ask the problem of less efficient.When inquiring data, dictionary is concurrently obtained respectively from relevant database and NoSql databases
Data and acquired original data are more efficient compared to Series poll, quick.Query result is finally converted to the two of bivariate table structure
Result set is tieed up, so as to page presentation, query result is made to facilitate readability.
Description of the drawings
Fig. 1 is a kind of flow chart of isomeric data storage querying method provided by one embodiment of the present invention；
Fig. 2 is a kind of functional block diagram of isomeric data storage inquiry system provided by one embodiment of the present invention.
Specific embodiment
The present invention design concept be：Existing magnanimity isomeric data search efficiency is relatively low, for such case, the present invention
The storage mode of layout data first analyzes business datum, and anatomy is decomposed into dictionary data and acquired original data, by dictionary number
According in storage to relevant database, acquired original data are stored into NoSql databases, then concurrently from relationship type number
According to dictionary data and acquired original data is obtained respectively in library and NoSql databases, query result is finally converted into bivariate table
The two-dimensional result collection of structure so that traditional Relational DataBase and NoSql databases can preferably play the advantages of respective and spy
Property, solve the problems, such as that magnanimity isomeric data search efficiency is relatively low.
Embodiment one
Fig. 1 is a kind of flow chart of isomeric data storage querying method provided by one embodiment of the present invention, such as Fig. 1 institutes
Show, isomeric data storage querying method provided in this embodiment includes：
Step S110：Isomeric data is decomposed into dictionary data and acquired original data, dictionary data is stored to several
It, will be in the storage to several NoSql databases of acquired original data in relevant database.
First, architecturally the storage mode of layout data, analysis business datum, anatomy are decomposed into dictionary data, that is, compare
More cured data and acquired original data, i.e., for the data of statistical analysis.In data loading, classification storage is introduced
By in dictionary data storage to traditional Relational DataBase, such as Mysql, acquired original data are stored to NoSql data for thinking
In library, such as search engine Elasticsearch, since Elasticsearch is by way of indexed search, in inquiry number
According to when, it is faster than traditional Relational DataBase inquiry velocity, be suitble to from mass data retrieval and inquisition, so as to solve relationship type number
According to library the problem of slow is inquired under TB level data.
Step S120：When inquiring data, parallel from each relevant database and each NoSql database respectively
Obtain dictionary data and acquired original data.
The present embodiment is provided with one for inquiring the foundation class of data, is each relational data using the foundation class
Library and each NoSql database distribute an inquiry thread, parallel from each relevant database in a manner of multithreading
Middle acquisition dictionary data simultaneously obtains acquired original data from each NoSql database, and multithreading is used for isomeric data
Parallel form is more efficient compared to Series poll, quick.
Step S130：Parallel query result is subjected to convergence merging, by all relevant databases and NoSql databases
The multidimensional consequence collection of return is converted to the two-dimensional result collection of bivariate table structure, is exported as query result.
By taking the application scenarios in report as an example, traditional Relational DataBase uses Mysql, while NoSql databases make
Use Elasticsearch.Data storage uses the thinking of classification storage, i.e. dictionary data deposit Mysql, acquired original data are deposited
Enter Elasticsearch.When carrying out isomeric data parallel query, it is first determined the data source and look into that each thread individually accesses
The class name of foundation class, while the data source name of configuration querying Mysql and inquiry are configured in report XML for inquiry mode
The data source name of Elasticsearch and the sql sentences respectively inquired, Elasticsearch are needed using class sql, under
Face is a kind of specific configuration method：
Foundation class BaseJointTable inquires Mysql and Elasticsearch simultaneously in a manner of multi-threaded parallel, meets
The real-time performance requirement of inquiry.When newly-increased heterogeneous database, foundation class can be changed, convenient for extension.
After per thread all returns the result collection, can respective result set be subjected to convergence merging as needed, if
There are the demands such as sequence, paging, ranks transposition, then can carry out data reprocessing：Judge whether multidimensional consequence collection needs ranks to turn
It puts, when needing ranks transposition, to multidimensional consequence collection procession transposition；Judge whether multidimensional consequence collection needs to sort, when need
When sorting, multidimensional consequence collection is ranked up；Judge whether multidimensional consequence collection needs paging, when needing paging, to multidimensional
Result set carries out paging, ultimately generates the two-dimensional result collection for meeting displaying requirement, so as to page presentation, facilitates query result easy
It reads.
The present embodiment, can be ripe, logical using traditional Relational DataBase well for Query in Heterogeneous Databases environment
With the characteristics of, use cost is low, compatible old application system framework, and can well adapt in current generation mass data storage
The problem of needing using NoSql databases, combines heterogeneous database respectively advantage, while relative to the realization of dump thinking,
A kind of feasible, more efficient, reusable, expansible realization method are provided, greatly improves query performance, is met in real time
The performance requirement of inquiry.Simultaneously, moreover it is possible to the type of database of support is very easily extended, if to support more isomeric datas
Library, it is only necessary to which multiplexing or modification original base class increase new Query in Heterogeneous Databases mode.
Embodiment two
Fig. 2 is a kind of functional block diagram of isomeric data storage inquiry system provided by one embodiment of the present invention.Such as Fig. 2 institutes
Show, isomeric data storage inquiry system provided in this embodiment includes data resolving cell 210, data query unit 240, inquiry
As a result output unit 250, several relations type database 220 and several NoSql databases 230.
Data resolving cell 210 is used to isomeric data being decomposed into dictionary data and acquired original data, and by dictionary number
According in storage to relevant database 220, by the storage to NoSql databases 230 of acquired original data, can utilize well
The characteristics of traditional Relational DataBase is ripe, general, use cost is low, compatible old application system framework, and can fit well
Should in current generation mass data storage need using NoSql databases the problem of.MySql can be selected in relevant database,
Elasticsearch can be selected in NoSql databases.Data query unit 240 is parallel from each relevant database 220 and every
Dictionary data and acquired original data are obtained respectively in one NoSql database 230, it is more efficient, quick compared to serially obtaining.It looks into
It askes result output unit 250 and parallel query result is subjected to convergence merging, by all relevant database 220 and NoSql numbers
The multidimensional consequence collection returned according to library 230 is converted to the two-dimensional result collection of bivariate table structure, is exported as query result, so as to the page
Displaying, makes query result facilitate readability.
In a preferred embodiment, data query unit 240 is specifically used for：Setting one is used to inquire the foundation class of data,
An inquiry thread is distributed for each relevant database 220 and each NoSql database 230 using the foundation class, with
The mode of multithreading obtains dictionary data from each relevant database 220 and parallel from each NoSql database 230
Middle acquisition acquired original data.It is further preferred that data query unit 240 carries out data query especially by following steps：
The dataSource link of the class name of foundation class, configuration querying relevant database 220 and NoSql databases 230 is configured in report XML
Claim, the sql sentences of configuration querying relevant database 220 and NoSql databases 230.
In a further advantageous embodiment, query result output unit 250 is specifically used for judging whether multidimensional consequence collection needs
Ranks transposition is wanted, when needing ranks transposition, to multidimensional consequence collection procession transposition；And judge whether multidimensional consequence collection needs
It sorts, when needing sequence, multidimensional consequence collection is ranked up；And judge whether multidimensional consequence collection needs paging, when need
When wanting paging, paging is carried out to multidimensional consequence collection, multidimensional consequence collection is made to be converted to the two-dimensional result collection of bivariate table structure, so as to page
Face is shown, query result is made to facilitate readability.
The above description is merely a specific embodiment, under the above-mentioned guidance of the present invention, those skilled in the art
Other improvement or deformation can be carried out on the basis of above-described embodiment.It will be understood by those skilled in the art that above-mentioned tool
The purpose of the present invention is only preferably explained in body description, and protection scope of the present invention should be subject to the protection scope in claims.
Claims (10)
1. a kind of isomeric data stores querying method, which is characterized in that the method includes：
Isomeric data is decomposed into dictionary data and acquired original data, by dictionary data storage to several relations type data
It, will be in acquired original data storage to several NoSql databases in library；
When inquiring data, obtained respectively from relevant database each described and each described NoSql database parallel
The dictionary data and the acquired original data；
Parallel query result is subjected to convergence merging, the multidimensional knot that all relevant databases and NoSql databases are returned
Fruit collects the two-dimensional result collection for being converted to bivariate table structure, is exported as query result.
2. isomeric data as described in claim 1 stores querying method, which is characterized in that described parallel from pass each described
It is to obtain the dictionary data and the acquired original data respectively in type database and each described NoSql database, has
Body includes：
Setting one is used to inquire the foundation class of data；
Using the foundation class inquiry thread is distributed for each relevant database and each NoSql database；
Dictionary data is obtained from each relevant database parallel and from every in a manner of multithreading using the foundation class
Acquired original data are obtained in one NoSql database.
3. isomeric data as claimed in claim 2 stores querying method, which is characterized in that the setting one is used to inquire number
According to foundation class, specifically include：
The class name of the foundation class is configured in report XML；
The data source name of relevant database described in configuration querying and the NoSql databases；
The sql sentences of relevant database described in configuration querying and the NoSql databases.
4. isomeric data as described in claim 1 stores querying method, which is characterized in that described by all relational datas
The two-dimensional result collection that the multidimensional consequence collection that library and NoSql databases return is converted to bivariate table structure includes：
Judge whether multidimensional consequence collection needs ranks transposition, when needing ranks transposition, to multidimensional consequence collection procession transposition；
And/or
Judge whether multidimensional consequence collection needs to sort, when needing sequence, multidimensional consequence collection is ranked up；
And/or
Judge whether multidimensional consequence collection needs paging, when needing paging, paging is carried out to multidimensional consequence collection.
5. isomeric data as described in claim 1 stores querying method, which is characterized in that the relevant database is
Mysql, the NoSql databases are Elasticsearch.
6. a kind of isomeric data stores inquiry system, which is characterized in that the system comprises：Data resolving cell, data query
Unit, query result output unit, several relations type database and several NoSql databases；
The data resolving cell, for isomeric data to be decomposed into dictionary data and acquired original data, and by the dictionary
It, will be in acquired original data storage to the NoSql databases in data storage to the relevant database；
The data query unit, for parallel from relevant database each described and each described NoSql database
It is middle to obtain the dictionary data and the acquired original data respectively；
The query result output unit, for parallel query result to be carried out convergence merging, by all relevant databases
The multidimensional consequence collection returned with NoSql databases is converted to the two-dimensional result collection of bivariate table structure, is exported as query result.
7. isomeric data as claimed in claim 6 stores inquiry system, which is characterized in that the data query unit is specifically used
In：Setting one is each relevant database and each using the foundation class for inquiring the foundation class of data
NoSql databases distribute one inquiry thread, using the foundation class in a manner of multithreading parallel from each relationship type number
Acquired original data are obtained according to acquisition dictionary data in library and from each NoSql database.
8. isomeric data as claimed in claim 7 stores inquiry system, which is characterized in that the data query unit specifically leads to
Following steps setting is crossed for inquiring the foundation class of data：The class name of the foundation class is configured in report XML；Configuration querying institute
State the data source name of relevant database and the NoSql databases；Relevant database described in configuration querying and described
The sql sentences of NoSql databases.
9. isomeric data as claimed in claim 6 stores inquiry system, which is characterized in that the query result output unit tool
Body is used for：
Judge whether multidimensional consequence collection needs ranks transposition, when needing ranks transposition, to multidimensional consequence collection procession transposition；
And/or
Judge whether multidimensional consequence collection needs to sort, when needing sequence, multidimensional consequence collection is ranked up；
And/or
Judge whether multidimensional consequence collection needs paging, when needing paging, paging is carried out to multidimensional consequence collection.
10. isomeric data as claimed in claim 6 stores inquiry system, which is characterized in that the relevant database is
Mysql, the NoSql databases are Elasticsearch.
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Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109656958A (en) * | 2018-12-18 | 2019-04-19 | 北京小米移动软件有限公司 | Data query method and system |
| CN110597927A (en) * | 2019-10-14 | 2019-12-20 | 上海依图网络科技有限公司 | Storage query method and device based on heterogeneous database |
| CN110895549A (en) * | 2019-09-04 | 2020-03-20 | 成都四方伟业软件股份有限公司 | Quantized data retrieval method and system |
| CN110968582A (en) * | 2019-11-01 | 2020-04-07 | 苏宁云计算有限公司 | Crowd generation method and device |
| CN111143427A (en) * | 2019-11-25 | 2020-05-12 | 中国科学院计算技术研究所 | Distributed information retrieval method, system and device based on-line computing |
| CN111159106A (en) * | 2019-12-30 | 2020-05-15 | 亚信科技（中国）有限公司 | Data query method and device |
| CN111159218A (en) * | 2019-12-31 | 2020-05-15 | 中科曙光国际信息产业有限公司 | Data processing method and device and readable storage medium |
| CN111414363A (en) * | 2020-03-13 | 2020-07-14 | 上海银赛计算机科技有限公司 | parallel heterogeneous method, system, medium and device suitable for client data in MySQL |
| CN111897824A (en) * | 2020-03-25 | 2020-11-06 | 上海云励科技有限公司 | Data operation method, device, equipment and storage medium |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103425780A (en) * | 2013-08-19 | 2013-12-04 | 曙光信息产业股份有限公司 | Data inquiry method and data inquiry device |
| KR101472257B1 (en) * | 2014-07-22 | 2014-12-11 | (주)카디날정보기술 | Method and device for parallel query processing using predictable logical data locality |
| CN104391899A (en) * | 2014-11-07 | 2015-03-04 | 中国建设银行股份有限公司 | Data management method and system for centralized clearing system |
| CN104504137A (en) * | 2014-12-31 | 2015-04-08 | 深圳市科漫达智能管理科技有限公司 | Data storage method and system |
| CN105279281A (en) * | 2015-11-17 | 2016-01-27 | 天泽信息产业股份有限公司 | Internet-of-things data access method |
| CN105512939A (en) * | 2015-12-04 | 2016-04-20 | 中国建设银行股份有限公司 | Foreign exchange transaction-related data storage and query method, declaration method and system |
| CN105868411A (en) * | 2016-04-27 | 2016-08-17 | 国网上海市电力公司 | Non-relation type database and relation type database integrated data query method and system |
| CN106126604A (en) * | 2016-06-20 | 2016-11-16 | 华南理工大学 | A kind of social security data log analysis process system based on Distributed Data Warehouse |
-
2016
- 2016-12-23 CN CN201611205958.XA patent/CN108241627A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103425780A (en) * | 2013-08-19 | 2013-12-04 | 曙光信息产业股份有限公司 | Data inquiry method and data inquiry device |
| KR101472257B1 (en) * | 2014-07-22 | 2014-12-11 | (주)카디날정보기술 | Method and device for parallel query processing using predictable logical data locality |
| CN104391899A (en) * | 2014-11-07 | 2015-03-04 | 中国建设银行股份有限公司 | Data management method and system for centralized clearing system |
| CN104504137A (en) * | 2014-12-31 | 2015-04-08 | 深圳市科漫达智能管理科技有限公司 | Data storage method and system |
| CN105279281A (en) * | 2015-11-17 | 2016-01-27 | 天泽信息产业股份有限公司 | Internet-of-things data access method |
| CN105512939A (en) * | 2015-12-04 | 2016-04-20 | 中国建设银行股份有限公司 | Foreign exchange transaction-related data storage and query method, declaration method and system |
| CN105868411A (en) * | 2016-04-27 | 2016-08-17 | 国网上海市电力公司 | Non-relation type database and relation type database integrated data query method and system |
| CN106126604A (en) * | 2016-06-20 | 2016-11-16 | 华南理工大学 | A kind of social security data log analysis process system based on Distributed Data Warehouse |
Cited By (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109656958A (en) * | 2018-12-18 | 2019-04-19 | 北京小米移动软件有限公司 | Data query method and system |
| CN110895549A (en) * | 2019-09-04 | 2020-03-20 | 成都四方伟业软件股份有限公司 | Quantized data retrieval method and system |
| CN110895549B (en) * | 2019-09-04 | 2022-12-06 | 成都四方伟业软件股份有限公司 | Quantized data retrieval method and system |
| CN110597927B (en) * | 2019-10-14 | 2022-08-16 | 上海依图网络科技有限公司 | Storage query method and device based on heterogeneous database |
| CN110597927A (en) * | 2019-10-14 | 2019-12-20 | 上海依图网络科技有限公司 | Storage query method and device based on heterogeneous database |
| CN110968582A (en) * | 2019-11-01 | 2020-04-07 | 苏宁云计算有限公司 | Crowd generation method and device |
| CN110968582B (en) * | 2019-11-01 | 2022-12-30 | 苏宁云计算有限公司 | Crowd generation method and device |
| CN111143427A (en) * | 2019-11-25 | 2020-05-12 | 中国科学院计算技术研究所 | Distributed information retrieval method, system and device based on-line computing |
| WO2021103207A1 (en) * | 2019-11-25 | 2021-06-03 | 中国科学院计算技术研究所 | Distributed information retrieval method and system based on in-network computing, and device |
| CN111143427B (en) * | 2019-11-25 | 2023-09-12 | 中国科学院计算技术研究所 | Distributed information retrieval method, system and device based on online computing |
| CN111159106A (en) * | 2019-12-30 | 2020-05-15 | 亚信科技（中国）有限公司 | Data query method and device |
| CN111159106B (en) * | 2019-12-30 | 2023-04-07 | 亚信科技（中国）有限公司 | Data query method and device |
| CN111159218A (en) * | 2019-12-31 | 2020-05-15 | 中科曙光国际信息产业有限公司 | Data processing method and device and readable storage medium |
| CN111159218B (en) * | 2019-12-31 | 2023-10-31 | 中科曙光国际信息产业有限公司 | Data processing method, device and readable storage medium |
| CN111414363A (en) * | 2020-03-13 | 2020-07-14 | 上海银赛计算机科技有限公司 | parallel heterogeneous method, system, medium and device suitable for client data in MySQL |
| CN111414363B (en) * | 2020-03-13 | 2023-04-14 | 上海银赛计算机科技有限公司 | Parallel heterogeneous method, system, medium and equipment suitable for client data in MySQL |
| CN111897824A (en) * | 2020-03-25 | 2020-11-06 | 上海云励科技有限公司 | Data operation method, device, equipment and storage medium |
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