CN104915341B - Visualize multiple database ETL integrated approaches and system - Google Patents
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- CN104915341B CN104915341B CN201410086142.4A CN201410086142A CN104915341B CN 104915341 B CN104915341 B CN 104915341B CN 201410086142 A CN201410086142 A CN 201410086142A CN 104915341 B CN104915341 B CN 104915341B
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Abstract
The present invention provides visualization multiple database ETL integrated approaches and system, method to include the following steps：Connect source database and target database；It is matched by source database and the ETL of target database, obtains the SQL statement of the source table of source database；The ETL data in multiple source datas library are optimized and performed, obtain to SQL statement and are injected into the object table of target database.System includes database management system level：Connect source database and target database；It is matched by source database and the ETL of target database, obtains the SQL statement of the source table of source database；Semantic layer：The ETL data in multiple source datas library are optimized and performed, obtain to SQL statement and are injected into the object table of target database.The present invention reduces the complexity that multiple database integrates, and improves the efficiency of geo-database integration, reduces the risk of geo-database integration.
Description
Technical field
The present invention relates to geo-database integration exploitations and database running optimizatin field, are a set of to be configured by graphic interface
Realize that multitype database integrates, data pick-up and the integrated approach and system of injection.
Background technology
With the rapid development of information technology, database application is more and more extensive, since department service and function belong to not
Together, different database environments is employed during each application system development, very big difficulty, the collection of multiple database are brought to practical application
Be always a problem into application technology, it is most according to application technology include to software system integration application, database it is visual
Change problem, parser of data etc..At present, although about geo-database integration method in the presence of one side is this kind of method
Integration degree it is not high, it is low that Query Efficiency is carried out after integrated；In addition be this kind of method flexibility it is poor, match
It puts comparatively laborious, if encounter the more complicated tables of data of design and field and numerous situations, not only needs largely
Time configuration, and easily malfunction.
For at present, existing main difficulty is the integrated of multiple database, data migration process optimization problem, different data
The efficiency that library integrates.Due to framework difference, multiple database, which integrates, needs multiple technologies to support；Data migration process is by data
Magnitude influences, and a large amount of Data Migration can cause the reduction of database operational efficiency, influence the use of database；Client it is various
Property can influence integrated efficiency, between client and client, there are channel transmissions for client and database side, can cause to transmit
Inefficiency.
Invention content
The object of the present invention is to provide a set of more ETL process integrated approaches of visualization.Institute to achieve the above object of the invention
The technical solution adopted is that：
Multiple database ETL integrated approaches are visualized, are included the following steps：
Connect source database and target database；It is matched by source database and the ETL of target database, obtains source data
The SQL statement of the source table in library；
The ETL data in multiple source datas library are optimized and performed, obtain to SQL statement and are injected into target database
Object table.
Described to be matched by source database and the ETL of target database, the SQL statement for obtaining the source table of source database includes
Following steps：
Source database and target database and table name, field is configured, and judges the data of source database and target database
Library type；
Different ETL Regularias are determined according to the type of database of source database and target database, further according to source data
The source table in library obtains the SQL statement of source table by ETL Regularias；
The ETL data for optimizing and performing to SQL statement, obtain multiple source datas library are simultaneously injected into target data
The object table in library includes the following steps：
Processing SQL statement simultaneously optimizes SQL statement according to the matched result of ETL rule bases；
The API that calling platform layer provides performs the SQL statement after optimization and obtains ETL data and be stored in data buffer zone, root
ETL data are injected to the object table of object library according to ETL rule bases.
The processing SQL statement is simultaneously optimized including following step SQL statement according to the matched result of ETL rule bases
Suddenly：
SQL statement is established into a tree construction；Semantic test is carried out to each node of tree construction, and carries out structure and turns
It changes, the algebraic manipulation that parsing tree is converted to the inquiry plan for representing initial accords with tree；Algebraic manipulation symbol tree is converted to and performs speed
The most fast SQL sequences of degree.
Multiple database ETL integrated systems are visualized, including：
Database management system level：Connect source database and target database；Pass through source database and target database
ETL is matched, and obtains the SQL statement of the source table of source database；
Semantic layer：The ETL data in multiple source datas library are optimized and performed, obtain to SQL statement and are injected into target
The object table of database.
The database management system level includes：
Graphical configuration interface：Source database and target database and table name, field is configured, and judges source database and mesh
Mark wide area information server type；
ETL rule bases：Different ETL Regularias are determined according to the type of database of source database and target database, then
SQL statement is obtained by ETL Regularias according to the source table of source database；
The semantic layer includes：
Query compiler device：Processing SQL statement simultaneously optimizes SQL statement according to the matched result of ETL rule bases；
Enforcement engine：The API that calling platform layer provides performs the SQL statement after optimization and obtains ETL data and be stored in data
ETL data are injected the object table of object library according to ETL rule bases by buffering area.
The query compiler device includes：
Query analyzer：SQL statement is established into a tree construction；
Inquire preprocessor：Semantic test is carried out to each node of tree construction, and each node of tree construction is carried out
Semantic test, and structure conversion is carried out, the algebraic manipulation that parsing tree is converted to the inquiry plan for representing initial accords with tree；
Query optimizer：Algebraic manipulation symbol tree is converted to and performs fastest SOL sequences.
The invention has the advantages that and advantage：
1. the present invention reduces the complexity that multiple database integrates, the efficiency of geo-database integration is improved, reduces data base set
Into risk.
2. the present invention is designed by hierarchical logic, the data source of each database is solved in hardware platform, operating system and logical
Believe the difference problem of agreement, the design using logic is carried out on a higher abstraction hierarchy, reduce answering for system realization
Polygamy, and make system that there is good explorative and autgmentability.
3. the present invention completes quick data query and unloading by query compiler device, query optimizer and enforcement engine.
4. the present invention realizes by graphical configuration interface and ETL rule bases and carries out syntactic analysis and verification, to avoid people
For mistake, ensure the correct execution of data pick-up.
5. the present invention realizes support of the system to data source, ensure that system is clever in different platform by podium level
It is living integrated.
Description of the drawings
Fig. 1 is the visualization multiple database ETL integrated approach frame diagrams of the present invention；
Fig. 2 is ETL process flows diagram flow chart.
Specific embodiment
The present invention is described in further detail with reference to the accompanying drawings and embodiments.
The extraction of ETL (Extract, Transform, Load) comprising data, conversion and loading.This method is using graphically
Human-computer interaction interface multiple data sources are configured, then from these source databases, number is obtained according to certain ETL logical methods
According to after conversion, being loaded into target data and handled, in order to improve the operational efficiency of database, ETL in whole process
Logical method can optimize decomposition according to the characteristics of distinct type data-base sql like language.
The present invention completes the configuration of multi-data source, by the way that ETL rules are configured, from source by graphical human-computer interaction interface
Data are obtained in database, after conversion, target database is loaded into and is handled, complete data integration.Specific steps are such as
Under：
1）Data source is defined, database, table name, the configuration of field are carried out by graphical configuration interface.
2）Analyze data source characteristic, propose unified configuration interface, definition for Oracle, DB2, SQLSERVER,
The adapter of SYBASE.
3）Define query compiler device, by the inquiry of textual form, establish a tree construction, semantic inspection carried out to inquiry
It looks into, forms the initial sequence of operation.
4）Query optimizer is defined, the most fast sequence of operation is determined using statistical data.
5）Enforcement engine is defined, the responsible each step performed in the sequence of operation chosen operates data, and be put into
It is interacted in buffering area with scheduler, has been added the data locked to avoid accessing.
6）ETL rules are defined, the data of buffering area is read, and carry out unloading, data is checked by graphical interfaces.
The semantic layer defines query compiler device, query optimizer and enforcement engine, by text, pass through optimization
The efficient sequence of operation is formed, is responsible for interacting with database by enforcement engine.
The design of visualization multiple database ETL integrated approaches is mainly reflected in three levels：Podium level, semantic layer and data
Base management system layer, such as Fig. 1.Designed by hierarchical logic, solve the data source of each database in hardware platform, operating system and
The difference problem of communication protocol carries out the design using logic on a higher abstraction hierarchy, reduces system realization
Complexity, and make system that there is good explorative and autgmentability.
1) podium level：
Including the various applications needed through multidatabase system layer external interface Access Integration information.Podium level includes hard
The configuration interface of part information, operating system and communication protocol for other application layer, accesses data base call podium level and carries
The interface of confession just looks like the same in one database of access, has the function that while access data in multiple databases.
2) semantic layer：
Include two parts：Query compiler device and enforcement engine.
A) query compiler device：
Query compiler device is by query translation into a kind of internal form, referred to as inquiry plan.Inquiry plan is will be in data
The sequence of operations of execution.In general, the operation in inquiry plan is the realization of " relational algebra ".
Query compiler device includes：
1. query analyzer it is by the inquiry of textual form, establishes a tree construction.
2. inquiring preprocessor, it carries out inquiry semantic test (for example, checking that the relationship being previously mentioned in inquiry is
It is no to be all implicitly present in), and certain tree construction conversions are carried out, parsing tree is converted into the initial inquiry plan of expression
Algebraic manipulation symbol tree.
3. query optimizer, initial inquiry plan is converted to the most effective sequence of operation for real data by it.
Query compiler device determines which sequence of operation may be most fast using metadata and about the statistical data of data.
B) enforcement engine：
Enforcement engine is responsible for performing each step in the inquiry plan chosen.In order to be operated to data, enforcement engine
It database data and must be put into buffering area and scheduler interacts, to avoid the data that have been added lock are accessed.Whole
During a, any event will record corresponding log information by log manager.
3) database management system level：
Include graphical configuration interface and ETL rule bases.In multitype database operating process is carried out, to ensure in rule
Table name, field name, field type consistency, meet the constraints of data, the decimation rule established through visual edit needs
Syntactic analysis and verification are carried out, to avoid mistake, ensures the correct execution of data pick-up.
The execution of ETL process is divided into 4 parts：1. it is connected to data source；2. SQL statement is parsed according to decimation rule, and
Using the SQL statement performed after principle of optimality optimization is resolved, from one or more tables of data of source database, inquire
To intermediate result data；3. conversion process intermediate result data, obtains result data；4. result data loads (storage) to target
In the object table of database.It can be seen that ETL process contains the complete information performed needed for data pick-up work, including source
Database, source data table, extraction and perform the principle of optimality, transformation rule, target database, target matrix etc..
Each level of the present invention realizes different functions, below to specifically describe：
1）Podium level
Including the various applications needed through multidatabase system layer external interface Access Integration information.Podium level includes hard
Part information, operating system, database and communication protocol configuration interface, hardware platform mainly has minicomputer, microcomputer server, grasps
There are Windows, Unix, AIX etc. as system, database has Oracle, DB2, SQLSERVER, SYBASE, is connect by unified configuration
Mouthful, it realizes the Seamless integration- of application system, for other application layer, accesses the interface that data base call podium level provides,
Just look like the same in one database of access, have the function that while access data in multiple databases.
2）Semantic layer
Semantic layer realizes the structure for including query compiler device and enforcement engine, and different data source query sentences is different, root
According to data source characteristic, semanteme is determined, and parsed, optimized, performed.
3）Database management system level
Data, the configuration of tables of data and field, including database and tables of data are carried out using the graphic interface of offer
Configuration, service configuration mainly include address of service update and update are connected with database.
4）ETL rule bases
First according to data source difference, different ETL Regularias are determined, secondly for specific data source, formulate ETL rule
Then, the structure in implementation rule library.Rule base is for defining and storing data pick-up, data conversion and data loading rule.
As shown in Figure 2：
STEP1：It obtains and parses source database connection string；Data source includes EXCEL data sources, flat file data
Source, relational database data source etc., wherein relational database data source include Oracle, Sql Server, DB2 etc..Data source
Connection string needs to confirm following field, by taking Oracle as an example, including：Server name, database-name, user, password
Deng.
STEP2：It obtains and parses target database connection string；Target database type is identical with data source category,
Connection string field information is essentially identical.It is assumed that target database is Sql Server.
STEP3：Database, table name, the configuration of field are carried out by graphical configuration interface；By taking individual data source as an example：
Data source（Oracle）Source table data dictionary is as shown in table 1, and source table is as shown in table 2：
Table 1
| Field name | Field type | Major key |
| EquipID | VARchar2（32） | Y |
| EquipName | VARchar2（64） | |
| Sub_Equip_Flag | VARchar2（1） | |
| Up_Down_Flag | VARchar2（1） |
Table 2
| EquipID | EquipName | Sub_Equip_Flag | Up_Down_Flag |
| DA_001 | 1# equipment | N | U |
| DA_001A | 1# equipment | Y | U |
| DA_002 | 2# equipment | N | D |
Target database（Sql Server）Object table data dictionary is as shown in table 3：
Table 3
| Field name | Field type | Major key |
| EquipID | NVARchar（32） | Y |
| EquipName | NVARchar（64） | |
| Sub_Flag | BIT | |
| Equip_Status | BIT |
It is as shown in table 4 to define field matching rule：
Table 4
| Oracle（Source） | Sql Server（Target） |
| EquipID | EquipID |
| EquipName | EquipName |
| Sub_Equip_Flag | Sub_Flag |
| Up_Down_Flag | Equip_Status |
Data type conversion analysis is as shown in table 5：
Table 5
Definition value transformation rule is as shown in table 6：
Table 6
Define data type conversion rule as shown in table 7：
Table 7
It defines data and splits rule：
1）Load target database.
2）Definition splits rule：Existing record, is expressed as Condition1 in target database；In target database
In be exist record, be expressed as Condition2.
3）Define Condition1, rules process method.
4）Define Conditon2, rules process method.
STEP4：Judge the type of database of source database and object library, and carry out ETL rule storehouse matchings；
STEP5：Connect data source and target database；
STEP6：ETL decimation rule character strings are parsed, obtain the SQL statement of Data source table；
STEP7：Start query compiler device, handle SQL statement and verify whether there is conflict and mistake；
STEP8：Starting guide engine（That is query compiler device）, SQL statement is carried out according to ETL rule bases matched result
Optimization；
STEP9：Start enforcement engine, the API that calling platform layer provides performs the SQL statement after optimization；
STEP10：Multiple database ETL data are obtained, are stored in data buffer zone；
STEP11：According to ETL regulation engines, the data of data buffer zone deposit are arranged, and are injected into object table；
STEP12：Whether verification injection is effective, and prompts.
The present invention has been successfully applied in the integration of information system of plurality of classes, such as manufacturing execution system, finance system
System, centralized control system etc. by the application of the present invention, also greatly improve convenience and stability that multiple database integrates.
Claims (4)
1. visualize multiple database ETL integrated approaches, it is characterised in that include the following steps：
Connect source database and target database；It is matched by source database and the ETL of target database, obtains source database
The SQL statement of source table；
The ETL data in multiple source datas library are optimized and performed, obtain to SQL statement and are injected into the target of target database
Table；
The ETL data for optimizing and performing to SQL statement, obtain multiple source datas library are simultaneously injected into target database
Object table includes the following steps：
Processing SQL statement simultaneously optimizes SQL statement according to the matched result of ETL rule bases；
The API that calling platform layer provides performs the SQL statement after optimization and obtains ETL data and be stored in data buffer zone, according to
ETL data are injected the object table of object library by ETL rule bases；
The processing SQL statement and being optimized according to the matched result of ETL rule bases to SQL statement includes the following steps：
SQL statement is established into a tree construction；Semantic test is carried out, and carry out structure conversion to each node of tree construction, it will
Parsing tree is converted to the algebraic manipulation symbol tree for the inquiry plan for representing initial；It is fastest that algebraic manipulation symbol tree is converted into execution
SQL sequences.
2. visualization multiple database ETL integrated approaches according to claim 1, which is characterized in that described to pass through source data
The ETL of library and target database is matched, and the SQL statement for obtaining the source table of source database includes the following steps：
Source database and target database and table name, field is configured, and judges source database and the class database of target database
Type；
Different ETL Regularias are determined according to the type of database of source database and target database, further according to source database
Source table obtains the SQL statement of source table by ETL Regularias.
3. visualize multiple database ETL integrated systems, it is characterised in that including：
Database management system level：Connect source database and target database；Pass through ETL of source database and target database
Match, obtain the SQL statement of the source table of source database；
Semantic layer：The ETL data in multiple source datas library are optimized and performed, obtain to SQL statement and are injected into target data
The object table in library；
The semantic layer includes：
Query compiler device：Processing SQL statement simultaneously optimizes SQL statement according to the matched result of ETL rule bases；
Enforcement engine：The API that calling platform layer provides performs the SQL statement after optimization and obtains ETL data and be stored in data buffering
ETL data are injected the object table of object library according to ETL rule bases by area；
The query compiler device includes：
Query analyzer：SQL statement is established into a tree construction；
Inquire preprocessor：Semantic test is carried out to each node of tree construction, and each node of tree construction is carried out semantic
It checks, and carries out structure conversion, the algebraic manipulation that parsing tree is converted to the inquiry plan for representing initial accords with tree；
Query optimizer：Algebraic manipulation symbol tree is converted to and performs fastest SOL sequences.
4. visualization multiple database ETL integrated systems according to claim 3, which is characterized in that the data base administration
System layer includes：
Graphical configuration interface：Source database and target database and table name, field is configured, and judges source database and number of targets
According to the type of database in library；
ETL rule bases：Different ETL Regularias are determined according to the type of database of source database and target database, further according to
The source table of source database obtains SQL statement by ETL Regularias.
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| CN107169130A (en) * | 2017-06-08 | 2017-09-15 | 贵州优联博睿科技有限公司 | The visual inquiry method and system of a kind of database |
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| CN112783923A (en) * | 2020-11-25 | 2021-05-11 | 辽宁振兴银行股份有限公司 | Implementation method for efficiently acquiring database based on Spark and Impala |
| CN112527815A (en) * | 2020-12-02 | 2021-03-19 | 平安医疗健康管理股份有限公司 | Script migration method and device for database, computer equipment and storage medium |
| CN112434059B (en) * | 2021-01-26 | 2021-06-22 | 腾讯科技（深圳）有限公司 | Data processing method, data processing device, computer equipment and storage medium |
| CN113792098B (en) * | 2021-08-02 | 2023-06-20 | 中国城市规划设计研究院 | Big data visualization method, system and medium based on database SQL (structured query language) imaging |
| CN113934786B (en) * | 2021-09-29 | 2023-09-08 | 浪潮卓数大数据产业发展有限公司 | Implementation method for constructing unified ETL |
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