CN110019334A - A kind of optimization method and its system of multidimensional inquiring analysis - Google Patents
A kind of optimization method and its system of multidimensional inquiring analysis Download PDFInfo
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- 238000005457 optimization Methods 0.000 title claims abstract description 24
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- 238000006116 polymerization reaction Methods 0.000 claims abstract description 22
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Abstract
The present invention relates to the optimization method and its system of a kind of analysis of multidimensional inquiring, this method includes obtaining SQL statement；SQL statement is carried out to analyze assembled processing, obtains new SQL statement；Transaction management is carried out according to new SQL statement, is connected to corresponding database；To the data aggregate in database, and return to the data of polymerization.The present invention utilizes postgresql column memory technology of the Rolap multi-dimensional engine in big data quantity query process, analysis translation and the polymerization of data are carried out to new SQL statement, it is separated using the data installation field of column storage external table by column and single cent part individually stores, when inquiry in the case where no index, the data for only needing to be traversed for respective column greatly reduce the data volume that data need to be traversed for, can compressing data reduce occupy memory space, realize the bottleneck for solving traditional relational data library inquiry data, promote search efficiency, meet high concurrent read-write demand, have high dilatancy and availability.
Description
Technical field
The present invention relates to data processing methods, more specifically refer to a kind of analysis of multidimensional inquiring optimization method and
Its system.
Background technique
The process of big data query analysis is generally basede on row storage relevant database and carries out at present, for relational data
For library, refer to the database for carrying out group organization data using relational model, what relational model referred to is exactly two-dimensional table model, and
One relevant database be exactly as bivariate table and its between connection composed by a data organization, two-dimentional table structure right and wrong
It often close to a concept in the logic world, is easier to understand, therefore closes for other models such as relatively netted, level of relational model
It is that type database has the advantages that be readily appreciated that；General sql like language makes operative relationship type database very convenient, therefore closes
It is easy to use to be that type database has the advantages that；Relevant database has integrality abundant, and entity integrity, reference are complete
Property and user-defined integrality greatly reduce data redundancy and the inconsistent probability of data.
But current relevant database is in use, there are some bottlenecks: the user concurrent of website is very
Height often reaches secondary read-write requests up to ten thousand per second, and for traditional Relational DataBase, hard disk I/O is a very big bottle
Neck；The data volume that website generates daily be it is huge, for relevant database, in a table comprising mass data
Inquiry, efficiency is low-down；In the structure based on web, database be most difficult to carry out it is extending transversely, when one apply
When the user volume and amount of access growing day by day of system, database but have no idea as web server and app server that
Sample comes scalability and load capacity simply by the more hardware of addition and service node.It is small for much needing to provide 24
When persistent service website for, being upgraded to Database Systems and being extended is very painful thing, generally requires to stop
Machine maintenance and Data Migration.For website, transaction consistency, read-write real-time and the complexity SQL of relevant database
For website, use is had no, in relevant database, leads to the main of poor performance the reason is that the association of multilist is looked into
It askes, and the complicated SQL report query of complicated data analysis type.
Therefore, it is necessary to design a kind of optimization method of multidimensional inquiring analysis, realizes and solve traditional relationship type number
According to the bottleneck of library inquiry data, search efficiency is promoted, and meets high concurrent read-write demand, has high dilatancy and availability.
Summary of the invention
It is an object of the invention to overcome the deficiencies of existing technologies, a kind of optimization method of multidimensional inquiring analysis is provided
And its system.
To achieve the above object, the invention adopts the following technical scheme: a kind of multidimensional inquiring analysis optimization method,
The described method includes:
Obtain SQL statement；
The SQL statement is carried out to analyze assembled processing, obtains new SQL statement；
Transaction management is carried out according to new SQL statement, is connected to corresponding database；
To the data aggregate in database, and return to the data of polymerization.
Its further technical solution are as follows: the step of obtaining SQL statement, comprising the following specific steps
Obtain inquiry instruction；
The inquiry instruction is converted into SQL statement.
Its further technical solution are as follows: the step of analyzing assembled processing, obtaining new SQL statement is carried out to the SQL statement,
Comprising the following specific steps
SQL statement is analyzed, base table information is obtained；
According to the basic Table Properties of base table acquisition of information, database table information is formed；
Judge whether the basic Table Properties are column storage external table；
If it is not, then entering end step；
If so, column storage external table information and SQL statement is assembled, form new SQL statement.
Its further technical solution are as follows: to the data aggregate in database, and the step of returning to the data of polymerization, including with
Lower specific steps:
The analysis of new SQL statement is translated into executive plan；
Judge column storage external table instruction whether is carried in executive plan；
If so, polymerizeing to the data in column storage external table, and return to the data of polymerization；
If it is not, then entering end step.
The present invention also provides a kind of optimization systems of multidimensional inquiring analysis, including SQL statement acquiring unit, processing
Unit, connection unit and polymerized unit；
The SQL statement acquiring unit, for obtaining SQL statement；
The processing unit analyzes assembled processing for carrying out to the SQL statement, obtains new SQL statement；
The connection unit is connected to corresponding database for carrying out transaction management according to new SQL statement；
The polymerized unit for the data aggregate in database, and returns to the data of polymerization.
Its further technical solution are as follows: the SQL statement acquiring unit includes that inquiry instruction obtains module and modulus of conversion
Block；
The inquiry instruction obtains module, for obtaining inquiry instruction；
The conversion module, for the inquiry instruction to be converted to SQL statement.
Its further technical solution are as follows: the processing unit includes analysis module, attribute acquisition module, determined property module
And assembling module；
The analysis module obtains base table information for analyzing SQL statement；
The attribute obtains module, for forming database table information according to the basic Table Properties of base table acquisition of information；
The determined property module, for judging whether the basic Table Properties are column storage external table；
The assembling module is used for if so, column storage external table information and SQL statement assembly are formed new SQL language
Sentence.
Its further technical solution are as follows: the polymerized unit includes translation module, carries judgment module and data aggregate
Module；
The translation module, for the analysis of new SQL statement to be translated to executive plan；
The carrying judgment module, for judging whether carry column storage external table instruction in executive plan；
The data aggregate module for polymerizeing if so, storing the data in external table to column, and returns to polymerization
Data.
Compared with the prior art, the invention has the advantages that: a kind of optimization side of multidimensional inquiring analysis of the invention
Method arranges storage external table information to SQL statement assembly, forms new SQL statement, it is more that Rolap is utilized by obtaining SQL statement
Tie up postgresql column memory technology of the engine in big data quantity query process, to new SQL statement carry out analysis translation and
The polymerization of data is separated by column using the data installation field of column storage external table and single cent part individually stores, and when inquiry is not having
In the case where having index, it is only necessary to which the data for traversing respective column greatly reduce the data volume that data need to be traversed for, and can be to data
Compression, which is reduced, occupies memory space, realizes the bottleneck for solving traditional relational data library inquiry data, promotes search efficiency, and
Meet high concurrent read-write demand, has high dilatancy and availability.
The invention will be further described in the following with reference to the drawings and specific embodiments.
Detailed description of the invention
Fig. 1 is a kind of flow chart of the optimization method for multidimensional inquiring analysis that the specific embodiment of the invention provides；
Fig. 2 is the flow chart for the acquisition SQL statement that the specific embodiment of the invention provides；
Fig. 3 is the flow chart for analyze to the SQL statement assembled processing that the specific embodiment of the invention provides；
Fig. 4 be the specific embodiment of the invention provide to the data aggregate in database and return polymerization data process
Figure；
Fig. 5 is a kind of structural block diagram of the optimization method for multidimensional inquiring analysis that the specific embodiment of the invention provides；
Fig. 6 is the structural block diagram for the SQL statement acquiring unit that the specific embodiment of the invention provides；
Fig. 7 is the structural block diagram for the processing unit that the specific embodiment of the invention provides；
Fig. 8 is the structural block diagram for the polymerized unit that the specific embodiment of the invention provides.
Specific embodiment
In order to more fully understand technology contents of the invention, combined with specific embodiments below to technical solution of the present invention into
One step introduction and explanation, but not limited to this.
The specific embodiment as shown in Fig. 1~8, a kind of optimization system of multidimensional inquiring analysis provided in this embodiment
System during being used in using terminal inquiry data, realizes the bottle for solving traditional relational data library inquiry data
Neck promotes search efficiency, and meets high concurrent read-write demand, has high dilatancy and availability.
As shown in Figure 1, a kind of optimization method of multidimensional inquiring analysis, which is characterized in that the described method includes:
S1, SQL statement is obtained；
S2, the SQL statement is carried out to analyze assembled processing, obtains new SQL statement；
S3, transaction management is carried out according to new SQL statement, is connected to corresponding database；
S4, to the data aggregate in database, and return to the data of polymerization.
For above-mentioned S1 step, the step of obtaining SQL statement, comprising the following specific steps
S11, inquiry instruction is obtained；
S12, the inquiry instruction is converted into SQL statement.
For above-mentioned S11 step, specifically about established rules by instruction is passed through after Rolap multi-dimensional engine reception inquiry instruction
Then it is parsed into SQL statement.
Further, above-mentioned S2 step carries out the SQL statement to analyze assembled processing, obtains new SQL statement
Step, comprising the following specific steps
S21, analysis SQL statement, obtain base table information；
S22, according to the basic Table Properties of base table acquisition of information, form database table information；
S22, judge whether the basic Table Properties are column storage external table；
If it is not, then entering end step；
S24, external table information and SQL statement assembly are stored if so, will arrange, forms new SQL statement.
Above-mentioned S21 step specifically carries out secondary operation to SQL statement, by SQL statement about exterior portion to S24 step
The information divided is split, and obtains table name, passes through table name to the basic Table Properties of postgresql data acquisition, forms database table
Information adds external table access sentence in existing SQL statement if database table information is judged to arranging storage external table,
Again it is assembled into new SQL statement, that is, column storage external table information and SQL statement is assembled, forms new SQL statement, it is assembled
Column storage external table information is specifically separated by column using the data installation field of column storage external table and single cent part is individually deposited
Storage, when inquiry in the case where no index, it is only necessary to which the data for traversing respective column greatly reduce the data that data need to be traversed for
Amount.And it can compressing data reduction occupancy memory space.
For above-mentioned S3 step, the good SQL statement of secondary operation is subjected to transaction management and database connects
The connection in pond, re-sends to postgre database, and database returns to query result by column memory module aggregated data.
Further, above-mentioned S4 step, to the data aggregate in database, and the step of returning to the data of polymerization,
Comprising the following specific steps
S41, the analysis of new SQL statement is translated into executive plan；
S42, judge column storage external table instruction whether is carried in executive plan；
S43, it polymerize if so, storing the data in external table to column, and returns to the data of polymerization；
If it is not, then entering end step.
For above-mentioned S41 step to S43 step, Postgresql provides general database ability, but itself does not have
Column storage capacity needs to store external table expansion module cstore_fdw according to column to it.Postgresql is new SQL statement point
Analysis is translated into executive plan, if executive plan carries column storage external table instruction, gives column storage expanding module cstore_
Fdw handles data, and the data having polymerize return to postgresql and return again to.
Configuration installation postgresql column memory module cstore_fdw, handles column storage.Pass through this module
The data installation field of cstore_fdw processing, table is separated by column and single cent part individually stores, in the feelings not indexed when inquiry
Under condition, it is only necessary to which the data for traversing respective column greatly reduce the data volume that data need to be traversed for.And can compressing data reduction account for
Use memory space.Rolap multi-dimensional engine is improved in big data quantity inquiry, the presence of traditional row storage relevant database
Performance bottleneck.Postgresql column memory technology is introduced, data query logic mechanism is transformed, breaks through inquiry bottleneck.
Rolap is based on relevant database multidimensional analysis engine
For example: defining a table, field is Id Name Age Info City, is inserted into 10,000,000 data, time-consuming
7 minutes, occupy storage 390M；Do with dimension Age 0~18,19~30,31~65 analysis to table as column, is point with quantity
Index is analysed, analysis is executed, it is 200 milliseconds time-consuming, it is arranged because only needing to use Age mono- to the statistics of quantity, performance obtains huge
It is promoted.
A kind of optimization method of above-mentioned multidimensional inquiring analysis arranges SQL statement assembly by obtaining SQL statement
External table information is stored, new SQL statement is formed, Rolap multi-dimensional engine is utilized in big data quantity query process
Postgresql column memory technology carries out analysis translation and the polymerization of data to new SQL statement, utilizes column storage external table
Data install that field is separated by column and single cent part individually stores, when inquiry in the case where no index, it is only necessary to which traversal corresponds to
The data of column greatly reduce the data volume that data need to be traversed for, and can compressing data reduce and occupy memory space, realize and solve
The bottleneck of traditional relational data library inquiry data promotes search efficiency, and meets high concurrent read-write demand, has high expansion
Property and availability.
As shown in figure 5, the present embodiment additionally provides a kind of optimization system of multidimensional inquiring analysis comprising SQL language
Sentence acquiring unit 1, processing unit 2, connection unit 3 and polymerized unit 4；
SQL statement acquiring unit 1, for obtaining SQL statement.
Processing unit 2 analyzes assembled processing for carrying out to the SQL statement, obtains new SQL statement.
Connection unit 3 is connected to corresponding database for carrying out transaction management according to new SQL statement.
Polymerized unit 4 for the data aggregate in database, and returns to the data of polymerization.
It include that inquiry instruction obtains module 11 and conversion module 12 for above-mentioned SQL statement acquiring unit 1.
Inquiry instruction obtains module 11, for obtaining inquiry instruction.
Conversion module 12, for the inquiry instruction to be converted to SQL statement.
Above-mentioned SQL statement acquiring unit 1 is specifically by instruction is passed through about after Rolap multi-dimensional engine reception inquiry instruction
Set pattern is then parsed into SQL statement.
Further, above-mentioned processing unit 2 includes analysis module 21, attribute acquisition module 22, determined property module
23 and assembling module 24.
Analysis module 21 obtains base table information for analyzing SQL statement.
Attribute obtains module 22, for forming database table information according to the basic Table Properties of base table acquisition of information.
Determined property module 23, for judging whether the basic Table Properties are column storage external table.
Assembling module 24 is used for if so, column storage external table information and SQL statement assembly are formed new SQL statement.
Above-mentioned processing unit 2 is specifically to carry out secondary operation to SQL statement, the information by SQL statement about exterior portion point
It splits, obtains table name, by table name to the basic Table Properties of postgresql data acquisition, form database table information, such as
Fruit database table information is judged to arranging storage external table, then adds external table access sentence in existing SQL statement, again assembled
It is assembled at new SQL statement, that is, by column storage external table information and SQL statement, new SQL statement is formed, assembly column storage is outer
Portion's table information is specifically separated by column using the data installation field of column storage external table and single cent part individually stores, when inquiry
In the case where no index, it is only necessary to which the data for traversing respective column greatly reduce the data volume that data need to be traversed for.And it can be right
Data compression, which is reduced, occupies memory space.
For above-mentioned connection unit 3, the good SQL statement of secondary operation is subjected to transaction management and database connects
The connection for connecing pond, re-sends to postgre database, and database returns to query result by column memory module aggregated data.
Further, above-mentioned polymerized unit 4 includes translation module 41, carries judgment module 42 and data aggregate mould
Block 43.
Translation module 41, for the analysis of new SQL statement to be translated to executive plan.
Judgment module 42 is carried, for judging whether carry column storage external table instruction in executive plan；
Data aggregate module 43 for polymerizeing if so, storing the data in external table to column, and returns to polymerization
Data.
Postgresql provides general database ability, but itself does not have column storage capacity, needs to deposit it according to column
Store up external table expansion module cstore_fdw.The analysis of new SQL statement is translated into executive plan by Postgresql, if executing meter
It draws and carries column storage external table instruction, give column storage expanding module cstore_fdw processing data, the data having polymerize return
It is returned again to postgresql.
Configuration installation postgresql column memory module cstore_fdw, handles column storage.Pass through this module
The data installation field of cstore_fdw processing, table is separated by column and single cent part individually stores, in the feelings not indexed when inquiry
Under condition, it is only necessary to which the data for traversing respective column greatly reduce the data volume that data need to be traversed for.And can compressing data reduction account for
Use memory space.Rolap multi-dimensional engine is improved in big data quantity inquiry, the presence of traditional row storage relevant database
Performance bottleneck.Postgresql column memory technology is introduced, data query logic mechanism is transformed, breaks through inquiry bottleneck.
Rolap is based on relevant database multidimensional analysis engine
For example: defining a table, field is Id Name Age Info City, is inserted into 10,000,000 data, time-consuming
7 minutes, occupy storage 390M；Do with dimension Age 0~18,19~30,31~65 analysis to table as column, is point with quantity
Index is analysed, analysis is executed, it is 200 milliseconds time-consuming, it is arranged because only needing to use Age mono- to the statistics of quantity, performance obtains huge
It is promoted.
A kind of optimization system of above-mentioned multidimensional inquiring analysis arranges SQL statement assembly by obtaining SQL statement
External table information is stored, new SQL statement is formed, Rolap multi-dimensional engine is utilized in big data quantity query process
Postgresql column memory technology carries out analysis translation and the polymerization of data to new SQL statement, utilizes column storage external table
Data install that field is separated by column and single cent part individually stores, when inquiry in the case where no index, it is only necessary to which traversal corresponds to
The data of column greatly reduce the data volume that data need to be traversed for, and can compressing data reduce and occupy memory space, realize and solve
The bottleneck of traditional relational data library inquiry data promotes search efficiency, and meets high concurrent read-write demand, has high expansion
Property and availability.
It is above-mentioned that technology contents of the invention are only further illustrated with embodiment, in order to which reader is easier to understand, but not
It represents embodiments of the present invention and is only limitted to this, any technology done according to the present invention extends or recreation, by of the invention
Protection.Protection scope of the present invention is subject to claims.
Claims (8)
1. a kind of optimization method of multidimensional inquiring analysis, which is characterized in that the described method includes:
Obtain SQL statement；
The SQL statement is carried out to analyze assembled processing, obtains new SQL statement；
Transaction management is carried out according to new SQL statement, is connected to corresponding database；
To the data aggregate in database, and return to the data of polymerization.
2. a kind of optimization method of multidimensional inquiring analysis according to claim 1, which is characterized in that obtain SQL language
The step of sentence, comprising the following specific steps
Obtain inquiry instruction；
The inquiry instruction is converted into SQL statement.
3. a kind of optimization method of multidimensional inquiring analysis according to claim 1 or 2, which is characterized in that described
SQL statement carries out the step of analyzing assembled processing, obtaining new SQL statement, comprising the following specific steps
SQL statement is analyzed, base table information is obtained；
According to the basic Table Properties of base table acquisition of information, database table information is formed；
Judge whether the basic Table Properties are column storage external table；
If it is not, then entering end step；
If so, column storage external table information and SQL statement is assembled, form new SQL statement.
4. a kind of optimization method of multidimensional inquiring analysis according to claim 3, which is characterized in that in database
Data aggregate, and the step of returning to the data of polymerization, comprising the following specific steps
The analysis of new SQL statement is translated into executive plan；
Judge column storage external table instruction whether is carried in executive plan；
If so, polymerizeing to the data in column storage external table, and return to the data of polymerization；
If it is not, then entering end step.
5. a kind of optimization system of multidimensional inquiring analysis, which is characterized in that including SQL statement acquiring unit, processing unit,
Connection unit and polymerized unit；
The SQL statement acquiring unit, for obtaining SQL statement；
The processing unit analyzes assembled processing for carrying out to the SQL statement, obtains new SQL statement；
The connection unit is connected to corresponding database for carrying out transaction management according to new SQL statement；
The polymerized unit for the data aggregate in database, and returns to the data of polymerization.
6. a kind of optimization system of multidimensional inquiring analysis according to claim 5, which is characterized in that the SQL language
Sentence acquiring unit includes that inquiry instruction obtains module and conversion module；
The inquiry instruction obtains module, for obtaining inquiry instruction；
The conversion module, for the inquiry instruction to be converted to SQL statement.
7. a kind of optimization system of multidimensional inquiring analysis according to claim 6, which is characterized in that the processing is single
Member includes analysis module, attribute acquisition module, determined property module and assembling module；
The analysis module obtains base table information for analyzing SQL statement；
The attribute obtains module, for forming database table information according to the basic Table Properties of base table acquisition of information；
The determined property module, for judging whether the basic Table Properties are column storage external table；
The assembling module is used for if so, column storage external table information and SQL statement assembly are formed new SQL statement.
8. a kind of optimization system of multidimensional inquiring analysis according to claim 7, which is characterized in that the polymerization is single
Member includes translation module, carries judgment module and data aggregate module；
The translation module, for the analysis of new SQL statement to be translated to executive plan；
The carrying judgment module, for judging whether carry column storage external table instruction in executive plan；
The data aggregate module for polymerizeing if so, storing the data in external table to column, and returns to the number of polymerization
According to.
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| CN111538747A (en) * | 2020-05-27 | 2020-08-14 | 支付宝(杭州)信息技术有限公司 | Data query method, device and equipment and auxiliary data query method, device and equipment |
| CN111538747B (en) * | 2020-05-27 | 2023-04-14 | 支付宝(杭州)信息技术有限公司 | Data query method, device and equipment and auxiliary data query method, device and equipment |
| CN116861455A (en) * | 2023-06-25 | 2023-10-10 | 上海数禾信息科技有限公司 | Event data processing method, system, electronic device and storage medium |
| CN116861455B (en) * | 2023-06-25 | 2024-04-26 | 上海数禾信息科技有限公司 | Event data processing method, system, electronic device and storage medium |
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