CN103577590A - Data query method and system - Google Patents
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- CN103577590A CN103577590A CN201310561848.7A CN201310561848A CN103577590A CN 103577590 A CN103577590 A CN 103577590A CN 201310561848 A CN201310561848 A CN 201310561848A CN 103577590 A CN103577590 A CN 103577590A
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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
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2453—Query optimisation
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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
- G06F16/22—Indexing; Data structures therefor; Storage structures
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- G06F16/2264—Multidimensional index structures
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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
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Abstract
The invention discloses a data query method and system. The data query method includes the steps of firstly, extracting various dimensionalities in a business system, building a plurality of logical tables of business data for describing the business system, building incidence relations between the logical tables and the dimensionalities, then building mapping relations between a physical table and the logical tables according to the physical table of the business system, writing logical query statements according to the logical tables and a logical data query grammar defined according to a rule, finally, according to the mapping relations between the physical table and the logical tables, converting the logical query statements into structuring query statements, and executing the structuring query statements in a database to complete querying of the business data. According to the data query method and system, the complexity of data table understanding and writing can be reduced, and the understandability of a data structure of the business system is improved.
Description
Technical field
The present invention relates to data storage and inquiring technology field, be specifically related to a kind of new data enquire method and system.
Background technology
RDB(Relational Database, relational database) and on SQL(Structured Query Language, Structured Query Language (SQL)) be most widely used data storage and query scheme in current information system.RDB is stored in some physics tables (elementary cell of store data in relational database by data, there is the record that some data structures are identical to form, when context is clear, will be called for short table) in, each table consists of the identical record of some data structures, and the attribute of record is called field.Some field be appointed as the major key of table wherein, requires the value of these fields (group) unique in record in table (do not have two values that are recorded in these fields identical), can be a unique definite record by this group field value like this.
When recording of another table will be quoted in the record of certain table (if department's field of employee's table is by the record of quoting in department table), set up reference list to the external key of referenced table, in reference list, some of every record is called the major key of certain record that the field value of external key is referenced table.A table can be set up a plurality of external keys of quoting other table, can also set up the external key (as the spouse's field in person chart is still quoted the record in person chart) of quoting this table, also may set up a plurality of associations (area table is all quoted in as regional in the birth in person chart and operational area) for same referenced table.
The data of an operation system may have a plurality of tables to form, all may be relevant between these tables, and associated also more than one sometimes, associated with this table oneself even in addition.Like this, in RDB, these tables will form a reticulate texture, and the associated quantity between N table is N
2level other, be unfavorable for that very much application developer understands the architecture of business datum.Meanwhile, the degree of coupling between table and table is also very high, causes the part of application program to safeguard that modification is all very difficult.
During recording in will taking out a plurality of relevant tables, SQL adopts connective grammar to write, its ultimate principle can be understood as first does complete multiplication cross (being cartesian product) by the record in a plurality of tables, re-use the filtercondition that the external key of reference list and the external key of referenced table equate multiplication cross unnecessary record is out removed, thereby obtain last result.If there be the N of relating to table, all likely relevant between any two, the connection filtercondition that may write out has N* (N-1)/2, and complexity is also N
2level other, cause writing very difficult.
Summary of the invention
For the defect existing in prior art, the object of the present invention is to provide a kind of data enquire method and system, reduce the complexity that tables of data is understood and write, improve the intelligibility of the data structure of operation system.
For achieving the above object, the technical solution used in the present invention is as follows:
, comprise the following steps:
(1) extract the every dimension in operation system;
(2) set up some logical tables of described operation system, and set up the incidence relation between each logical table and described dimension; Described logical table is for describing the business datum of operation system;
(3), according to the physics table of operation system, set up the mapping relations between physics table and each logical table; Described physics table is for the business datum of storage service system;
(4) according to logical table and the logical data query grammar of pressing rule definition, write Boolean query statement LSQL;
(5) according to the mapping relations between physics table and logical table, Boolean query statement LSQL is converted into structured query sentence SQL, and by the inquiry of SQL statement complete business datum in database.
Further, a kind of data enquire method as above, in step (1), during every dimension in extracting operation system, also comprises and extracts the level that every dimension comprises, and determines the calculated relationship between the level of every dimension; The level of described every dimension comprises basal layer and gathers layer; The described layer that gathers refers to that this level can be calculated by other one or more basic levels.
Further, a kind of data enquire method as above, in step (2), described logical table comprises some logical fields, the concrete mode of setting up the incidence relation between logical table and described dimension is:
The external key of logical table is set to point to the field of the level of certain dimension or certain dimension, and the major key of logical table is field or a unique field groups of a plurality of value that value is unique in logical table.
Further, a kind of data enquire method as above, the concrete mode of setting up the mapping relations between physics table and logical table is:
A) in physics table, select the base table corresponding with each logical table, each logical field in logical table can both be calculated by described base table;
B) set up the major key of logical table and the mapping relations between base table major key;
C) set up the calculated relationship between non-major key logical field and base table field in logical table.
Further, a kind of data enquire method as above, in step a), determines the base table corresponding with it according to the data area of the described business datum of logical table.
Further again, a kind of data enquire method as above, in step c), the calculated relationship in described logical table between non-major key logical field and base table field refers to that the expression formula that each logical field in logical table consists of base table field represents.
Further, a kind of data enquire method as above, in step (5), the concrete mode that LSQL query statement is converted into SQL statement is:
According to described logical data query statement LSQL, obtain the business datum item in statement, the mapping relations according between described business datum item and logical table and physics table, change into the SQL query statement based on physics table by LSQL statement.
, comprising:
Dimension abstraction module, for extracting every dimension of operation system;
Logical table is set up module, sets up some logical tables of described operation system, and sets up the incidence relation between each logical table and described dimension; Described logical table is for describing the business datum of operation system;
Mapping relations are set up module, for according to the physics table of operation system, set up the mapping relations between physics table and each logical table;
Boolean query statement design module, for according to logical table and the logical data query grammar of pressing rule definition, writes Boolean query statement LSQL;
Data query module, is converted into structured query sentence SQL for the mapping relations according between physics table and logical table by Boolean query statement LSQL statement, and SQL statement is carried out to the inquiry with finishing service data in database.
Further, a kind of data query system as above, the level that described dimension abstraction module also comprises for extracting every dimension, and the calculated relationship between the level of definite every dimension; The level of described every dimension comprises basal layer and gathers layer; The described layer that gathers refers to that this level can be calculated by other one or more basic levels.
Further, a kind of data query system as above, described logical table is set up module and is comprised:
External key setting unit, for the external key of logical table is set, the external key of logical table is set to point to the field of the level of certain dimension or certain dimension;
Major key setting unit, for the major key of logical table is set, the major key of logical table is field or a unique field groups of a plurality of value that value is unique in logical table.
Further again, a kind of data query system as above, described mapping relations are set up module and are comprised:
Base table selected cell, for selecting the base table corresponding with each logical table at physics table, each logical field in logical table can both be calculated by described base table;
Major key relation is set up unit, for setting up the major key of logical table and the mapping relations between base table major key;
Field relation is set up unit, for setting up the calculated relationship between the non-major key logical field of logical table and base table field.
Further, a kind of data query system as above, described data query module comprises:
Statement converting unit, is converted into structured query sentence SQL statement for the mapping relations according between physics table and logical table by Boolean query statement LSQL statement, and the concrete mode of conversion is:
According to described logical data query statement LSQL, obtain the business datum item in statement, the mapping relations according between described business datum item and logical table and physics table, change into the SQL query statement based on physics table by LSQL statement;
Query unit, for the inquiry in the complete business datum of database by SQL statement.
Beneficial effect of the present invention is:
1) data model netted in relational database RDB is transformed into bus structure, each logical table is all associated with the dimension extracting in advance, and between logical table, no longer includes association.Associated quantity and logical table quantity Matching, complexity be N level other.This will greatly improve the data structure intelligibility of operation system.
2) owing to no longer including association between logical table, thereby reduce the degree of coupling between table, can carry out easily like this part of system and revise and upgrade and add, delete certain subsystem.
3) can be by design LSQL grammer (the logical data query language based on the method for the invention and system) on the basis of logical model, also only need to be for gathering dimension alignment when writing multilist correlation inquiry, and need not be concerned about the association between table, make to write complexity and also fall into N rank.
4) subordinate list pointing to for single external key is quoted, and LSQL can be used object mode to quote simply, simply regards the multilist association of this form as single table inquiry, greatly reduces the complexity of understanding and writing.
Accompanying drawing explanation
Fig. 1 is the structured flowchart of a kind of data query system in embodiment;
Fig. 2 is the process flow diagram of a kind of data enquire method in embodiment;
Fig. 3 is the tables of data that in embodiment, sale management system needs;
Fig. 4 determines the schematic diagram of logical table external key in embodiment;
Fig. 5 determines the schematic diagram of logical table major key in embodiment.
Embodiment
Below in conjunction with Figure of description and embodiment, the present invention is described in further detail.
For better explanation the present invention, first some abbreviations and Key Term in this embodiment are made an explanation:
RDB:Relational Database, relational database
SQL:Structured Query Language, Structured Query Language (SQL), a kind of program language for access relational databases data query
Physics table: the elementary cell of store data in relational database, has the record that some data structures are identical to form.When context is clear, will be called for short table.
The field of physics table: the attribute that forms physics table record.
The major key of physics table: the upper unique field (group) of value of each record in table.
The external key of physics table: the concept of relational database, certain table reference be changed to external key during the Major key of another table.
Dimension: some are for the standard of statistical summaries, and its span is determined and known in advance.As time, area, sex etc., be called for short dimension.
Layer: dimension can have many levels, if the time can be per diem, month, year, week etc. level gather, area can be divided into the multilayers such as Guo,Sheng, city.Between level, can there is calculated relationship
Logical table: the tables of data concept in the present invention, can set up certain mapping relations with some physics tables; When context is clear and definite, will be called for short table
The field of logical table: the field of logical table
The external key of logical table: in logical table, value is the field of dimension (or its layer)
The major key of logical table: respectively record the unique external key of value (group) in table
Subordinate list: the logical table that certain dimension (or its layer) of take is major key
Broad sense external key: recursive definition is the external key (or its layer) of the subordinate list of external key (or its layer) or broad sense external key
LSQL:Logical SQL, the logical data query language based on System Design of the present invention
Fig. 1 shows the structured flowchart of a kind of data query system in the specific embodiment of the invention, as can be seen from Figure, this system mainly comprises that dimension abstraction module 11, logical table are set up module 12, mapping relations are set up module 13, Boolean query statement design module 14 and data query module 15, wherein:
Logical table is set up some logical tables that module 12 is set up described operation system, and sets up the incidence relation between each logical table and described dimension; Described logical table is for describing the business datum of operation system; This module comprises for the external key of logical table is set, the external key of logical table is set to point to the external key setting unit of field of the level of certain dimension or certain dimension, and for the major key of logical table is set, the major key of logical table is the major key setting unit of the unique field of value or the unique field groups of a plurality of value in logical table.
Mapping relations are set up module 13 for according to the physics table of operation system, set up the mapping relations between physics table and each logical table; This module comprises for select the base table selected cell of the base table corresponding with each logical table at physics table, each logical field in logical table can both be calculated by described base table, for setting up the major key of logical table and the major key relation of the mapping relations between base table major key is set up unit, and set up unit for setting up the field relation of the calculated relationship between the non-major key logical field of logical table and base table field.
Boolean query statement design module 14, for according to logical table and the logical data query grammar of pressing rule definition, is write Boolean query statement LSQL;
Statement converting unit, is converted into structured query sentence SQL statement for the mapping relations according between physics table and logical table by Boolean query statement LSQL statement, and the concrete mode of conversion is:
According to described logical data query statement LSQL, obtain the business datum item in statement, the mapping relations according between described business datum item and logical table and physics table, change into the SQL query statement based on physics table by LSQL statement;
Query unit, for the inquiry in the complete business datum of database by SQL statement.
Fig. 2 shows the process flow diagram of a kind of data enquire method in the specific embodiment of the invention, and the method comprises the following steps:
Step S21: each dimension that extracts operation system;
The operation system of opening relationships database RDB as required, extracts the level that the every dimension that may use in operation system and every dimension comprise, and determines the calculated relationship between the level of every dimension.Dimension in present embodiment is some standards for statistical summaries operation system or correlation parameter, and its span is determined and known in advance.
Wherein, the level that dimension comprises comprises basal layer and gathers layer; The described layer that gathers refers to that this level can be calculated by one or more other basal layer.
For different operation systems, its required dimension of using is different, and for example, for a sale management system, its every dimension that will use just need to be tieed up by client, area dimension, date dimension and product dimension etc.And the included concrete level of each dimension is also different, for example, for time dimension, the level that this dimension comprises just comprises day, the moon, week, year etc., and in these levels, day is basal layer, and the moon is for gathering layer (can be calculated by day), same year, week are all also to gather layer, all can be calculated by day, and year also can be calculated by the moon.And calculated relationship between each level is also clear and definite, can determine, as the calculated relationship between Zhou Yu, the calculated relationship between Nian Yuyue etc. is all confirmable.But for the moon and these two levels of week, because the moon cannot be calculated by week, there is no calculated relationship between the two.
Calculated relationship between the level comprising by definite each dimension, makes the business datum of operation system gather or align according to the different levels of dimension.
Step S22: set up the logical table of business datum, and set up the incidence relation between logical table and dimension;
According to the needs of operation system, set up some logical tables of operation system, and set up the incidence relation between each logical table and described dimension.
Logical table is for describing the business datum of operation system, and logical table consists of some logical fields.As, for a sale management system, its logical table can comprise order table, returned money table, client's table etc., order table can be comprised of some fields such as order ID, Shipping Dates.
Wherein, the described incidence relation of setting up between each logical table and described dimension refers to the incidence relation of setting up between the dimension extracting in the external key of logical table and major key and step S21, or the incidence relation of the layer of the dimension extracting in the external key of logical table and major key and step S21, specific as follows:
The external key of logical table is set to point to the field of the level of certain dimension or certain dimension, sets up associated between logical table external key and dimension; The major key of logical table is field or a unique field groups of a plurality of value that value is unique in logical table, and the external key of logical table is for pointing to the field of the layer of certain dimension or dimension, and major key by the logical table record in can unique definite logical table.
By setting up above-mentioned incidence relation, just existing netted physics table relational model has been become to the logical table relational data model of bus type, between logical table, there is no direct relation, all logical tables are all set up associated with dimension (a similar bus).In the present invention, the external key of logical table is the field that value in logical table is dimension (or its layer), and major key is in logical table, respectively to record the unique field of value or field groups.
Step S23: according to the physics table of operation system, set up the mapping relations between physics table and logical table;
According to the physics table of operation system, set up the mapping relations between physics table and each logical table.Wherein, described physics table is for the business datum of storage service system, and physics table can be newly-built according to the needs of operation system, also can from existing database, take out physics list structure.Set up between physics table and logical table the concrete mode of mapping relations as follows:
A) in physics table, select the base table corresponding with each logical table, each logical field in logical table can both be calculated by described base table;
B) set up the major key of logical table and the mapping relations between base table major key;
C) set up the calculated relationship between non-major key logical field and base table field in logical table, this calculated relationship refers to that the expression formula that each logical field in logical table consists of base table field represents, modal situation is directly corresponding certain the base table field of logic finger tip.
Wherein, the physics table corresponding with each logical table is one mostly, is a plurality of sometimes, according to the data area of the described business datum of logical table, determines that it is corresponding with which or which physics table.If the logical table relevant to order is logic order table with corresponding for storing the physics order table of order data.Generally, it between logical table major key and major key with its corresponding base table, is relation one to one, in particular cases, the major key of possible logical table is not corresponding with the major key of base table, but still can according to the described mathematical logic of logical table, set up the mapping relations of its major key and base table major key, opening relationships is determined according to concrete condition.
Step S24: user need to write logical data query statement by the logical data query grammar of prior design according to inquiry;
Step S25: carry out data query according to the mapping relations between logical data query language and logical table and physics table in relational database.
User is according to the needs of its inquiry, according to logical table and the logical data query grammar of pressing rule definition, writing Boolean query statement is LSQL statement, when carrying out the inquiry of data, according to the mapping relations between the physics table of setting up in step S23 and logical table, it is existing SQL statement that Boolean query statement LSQL is converted into structured query sentence, and by the inquiry of SQL statement complete business datum in database.Data query mode concrete in present embodiment is as follows:
The Boolean query statement (being called LSQL query statement in present embodiment) of writing according to described logical data query language rule, obtain the business datum item in Boolean query statement, according to the mapping relations between described business datum item and logical table and physics table, described LSQL statement is changed into the physics query statement (being SQL query statement) based on physics table, finally by the inquiry of physics query statement complete data in relational database.
It should be noted that, LSQL in present embodiment is a kind of self-defining grammer system, to design for description problem is more convenient, it doesn't matter with concrete operation system, to any operation system, can be applicable to, similarly be another kind of SQL grammer, need to just can not design for specific business datum.Logical data query grammar and Boolean query statement are not unique, user can be according to the logical table of setting up, and the relation between logical table and the required dimension of operation system is designed query grammar and the statement of different-style, as long as the statement of designing and grammer can embody the incidence relation between logical table and operation system data (dimension), and can be according to the mapping relations between logical table and corresponding physics table, the conversion between completion logic statement and physics query statement.
A kind of for realizing the data query grammer of the method for the invention and system by defining in present embodiment, designed the logical data query language of system, and in relational database, complete inquiry based on this language, that is to say and will by logical data query language, complete the definition of query grammar based on data query mode of the present invention, then change into database SQL and carry out.In present embodiment, write the logical data query language based on System Design of the present invention as LSQL statement, what step S24 realized is to convert LSQL to database SQL to carry out.
Below in conjunction with specific embodiment, the present invention is further described.
Embodiment
Operation system in the present embodiment is a sale management system, needs by area and time management client's order and returned money, and the business datum table existing in this system as shown in Figure 3.
Step 1, first, extracts required every dimension of using in this sale management system, comprises that client ties up, area dimension, date peacekeeping product dimension, and the level that each dimension comprises is specific as follows:
Area dimension: country, province, city
Date dimension: year, month (comprising year information), day (comprising information on days)
Determine in each dimension basal layer and gather the calculated relationship between layer, specific as follows:
Date dimension: year=int (month/100)
Year=year (day)
The moon=year (day) * 100+month (day)
As: year is 2012, and the moon is 201208, and day is 2012-08-01
Area dimension: country=left (province, 2)
Country=left (city, 2)
Province=left (city, 4)
As: country is 01, and province is 0122, and city is 01220315
Wherein, above-mentioned middle year(), month() and left() be all the function in SQL, as year(A) represent to return the integer in the time in the appointed day, month(A) represent to return the integer of the moon in the appointed day, left(n) represent to get the front n position in a character string, as left (province, 2) represents to get first 2 in the character string of province.
Step 2, set up the incidence relation of logical table and logical table and dimension (or layer), specific as follows:
A) set up the logical table of describing in logic business datum, logical table consists of some logical fields
The sale management system of the present embodiment is according to service needed, and the logical field that the logical table of foundation and each logical table comprise is specific as follows:
Order table (order id, client, Shipping Date, date of issue, product, the amount of money)
Returned money table (returned money id, client, date, the amount of money)
Client shows (Customer ID, customer name, location)
City table (id， city, city title)
Province table (id， province, province title)
Country's table (national id, national title)
Product table (product IDs, name of product)
B) set up the incidence relation between logical table and dimension
By determining external key and the major key of logical table, set up associated between logical table and dimension.The external key of logical table is set to point to the field of the level of certain dimension or certain dimension, and the major key of logical table is field or the unique field groups of a plurality of value that value is unique.
In the present embodiment, definite result of logical table external key and major key is as shown in table 4 and table 5, in Fig. 4 and Fig. 5, only show order table, returned money table and the external key of client's table and definite result of major key, for order table, its external key is client, date of issue, product and Shipping Date, and major key is order ID; For returned money table, its external key is client and date, and major key is returned money ID; For client's table, its external key is Customer ID and location, and major key is Customer ID.
By this step, just original netted table relational model has been become to the data model of bus type, there is no direct relation between table, all tables are all set up associated with dimension (a similar bus).
Step 3, set up the mapping relations between physics table and logical table, specific as follows:
A) from ready-made database, take out physics list structure, the physics list structure in the present embodiment is as follows:
order(orderId,customer,signDate,product,deliverDate,amount)
income(incomeId,customer,date,amount)
customer(customerID,customerName,area)
city(cityID,cityName)
province(provinceID,provinceName)
country(countryID,countryName)
product(productID,productName)
In the present embodiment, in order to distinguish physics table and logical table, the logical table in step 2 is described with Chinese, and the physics table in this step is described with English.
B) for each logical table, in physics table, select the base table that some major keys are identical corresponding with it, to guarantee to demonstrate,prove each field of logical table and can both be calculated by these base tables, in the present embodiment, the corresponding relation of logical table and base table is as follows:
Order---> order table income---> returned money table customer---> client table
City---> city table province---> province table country---> country table
Product---> product table
C) set up the mapping relations between logic major key and each base table major key
Order.orderID---> order table. order ID
Income.incomeID---> returned money table. returned money ID
Customer.customerID---> client's table. Customer ID
City.cityID---Biao. city, > city ID
Province.provinceID---Biao. province, > province ID
Country.countryID---> country table. national ID
Product.productID---> product table. product IDs
In the present embodiment, between the major key of logical table and base table major key, be relation one to one, as corresponding with the orderID of physics table order in the major key order ID of logic order table.
D) set up the calculated relationship between other non-major key logical field and base table field, be expression formula consisting of base table field of each logical field definition, modal situation is directly corresponding certain the base table field of logical field.
Structure in the present embodiment after completing steps c and steps d is as shown in the table:
| Logical table field | Physics literary name section (or its expression formula) |
| Order table. order ID | order.orderId |
| Order table. client | order.customer |
| Order table. date of issue | order.signDate |
| Order table. product | order.product |
| Order table. Shipping Date | order.deliverDate |
| Order table. the amount of money | order.amount |
| Returned money table. returned money ID | income.incomeID |
| Returned money table. client | income.customer |
| Returned money table. the date | income.date |
| Returned money table. the amount of money | income.amount |
| Client's table. Customer ID | customer.customerID |
| Client's table. customer name | customer.customerName |
| Client's table. location | customer.area |
| Biao. city, city id | city.cityID |
| Biao. city, city title | city.cityName |
| Biao. province, province id | province.provinceID |
| Biao. province, province title | province.provinceName |
| Country's table. national id | country.countryID |
| Country's table. national title | country.countryName |
| Product table. product IDs | product.productID |
| Product table. name of product | product.productName |
Step 4: design logic query statement LSQL;
Step 5: convert LSQL to database SQL and carry out
For convenience, defined the grammer (can define according to this principle the grammer of other form) of a kind of LSQL in present embodiment, the partial key defining in this grammer is listed below:
SELECT?T.x,…ON?D#L,…FROM?T?WHERE…BY?T.x?AT?D?JOIN?T…HAVING…
Wherein, SELECT, FROM, WHERE and HAVING are the conventional key words in SQL statement, and its implication is identical with SQL statement; JOIN, ON, BY and AT be the key word having in SQL but given new meaning and usage at LSQL, and concrete meaning sees below.
In the LSQL grammer of the present embodiment, need being described as follows of the parameter of using and the Boolean query statement that some being concrete::
1) layer of dimension (external key of logical table) represents with #, and as K#L, expressions dimension is K, the layer that L is K, specifically as:
Date #, the date # month, regional # is national, regional # province
2) field of broad sense external key can directly be used. and operational character is write out, and quotes subordinate list field and is equivalent to this table
Subordinate list field is the field of another table in physics table, it not the field of that table after FROM, be the field of foreign key field Compass in FROM table, if need not this literary style, will write the multiplication cross computing of two tables, relate to two tables, literary style is very complicated, and after the literary style with broad sense external key, the field of subordinate list is the equal of just that this literary name section is equally quoted, only become a table handling, problem has been simplified many.For example: the external key of logical table can multilayer be pointed out, such as the external key " client " of order table, points to client's table, the external key " location " in client's table, " location " is exactly the broad sense external key of order table so.
In statement T.K.F, T is table, and K is external key, and F is the field of external key Compass; Concrete, as order. client. location, the external key client of order table points to client's table, and the location field in client's table is exactly the broad sense external key of order table;
Equally, in statement T.K#L.F, T is table, and K is external key, the layer that L is K, and F is the field of external key Compass; Concrete, as client. # province, location. province title, the external key of client's table is that the identity name field that the province layer of location points in the table of Biao， province, province is exactly the broad sense external key of client's table.
3) select data item and can add polymerization calculating, as T.SUM (F), T.COUNT (1) etc.
Concrete as: order .sum (amount of money), client .count (1)
SUM and COUNT are also the key words of SQL, sue for peace exactly and count, order .SUM (amount of money) is exactly the amount field value summation to order table, and client .COUNT (1) shows counting to client, COUNT function need to have individual parameter, in the present embodiment, by parameter 1, represents
2) and 3) in operational character. be distinguishing, operational character. what be afterwards and be what is relevant above. be table above. be exactly the field of this table afterwards, this also has an agreement in SQL, at LSQL, also adopts; If. be external key above. after be the field of external key Compass, at SQL, do not support this literary style, be that the LSQL of the present embodiment arranges again.
4) source of select key table registration certificate; After FROM key word, can have a plurality of tables, represent that data take out from a plurality of tables, between multilist, with JOIN key word, connect, but not table with show between associated description entry;
As statement select client table. customer name, expression data are taken from the customer name field of client's table;
Statement:
The order table .sum(amount of money) from order table by client join client table, represents customer name and this client's order amount of money sum to be mapped; The amount of money of order table goes grouping to add up to by client, the corresponding total volume of each client, and BY is equivalent to the GROUP BY in SQL, has used the field of two tables in the SELECT clause of this SQL, upper another table of all JOIN again;
5) after BY key word, being its Classifying Sum field of showing above, must be the broad sense external key of this table, as omitted the major key with this table
As statement:
Select returned money table .sum (amount of money), the order table .sum(amount of money) from order table by client join returned money table by client, represent to add up the returned money amount of money and the order amount of money by client.
Statement:
Select client table. customer name, the order table .sum(amount of money) from order table by client join client shows by Customer ID (Customer ID can omit, because be the major key that client shows), represents to list customer name and its order amount of money adds up to by Customer ID.
6) parameter after ON key word is that target gathers dimension (and layer), uses the union of the BY of all tables during omission
Statement:
Select returned money table .sum (amount of money), the order table .sum(amount of money) on, client
From order table by Shipping Date #, client
Join returned money table by date #, client;
Represent by client and year adding up the returned money amount of money and the order amount of money
Above-mentioned statement also can be write as
Select returned money table .sum (amount of money), the order table .sum(amount of money)
From order table by Shipping Date #, client
Join returned money table by date #, client
7) can play another name to parameter after ON, to describe the corresponding relation of BY and ON with AT key word after BY, not describe corresponding relation the type by tieing up is automatically corresponding
Statement:
The select order table .sum(amount of money) on as delivers year, and a year as signs a bill year
From order table by Shipping Date # at delivers year, and date of issue # at signs a bill year
Expression is added up the order amount of money by delivery year with the year of signing a bill.
8) WHERE is for the condition of selecting of showing above
Statement:
Select returned money table .sum (amount of money), the order table .sum(amount of money) on, client
From order table where client. # province, location=' Hebei ' by Shipping Date #, client
Join returned money table where client. # province, location=' Hebei ' by date #, client
This statement list is shown in 6) in enumerate on the basis of statement, only add up the data that client location is Hebei province
Also can be write as:
Select returned money table .sum (amount of money), the order table .sum(amount of money)
On, client where client. # province, location=' Hebei '
From order table by Shipping Date #, client
Join returned money table by date #, client
9) HAVING is the condition of selecting for net result
The select sum(amount of money)
On, client
From order table by Shipping Date #, client
The having sum(amount of money) >10000
Suppose that former LSQL is:
Select returned money table .sum (amount of money), order table .sum (amount of money)
On, client where client. # province, location. province title=' Hebei '
From order table by Shipping Date #, client
Join returned money table by date #, client
Having order table .sum (amount of money) >10000
LSQL is converted to the step of physics SQL:
A) polishing abridged BY, ON, AT parameter, BY omits the major key with this table, and ON omits the union with BY, and AT omits and uses dimension of the same type corresponding successively
After polishing, LSQL becomes:
Select returned money table .sum (amount of money), order table .sum (amount of money)
On, client where client. # province, location. province title=' Hebei '
From order table by Shipping Date # at, client at client
Join returned money table by date # at, client at client
Having order table .sum (amount of money) >10000
B) for each table after FROM key word in LSQL, find out the associated data item using in LSQL
Finding out data item adds shown in surplus body as follows:
Select returned money table .sum (amount of money), order table .sum (amount of money)
On, client where client. # province, location. province title=' Hebei '
From order table by Shipping Date # at, client at client
Join returned money table by date # at, client at client
Having order table .sum (amount of money) >10000
C) according to the data item of using, generate the SQL subquery connecting based on base table
First subquery:
(SELECT YEAR (Shipping Date), client, sum (amount of money) FROM order table)
Second subquery:
(SELECT YEAR (date), client, sum (amount of money) FROM returned money table)
D), if quote subordinate list field in broad sense external key mode in data item, recursively connect again the base table of upper subordinate list
First subquery:
(SELECT YEAR (order table. Shipping Date), order table. client, sum (order table. the amount of money) FROM order table, province table, client show where left (client table. location, 2)=Biao. province, province ID and client table. Customer ID=order table. client)
Second subquery:
(SELECT YEAR (returned money table. the date), returned money table. client, sum (returned money table. the amount of money) FROM returned money table, province table, client show where left (client table. location, 2)=Biao. province, province IDand client table. Customer ID=returned money table. client)
E) WHERE parameter in spelling
First subquery:
(SELECT YEAR (order table. Shipping Date), order table. client, sum (order table. the amount of money) FROM order table, province table, client show where left (client table. location, 2)=Biao. province, province ID and client table. Customer ID=order table. Biao. province, client and province title=' Hebei ')
Second subquery:
(SELECT YEAR (returned money table. the date), returned money table. client, sum (returned money table. the amount of money) FROM returned money table, province table, client show where left (client table. location, 2)=Biao. province, province IDand client table. Customer ID=returned money table. Biao. province, client and province title=' Hebei ')
Whether the BY parameter that f) judges table is its major key, if not, according to BY parameter, generates GROUP BY statement
First subquery:
(SELECT YEAR (order table. Shipping Date), order table. client, sum (order table. the amount of money) FROM order table, province table, client show where left (client table. location, 2)=Biao. province, province ID and client table. Customer ID=order table. Biao. province, client and province title=' Hebei ' GROUP BY YEAR (order table. Shipping Date), order table. and client)
Second subquery:
(SELECT YEAR (returned money table. the date), returned money table. client, sum (returned money table. the amount of money) FROM returned money table, province table, client show where left (client table. location, 2)=Biao. province, province ID and client table. Customer ID=returned money table. Biao. province, client and province title=' Hebei ' GROUP BY YEAR (returned money table. the date), returned money table. and client)
G) subquery producing for each table is connected to (JOIN) according to the corresponding relation of ON and AT
SELECT T_1., T_1. client, the T_2. returned money amount of money, the T_1. order amount of money
FROM
(SELECT YEAR (order table. Shipping Date) year, order table. client, sum (order table. the amount of money) order amount of money FROM order table, province table, client show where left (client table. location, 2)=Biao. province, province ID and client table. Customer ID=order table. Biao. province, client and province title=' Hebei ' GROUP BY YEAR (order table. Shipping Date), order table. and client) T_1
join
(SELECT YEAR (returned money table. the date) year, returned money table. client, sum (returned money table. the amount of money) returned money amount of money FROM returned money table, province table, client show where left (client table. location, 2)=Biao. province, province ID and client table. Customer ID=returned money table. Biao. province, client and province title=' Hebei ' GROUP BY YEAR (returned money table. the date), returned money table. and client) T_2
ON T_1.=T_2. AND T_1. client=T_2. client
H) HAVING parameter in spelling
SELECT T_1., T_1. client, the T_2. returned money amount of money, the T_1. order amount of money
FROM
(SELECT YEAR (order table. Shipping Date) year, order table. client, sum (order table. the amount of money) order amount of money FROM order table, province table, client show where left (client table. location, 2)=Biao. province, province ID and client table. Customer ID=order table. Biao. province, client and province title=' Hebei ' GROUP BY YEAR (order table. Shipping Date), order table. and client) T_1
join
(SELECT YEAR (returned money table. the date) year, returned money table. client, sum (returned money table. the amount of money) returned money amount of money FROM returned money table, province table, client show where left (client table. location, 2)=Biao. province, province ID and client table. Customer ID=returned money table. Biao. province, client and province title=' Hebei ' GROUP BY YEAR (returned money table. the date), returned money table. and client) T_2
ON T_1.=T_2. AND T_1. client=T_2. client
WHERE T_1. order amount of money >10000
Above step is a theoretic description, also has the possibility of various optimizations in actual implementation procedure, and the mode that further describes final connection type (FULL/LEFT etc.), but ultimate principle can not change.
The LSQL statement relating in the present embodiment, for the convenience that user understands, has adopted a lot of key words and implication thereof in SQL grammer, but this mode of writing not is unique, can carry out other forms of writing according to principle of the present invention.Data enquire method of the present invention, the physics gauge seal of relational database RDB is dressed up to some logical tables, and design corresponding LSQL and carry out the data in query logic table, the data model in relational database, by the netted wire of changing into, is greatly reduced to the complexity of data query.
Obviously, those skilled in the art can carry out various changes and modification and not depart from the spirit and scope of the present invention the present invention.Like this, if within of the present invention these are revised and modification belongs to the scope of the claims in the present invention and equivalent technology thereof, the present invention is also intended to comprise these changes and modification interior.
Claims (12)
1. a data enquire method, comprises the following steps:
(1) extract the every dimension in operation system;
(2) set up some logical tables of described operation system, and set up the incidence relation between each logical table and described dimension; Described logical table is for describing the business datum of operation system;
(3), according to the physics table of operation system, set up the mapping relations between physics table and each logical table; Described physics table is for the business datum of storage service system;
(4) according to logical table and the logical data query grammar of pressing rule definition, write Boolean query statement LSQL;
(5) according to the mapping relations between physics table and logical table, Boolean query statement LSQL is converted into structured query sentence SQL, and by the inquiry of SQL statement complete business datum in database.
2. a kind of data enquire method as claimed in claim 1, is characterized in that, in step (1), during every dimension in extracting operation system, also comprises and extracts the level that every dimension comprises, and determine the calculated relationship between the level of every dimension; The level of described every dimension comprises basal layer and gathers layer; The described layer that gathers refers to that this level can be calculated by other one or more basic levels.
3. a kind of data enquire method as claimed in claim 1 or 2, is characterized in that, in step (2), described logical table comprises some logical fields, and the concrete mode of setting up the incidence relation between logical table and described dimension is:
The external key of logical table is set to point to the field of the level of certain dimension or certain dimension, and the major key of logical table is field or a unique field groups of a plurality of value that value is unique in logical table.
4. a kind of data enquire method as claimed in claim 3, is characterized in that, the concrete mode of setting up the mapping relations between physics table and logical table is:
A) in physics table, select the base table corresponding with each logical table, each logical field in logical table can both be calculated by described base table;
B) set up the major key of logical table and the mapping relations between base table major key;
C) set up the calculated relationship between non-major key logical field and base table field in logical table.
5. a kind of data enquire method as claimed in claim 4, is characterized in that, in step a), according to the data area of the described business datum of logical table, determines the base table corresponding with it.
6. a kind of data enquire method as claimed in claim 5, it is characterized in that, in step c), the calculated relationship in described logical table between non-major key logical field and base table field refers to that the expression formula that each logical field in logical table consists of base table field represents.
7. a kind of data enquire method as described in one of claim 1 to 6, is characterized in that, in step (5), the concrete mode that LSQL query statement is converted into SQL statement is:
According to described logical data query statement LSQL, obtain the business datum item in statement, the mapping relations according between described business datum item and logical table and physics table, change into the SQL query statement based on physics table by LSQL statement.
8. a data query system, comprising:
Dimension abstraction module, for extracting every dimension of operation system;
Logical table is set up module, sets up some logical tables of described operation system, and sets up the incidence relation between each logical table and described dimension; Described logical table is for describing the business datum of operation system;
Mapping relations are set up module, for according to the physics table of operation system, set up the mapping relations between physics table and each logical table;
Boolean query statement design module, for according to logical table and the logical data query grammar of pressing rule definition, writes Boolean query statement LSQL;
Data query module, is converted into structured query sentence SQL for the mapping relations according between physics table and logical table by Boolean query statement LSQL statement, and SQL statement is carried out to the inquiry with finishing service data in database.
9. a kind of data query system as claimed in claim 8, is characterized in that, the level that described dimension abstraction module also comprises for extracting every dimension, and the calculated relationship between the level of definite every dimension; The level of described every dimension comprises basal layer and gathers layer; The described layer that gathers refers to that this level can be calculated by other one or more basic levels.
10. a kind of data query system as claimed in claim 9, is characterized in that, described logical table is set up module and comprised:
External key setting unit, for the external key of logical table is set, the external key of logical table is set to point to the field of the level of certain dimension or certain dimension;
Major key setting unit, for the major key of logical table is set, the major key of logical table is field or a unique field groups of a plurality of value that value is unique in logical table.
11. a kind of data query systems as claimed in claim 10, is characterized in that, described mapping relations are set up module and comprised:
Base table selected cell, for selecting the base table corresponding with each logical table at physics table, each logical field in logical table can both be calculated by described base table;
Major key relation is set up unit, for setting up the major key of logical table and the mapping relations between base table major key;
Field relation is set up unit, for setting up the calculated relationship between the non-major key logical field of logical table and base table field.
12. a kind of data query systems as described in one of claim 8 to 11, is characterized in that, described data query module comprises:
Statement converting unit, is converted into structured query sentence SQL statement for the mapping relations according between physics table and logical table by Boolean query statement LSQL statement, and the concrete mode of conversion is:
According to described logical data query statement LSQL, obtain the business datum item in statement, the mapping relations according between described business datum item and logical table and physics table, change into the SQL query statement based on physics table by LSQL statement;
Query unit, for the inquiry in the complete business datum of database by SQL statement.
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