A Visual Approach to Semantic Query Design Using a Web-Based Graphical Query Designer
Query Design
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Query Design Objectives of the Lecture : • To learn a strategy for designing queries. • To learn how to use relational algebra concepts to implement the strategy. • To learn how to translate the resulting query design into SQL.
description
Query Design. Objectives of the Lecture :. To learn a strategy for designing queries. To learn how to use relational algebra concepts to implement the strategy. To learn how to translate the resulting query design into SQL. Relational Queries. A query has two parts : - PowerPoint PPT Presentation
Transcript of Query Design
Query Design
Objectives of the Lecture :
• To learn a strategy for designing queries.
• To learn how to use relational algebra concepts to implement the strategy.
• To learn how to translate the resulting query design into SQL.
Relational QueriesA query has two parts : derive a relation whose contents are the answer
to your query; retrieve that derived relation.
In SQL :
SELECT ........................................................................................................................... ;
Retrieve
Derivation of relation
Trivial !
Queries so far have retrieved relations whose derivations were relatively simple. Extremely sophisticated derivations - i.e. complex queries - can be written for relational DBs.
Query Design Strategy
1. Determine which relations in the DB hold relevant data :Which relation holds the Determinant data ?Which relation holds the Dependent data ?
2. Use relational algebra concepts to conceptually derive one relation that holds just the determinant & the dependent.
This relation holds the answer to the query.Each algebra operator represents a conceptually natural manipulation of relations.Simpler to use than SQL clauses & phrases.
3. Translate design into SQL.Most (not all) relational DBMSs use SQL, so translate into SQL in order to execute query.
Example Database
It is not necessary to know the data values in any relation, or any integrity constraints except attribute data types.
EmpNo EName SalaryM-S DeptNo
Employee
DeptNo DName Budget MgrNo
Dept
ProjNo Start End
Project
ProjNo EmpNo
Alloc
Example 1 : Determinant & Dependent
Query : Get the names & salaries of all married & widowed employees.
Determinant – who/what is it we want to know about ?Married & widowed employees.
Dependent – what do we want to know about the ‘determinant’ ?
Names & salaries.
Q. In which relation(s) are the determinant & dependent ?A. Both in relation Employee.
Need to form one relation from Employee with just the determinant & dependent data in.
Do this by ‘reducing’ Employee to just the relevant attributes & tuples. Get rid of the rest.
Example 1 : Derive One Relation
Get rid of all tuples except those containing the determinant (& dependent).
Get rid of all attributes except those containing the determinant & dependent.
Employee
Restrict[ M-S = ‘M’ Or M-S = ‘W’ ]
Project[ M-S, EName, Salary ]
Answer !
Example 1 : Convert to SQL
SELECT M_S, EName, Salary
FROM Employee
WHERE M_S = ‘M’ OR M_S = ‘W’ ;
Employee
Restrict[ M-S = ‘M’ Or M-S = ‘W’ ]
Project[ M-S, EName, Salary ]
Example 1 : Result
EName SalaryM-SJane 3000M
Ali 3100M
....... ........
....... ........
....... ........
Sid 4400W
Relation contains only the determinant & dependent.
Determinant
Dependant
Example 2 : Determinant & Dependent Query : Get the names, salaries & project numbers of
employees who work on projects.
Determinant – who/what is it we want to know about ? Employees who work on projects.
Dependent – what do we want to know about the ‘determinant’ ?Names, salaries and project numbers.
Q. In which relation(s) are the determinant & dependent ?A. Determinant in relation Alloc.
Dependent in relations Employee and Alloc.
Need to form one relation from Employee and Alloc with just the determinant & dependent data in.
Do this by ‘merging’ Employee and Alloc together & ‘reducing’ the result to just the required attributes & tuples.
‘Merging’ Relations1. ‘Horizontally’
A B C D
.... ..... .. .....
.... .... .. .....
.... .... .. .....
A B C D E
.... ..... .. ...... .....
.... .... .. ...... .....
.... .... .. ...... .....
D E
...... .....
...... ....
...... ....
2. ‘Vertically’
Join ==>
==>
A B C
.... ..... ..
.... .... ..
Union
A B C
.... ..... ..
.... .... ..
A B C
.... ..... ..
.... ..... ..
.... ..... ..
.... .... ..
Example needs a horizontal merge.
Example 2 : Derive One Relation
Merge relations ‘horizontally’.
Get rid of all attributes except those containing the determinant & dependent.
Answer !
Employee
Join[ EmpNo ]
Project[ ProjNo, EName, Salary ]
Alloc
Example 2 : Convert to SQL
SELECT ProjNo, EName, Salary
FROM Employee NATURAL JOIN Alloc ;
Employee
Project[ ProjNo, EName, Salary ]
Alloc
Join[ EmpNo ]
Example 2 : Result
Relation contains only the determinant & dependent.
Determinant
Dependant
EName SalaryProjNoJoan 2900P2
Uli 3200P2
....... ........
Ryan 4400P4
....... ........
....... ........
Example 3 : Determinant & Dependent
Query : Get the total salary of all married employees.
Determinant – who/what is it we want to know about ?Married employees.
Dependent – what do we want to know about the ‘determinant’ ? Salaries : but a calculation is needed to get the total !
Q. In which relation(s) are the determinant & dependent ?A. Both in relation Employee.
Need to form one relation from Employee with just the determinant & calculated dependent data in.
Do this by ‘reducing’ Employee to just the required tuples, and calculating what is required.
Calculating Data1. ‘Horizontally’
A B C D
.... ..... .. .....
.... .... .. .....
.... .... .. .....
A B C D E
.... ..... .. ...... .....
.... .... .. ...... .....
.... .... .. ...... .....
2. ‘Vertically’
Extend ==>
==>A C
.... ..
.... ..
A B C
.... ..... ..
.... ..... ..
.... ..... ..
.... .... ..
GroupBy
Example needs a vertical calculation.
Example 3 : Derive One Relation
Get rid of all tuples except those containing the determinant (& dependent).
Calculate the dependent, & get rid of all other attributes except the determinant.
Employee
Restrict[ M-S = ‘M’ ]
GroupBy[ M-S ] With[ Total <-- Bag[Salary] Sum ]
Answer !
Example 3 : Convert to SQL
SELECT M_S, SUM(ALL Salary) AS TotalFROM EmployeeWHERE M_S = ‘M’GROUP BY M_S ;
Employee
Restrict[ M-S = ‘M’ ]
GroupBy[ M-S ] With[ Total <-- Bag[Salary] Sum ]
Example 3 : Result
TotalM-S120,000M
Relation contains only the determinant & dependent.
Determinant
Dependant
Determinants
Always need a determinant and a dependent to design a query.
However determinant does not always need to be in the answer. Typically there are 2 cases where this arises :
1. If the determinant is a single value,then it can be left out of the answer,
because the query designer knows the determinant to which the dependent data refers, and so doesn’t need it in the answer.
2. If the query designer is not interested in distinguishing between different determining values,
then they can be left out,because they don’t matter.
Revised E.G. 1 : Determinant/DependentQuery : Get the names & salaries of all married
& widowed& widowed employees.
Determinant – who/what is it we want to know about ?Married & widowed& widowed employees.
Dependent – what do we want to know about the ‘determinant’ ?
Names & salaries.
Q. In which relation(s) are the determinant & dependent ?A. Both in relation Employee.
Need to form one relation from Employee with just the determinant & dependent data in.
Then remove the determinant data as well - it will have just one value, the ‘married’ value.
Revised E.G. 1 : Required Result
EName SalaryJane 3000
Ali 3100
....... .....
....... .....
Relation contains only dependent data.
No determinant because the query designer knows that all the dependent values now refer to ‘married’ people. Before some were married and some were widowed. Therefore they had to be distinguished.
Revised E.G. 1 : Derive One Relation
Get rid of all tuples not containing the single ‘married’ determinant value.
Get rid of all attributes except the dependent ones.
Employee
Restrict[ M-S = ‘M’ ]
Project[ EName, Salary ]
Revised E.G. 1 : Convert to SQL
SELECT EName, Salary
FROM Employee
WHERE M_S = ‘M’;
Employee
Restrict[ M-S = ‘M’ ]
Project[ EName, Salary ]
Revised E.G. 2 : Determinant/Dependent Query : Get the names, salaries & project numbers& project numbers of
employees who work on projects.
Determinant – who/what is it we want to know about ? Employees who work on projects.
Dependent – what do we want to know about the ‘determinant’ ?Names & salaries.
Q. In which relation(s) are the determinant & dependent ?A. Determinant in relation Alloc.
Dependent in relation Employee.
Form one relation from Employee and Alloc, by joining them. The result will contain all data about employees and their projects.
Then ‘reduce’ the result to just the dependent attributes.
Revised E.G. 2 : Required Result
Relation contains only dependent data. EName Salary
Joan 2900
Uli 3200
....... .....
Ryan 4400
....... .....
....... .....
No determinant because the query designer is not interested in the particular projects that employees work on. Before the individual projects were relevant. Therefore they had to be distinguished.
Revised E.G. 2 : Derive One Relation
Merge relations ‘horizontally’.
Get rid of all attributes except the dependents.
Employee
Join[ EmpNo ]
Project[ EName, Salary ]
Alloc
Revised E.G. 2 : Convert to SQL
SELECT EName, Salary
FROM Employee NATURAL JOIN Alloc ;
Employee
Project[ EName, Salary ]
Alloc
Join[ EmpNo ]
Revised E.G. 3 : Determinant/DependentQuery : Get the total salary of all married employees.
DeterminantMarried employees
DependentSalaries , but totalled.
Q. In which relation(s) are the determinant & dependent ?A. Both in relation Employee.
Need to form one relation from Employee with just the calculated dependent data in.
Do this by ‘reducing’ Employee to just the required tuples, and calculating what is required.
Don’t actually need to include ‘married’ in the result, since we know the employees referred to.
Revised E.G. 3 : Required Result
Total120,000
Relation contains only the calculated dependent.
No determinant because the query designer knows that the dependent result refers to ‘married’ people. Didn’t really need to include the ‘married’ marital-status value before.
Revised E.G. 3 : Derive One Relation
Get rid of all tuples except those referring to the ‘married’ determinant.
Calculate the total from the whole result of the restriction, because it only holds data about ‘married’ employees.
GroupBy[ ] With[ Total <-- Bag[Salary] Sum ]
Employee
Restrict[ M-S = ‘M’ ]
Revised E.G. 3 : Convert to SQL
SELECT SUM(ALL Salary) AS TotalFROM EmployeeWHERE M_S = ‘M’ ;
Employee
Restrict[ M-S = ‘M’ ]
GroupBy[ ] With[ Total <-- Bag[Salary] Sum ]
Nothing !
Dependants
Always need a determinant and a dependent to design a query.
If there are queries where only the dependant needs to be in the result,
are there queries where only the determinant needs to be in the result ?
The answer is, not very often.
The typical case is a query to discover if a determinant exists.Such a query typically requires an answer of yes/no or true/false.
Example with No Dependant in AnswerQuery : Are there any married employees ?
Determinant – who/what is it we want to know about ?Married employees.
Dependent – what do we want to know about the ‘determinant’ ?
Nothing ! Only whether they exist.
Q. In which relation(s) is the determinant?A. Relation Employee : contains data for all employees,
including their marital-status.
Need to form one relation from Employee with just the determinant data in.
Do this by ‘reducing’ Employee to just the marital-status attribute with tuples whose marital-status = ‘married’.
Required Result : First Attempt
Relation(s) contain only the determinant. Dependant is of no interest.
M-SM
M
M
M
M
M-S
Answer if there are ‘married’ employees.
Answer if there are no ‘married’ employees.
OR
Result Really Required
because the previous Yes answer could be very large (!)and the previous No answer could be misleading.
OR
Yes No
Unfortunately, SQL has no easy way to derive Yes/No answers.
design the query to deliver the previous answer(s).
Derive One Relation
Employee
Restrict[ M-S = ‘M’ ]
Project[ M-S ]
Get rid of all tuples except those containing the determinant value ‘married’.
Get rid of all attributes except the determinant value ‘married’.
Answer !
Do we need this step ? Only to prevent a Yes answer from being too big.
Convert to SQL
Employee
Restrict[ M-S = ‘M’ ]
Project[ M-S ]
SELECT M_SFROM EmployeeWHERE M_S = ‘M’ ;
ConclusionStrategy : Determine which relations hold the determinant & dependent data. Use relational algebra to derive one relation that holds both. Decide whether determinant or dependant data can be pruned out. Convert to SQL.
Further Developments Suppose determinant and/or dependent data is itself split over 2 or
more relations ? Combine them into one relation using the above approach. Then continue as before.
May need both horizontal and vertical calculations in one query. Even more advanced queries can be built on these foundations.
Design them with the same approach, applied recursively.
