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Relational Algebra 2

Relational Algebra 2. Relational Algebra. Formalism for creating new relations from existing ones Its place in the big picture:. Declartive query language. Algebra. Implementation. Relational algebra Relational bag algebra. SQL, relational calculus. Relational Algebra. Five operators:

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Relational Algebra 2

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  1. Relational Algebra 2

  2. Relational Algebra • Formalism for creating new relations from existing ones • Its place in the big picture: Declartivequerylanguage Algebra Implementation Relational algebraRelational bag algebra SQL,relational calculus

  3. Relational Algebra • Five operators: • Union:  • Difference: - • Selection: s • Projection: P • Cartesian Product:  • Derived or auxiliary operators: • Intersection, complement • Joins (natural,equi-join, theta join, semi-join) • Renaming: r

  4. 1. Union and 2. Difference • R1  R2 • Example: • ActiveEmployees  RetiredEmployees • R1 – R2 • Example: • AllEmployees -- RetiredEmployees

  5. What about Intersection ? • It is a derived operator • R1  R2 = R1 – (R1 – R2) • Also expressed as a join (will see later) • Example • UnionizedEmployees  RetiredEmployees

  6. 3. Selection • Returns all tuples which satisfy a condition • Notation: sc(R) • Examples • sSalary > 40000(Employee) • sname = “Smithh”(Employee) • The condition c can be =, <, , >,, <>

  7. Find all employees with salary more than $40,000. s Salary > 40000(Employee)

  8. 4. Projection • Eliminates columns, then removes duplicates • Notation: P A1,…,An(R) • Example: project social-security number and names: • PSSN, Name (Employee) • Output schema: Answer(SSN, Name)

  9. PSSN, Name (Employee)

  10. 5. Cartesian Product • Each tuple in R1 with each tuple in R2 • Notation: R1  R2 • Example: • Employee  Dependents • Very rare in practice; mainly used to express joins

  11. Relational Algebra • Five operators: • Union:  • Difference: - • Selection: s • Projection: P • Cartesian Product:  • Derived or auxiliary operators: • Intersection, complement • Joins (natural,equi-join, theta join, semi-join) • Renaming: r

  12. Renaming • Changes the schema, not the instance • Notation: rB1,…,Bn (R) • Example: • rLastName, SocSocNo (Employee) • Output schema: Answer(LastName, SocSocNo)

  13. Renaming Example Employee Name SSN John 999999999 Tony 777777777 • LastName, SocSocNo (Employee) LastName SocSocNo John 999999999 Tony 777777777

  14. Natural Join • Notation: R1 ⋈ R2 • Meaning: R1 ⋈ R2 = PA(sC(R1  R2)) • Where: • The selection sC checks equality of all common attributes • The projection eliminates the duplicate common attributes

  15. Employee Dependents = PName, SSN, Dname(sSSN=SSN2(Employee x rSSN2, Dname(Dependents)) Natural Join Example Employee Name SSN John 999999999 Tony 777777777 Dependents SSN Dname 999999999 Emily 777777777 Joe Name SSN Dname John 999999999 Emily Tony 777777777 Joe

  16. Natural Join • R= S= • R ⋈ S=

  17. Natural Join • Given the schemas R(A, B, C, D), S(A, C, E), what is the schema of R ⋈ S ? • Given R(A, B, C), S(D, E), what is R ⋈ S ? • Given R(A, B), S(A, B), what is R ⋈ S ?

  18. Theta Join • A join that involves a predicate • R1 ⋈q R2 = sq (R1  R2) • Here q can be any condition

  19. Eq-join • A theta join where q is an equality • R1 ⋈A=B R2 = s A=B (R1  R2) • Example: • Employee ⋈SSN=SSN Dependents • Most useful join in practice

  20. Semijoin • R ⋉ S = PA1,…,An (R ⋈ S) • Where A1, …, An are the attributes in R • Example: • Employee ⋉ Dependents

  21. Semijoins in Distributed Databases • Semijoins are used in distributed databases Dependents Employee network Employee ⋈ssn=ssn (s age>71 (Dependents)) T = PSSNs age>71 (Dependents) R = Employee ⋉ T Answer = R ⋈ Dependents

  22. seller-ssn=ssn pid=pid buyer-ssn=ssn Complex RA Expressions Pname Person Purchase Person Product Pssn Ppid sname=fred sname=gizmo

  23. Operations on Bags A bag = a set with repeated elements All operations need to be defined carefully on bags • {a,b,b,c}{a,b,b,b,e,f,f}={a,a,b,b,b,b,b,c,e,f,f} • {a,b,b,b,c,c} – {b,c,c,c,d} = {a,b,b,d} • sC(R): preserve the number of occurrences • PA(R): no duplicate elimination • Cartesian product, join: no duplicate elimination Important ! Relational Engines work on bags, not sets ! Reading assignment: 5.3 – 5.4

  24. Finally: RA has Limitations ! • Cannot compute “transitive closure” • Find all direct and indirect relatives of Fred • Cannot express in RA !!! Need to write C program

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