{[ promptMessage ]}

Bookmark it

{[ promptMessage ]}

8QP - QUERY PROCESSING(CHAPTER 13 Prof Ghandeharizadeh 1...

This preview shows pages 1–10. Sign up to view the full content.

09/27/09 Prof. Ghandeharizadeh 1 QUERY PROCESSING (CHAPTER 13)

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
09/27/09 Prof. Ghandeharizadeh 2 Software Architecture of a DBMS File System Buffer Pool Manager Abstraction of records Index structures Query Interpretor Query Optimizer Relational Algebra operators: , σ , ρ , δ , , , , ÷ , - Query Parser
09/27/09 Prof. Ghandeharizadeh 3 TERM DEFINITION P(R): Number of pages that constitute R t(R): Number of tuples that constitute R ν(A,R): the number of unique values for attribute A of R min(A,R): the minimum value for attribute A of R max(A,R): the maximum value for attribute A of R P(I R,A ): the number of pages that constitute the B + -tree index on attribute A of R d(I R,A ): the depth of a B + -tree index on attribute A of R lp(I R,A ): the number of leaf pages for a B + -tree index on attribute A of R B(I R,A ): the number of buckets for a hash index on attribute A of R

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
09/27/09 Prof. Ghandeharizadeh 4 HEAP FILE ORGANIZATION Assume a student table: Student(name, age, gpa, major) t(Student) = 16 P(Student) = 4 Bob, 21, 3.7, CS Mary, 24, 3, ECE Tom, 20, 3.2, EE Kathy, 18, 3.8, LS Kane, 19, 3.8, ME Lam, 22, 2.8, ME Chang, 18, 2.5, CS Vera, 17, 3.9, EE Louis, 32, 4, LS Martha, 29, 3.8, CS James, 24, 3.1, ME Pat, 19, 2.8, EE Chris, 22, 3.9, CS Chad, 28, 2.3, LS Leila, 20, 3.5, LS Shideh, 16, 4, CS
09/27/09 Prof. Ghandeharizadeh 5 Non-Clustered Hash Index A non-clustered hash index on the age attribute with 4 buckets, h(age) = age % B Bob, 21, 3.7, CS Mary, 24, 3, ECE Tom, 20, 3.2, EE Kathy, 18, 3.8, LS Kane, 19, 3.8, ME Lam, 22, 2.8, ME Chang, 18, 2.5, CS Vera, 17, 3.9, EE Louis, 32, 4, LS Martha, 29, 3.8, CS James, 24, 3.1, ME Pat, 19, 2.8, EE Chris, 22, 3.9, CS Chad, 28, 2.3, LS Leila, 20, 3.5, LS Shideh, 16, 4, CS (29, (3,2)) (24, (1, 2)) (32, (3,1)) (20, (1,3)) (18, (1, 4)) (22, (2,2)) (22, (4,1)) (19, (2, 1)) (28, (4,2)) (20, (4,3)) (16, (4,4)) 0 1 2 3 (19, (3, 4)) (18, (2,3)) (24, (3,3))

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
09/27/09 Prof. Ghandeharizadeh 6 Clustered Hash Index A clustered hash index on the age attribute with 4 buckets, h(age) = age % B Mary, 24, 3, ECE Tom, 20, 3.2, EE Kathy, 18, 3.8, LS Kane, 19, 3.8, ME Lam, 22, 2.8, ME Chang, 18, 2.5, CS Louis, 32, 4, LS Martha, 29, 3.8, CS James, 24, 3.1, ME Pat, 19, 2.8, EE Chris, 22, 3.9, CS Chad, 28, 2.3, LS Leila, 20, 3.5, LS Shideh, 16, 4, CS 0 1 2 3
09/27/09 Prof. Ghandeharizadeh 7 Non-Clustered Secondary B + -Tree A non-clustered secondary B+-tree on the gpa attribute Bob, 21, 3.7, CS Mary, 24, 3, ECE Tom, 20, 3.2, EE Kathy, 18, 3.8, LS Kane, 19, 3.8, ME Lam, 22, 2.8, ME Chang, 18, 2.5, CS Vera, 17, 3.9, EE Louis, 32, 4, LS Martha, 29, 3.8, CS James, 24, 3.1, ME Pat, 19, 2.8, EE Chris, 22, 3.9, CS Chad, 28, 2.3, LS Leila, 20, 3.5, LS Shideh, 16, 4, CS (3.7, (1, 1)) (3.8, (3,2)) (3.8, (2,1)) (3.9, (2,4)) (4, (3,1)) (3.8, (1,4)) (3.9, (4,1)) (4, (4,4)) (2.3, (4, 2)) (2.5, (2,3)) (2.8, (2,2)) (3.1, (3,3)) (3.2, (1,3) (2.8, (3,4)) (3, (1,2)) (3.5, (4,3)) 3.6

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
09/27/09 Prof. Ghandeharizadeh 8 Non-Clustered Primary B + -Tree A non-clustered primary B+-tree on the gpa attribute Bob, 21, 3.7, CS Mary, 24, 3, ECE Tom, 20, 3.2, EE Kathy, 18, 3.8, LS Kane, 19, 3.8, ME Lam, 22, 2.8, ME Chang, 18, 2.5, CS Vera, 17, 3.9, EE Louis, 32, 4, LS Martha, 29, 3.8, CS James, 24, 3.1, ME Pat, 19, 2.8, EE Chris, 22, 3.9, CS Chad, 28, 2.3, LS Leila, 20, 3.5, LS Shideh, 16, 4, CS (3.7, (3, 1)) (3.8, (3,2)) (3.8, (3,3)) (3.9, (4,2)) (4, (4,3)) (3.8, (3,4)) (3.9, (4,1)) (4, (4,4)) (2.3, (1, 1)) (2.5, (1,2)) (2.8, (1,3)) (3.1, (2,2)) (3.2, (2,3) (2.8, (1,4)) (3, (2,1)) (3.5, (2,4)) 3.6
09/27/09 Prof. Ghandeharizadeh 9 Clustered B + -Tree A clustered B+-tree on the gpa attribute It is impossible to have a clustered secondary B + -tree on an attribute.

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
This is the end of the preview. Sign up to access the rest of the document.

{[ snackBarMessage ]}

Page1 / 27

8QP - QUERY PROCESSING(CHAPTER 13 Prof Ghandeharizadeh 1...

This preview shows document pages 1 - 10. Sign up to view the full document.

View Full Document
Ask a homework question - tutors are online