Background material for Chapter 3 taken from CS 245

Transcription

1 Background material for Chapter 3 taken from CS 245 contributed by Hector Garcia-Molina selected/cut by Stefan Böttcher Background CS 245 material taken from CS245 contributed Notes by Hector 4 Garcia-Molina (Stanford University, USA) 1 / 1 Query Processing Q Query Plan Focus: Relational System Others? Background CS 245 material taken from CS245 contributed Notes by Hector 6 Garcia-Molina (Stanford University, USA) 2 / 2 1

2 Example Select B,D From R,S Where R.A = c S.E = 2 R.C=S.C Background CS 245 material taken from CS245 contributed Notes by Hector 6 Garcia-Molina (Stanford University, USA) 3 / 3 R A B C S C D E a x 2 b y 2 c z 2 d x 1 e y 3 Answer B D 2 x Background CS 245 material taken from CS245 contributed Notes by Hector 6 Garcia-Molina (Stanford University, USA) 4 / 4 2

3 How do we execute query? One idea - Do Cartesian product - Select tuples - Do projection Background CS 245 material taken from CS245 contributed Notes by Hector 6 Garcia-Molina (Stanford University, USA) 5 / 5 RXS R.A R.B R.C S.C S.D S.E a x 2 Bingo! Got one... a y 2.. C x 2.. Background CS 245 material taken from CS245 contributed Notes by Hector 6 Garcia-Molina (Stanford University, USA) 6 / 6 3

4 Relational Algebra - can be used to describe plans... Ex: Plan I Π B,D σ R.A= c S.E=2 R.C=S.C R X S OR: Π B,D [ σ R.A= c S.E=2 R.C = S.C (RXS)] Background CS 245 material taken from CS245 contributed Notes by Hector 6 Garcia-Molina (Stanford University, USA) 7 / 7 Another idea: Plan II Π B,D natural join σ R.A = c σ S.E = 2 R S Background CS 245 material taken from CS245 contributed Notes by Hector 6 Garcia-Molina (Stanford University, USA) 8 / 8 4

5 R S A B C σ (R) σ(s) C D E a 1 10 A B C C D E 10 x 2 b 1 20 c x 2 20 y 2 c y 2 30 z 2 d z 2 40 x 1 e y 3 Background CS 245 material taken from CS245 contributed Notes by Hector 6 Garcia-Molina (Stanford University, USA) 9 / 9 Plan III Use R.A and S.C Indexes (1) Use R.A index to select R tuples with R.A = c (2) For each R.C value found, use S.C index to find matching tuples (3) Eliminate S tuples S.E 2 (4) Join matching R,S tuples, project B,D attributes and place in result Background CS 245material taken from CS245 contributed Notes by Hector 6 Garcia-Molina (Stanford University, USA) 10 / 10 5

6 R A B C I1 A= c S C D E a x 2 b 1 20 <c,2,10> <10,x,2> 20 y 2 c 2 10 check=2? 30 z 2 d 2 35 output: <2,x> 40 x 1 e y 3 next tuple: <c,7,15> C I2 Background CS 245material taken from CS245 contributed Notes by Hector 6 Garcia-Molina (Stanford University, USA) 11 / 11 parse convert SQL query parse tree logical query plan apply laws improved l.q.p estimate result sizes l.q.p. +sizes consider physical plans Overview of Query Optimization statistics execute pick best {(P1,C1),(P2,C2)...} answer Pi estimate costs {P1,P2,..} Background CS 245material taken from CS245 contributed Notes by Hector 6 Garcia-Molina (Stanford University, USA) 12 / 12 6

7 Example: SQL query SELECT title FROM StarsIn WHERE starname IN ( SELECT name FROM MovieStar WHERE birthdate LIKE %1960 ); (Find the movies with stars born in 1960) Background CS 245material taken from CS245 contributed Notes by Hector 6 Garcia-Molina (Stanford University, USA) 13 / 13 Example: Parse Tree <Query> <SFW> SELECT <SelList> FROM <FromList> WHERE <Condition> <Attribute> <RelName> <Tuple> IN <Query> title StarsIn <Attribute> ( <Query> ) starname <SFW> SELECT <SelList> FROM <FromList> WHERE <Condition> <Attribute> <RelName> <Attribute> LIKE <Pattern> name MovieStar birthdate %1960 Background CS 245material taken from CS245 contributed Notes by Hector 6 Garcia-Molina (Stanford University, USA) 14 / 14 7

8 Example: Generating Relational Algebra StarsIn Πtitle σ <tuple> <condition> IN Πname <attribute> σbirthdate LIKE %1960 starname MovieStar Fig. 7.15: An expression using a two-argument σ, midway between a parse tree and relational algebra Background CS 245material taken from CS245 contributed Notes by Hector 6 Garcia-Molina (Stanford University, USA) 15 / 15 Example: Logical Query Plan Πtitle σstarname=name StarsIn Πname σbirthdate LIKE %1960 MovieStar Fig. 7.18: Applying the rule for IN conditions Background CS 245material taken from CS245 contributed Notes by Hector 6 Garcia-Molina (Stanford University, USA) 16 / 16 8

9 Example: Improved Logical Query Plan (L.Q.P.) Πtitle starname=name Question: Push project to StarsIn? StarsIn Πname σbirthdate LIKE %1960 MovieStar Fig. 7.20: An improvement on fig Background CS 245material taken from CS245 contributed Notes by Hector 6 Garcia-Molina (Stanford University, USA) 17 / 17 Example: Estimate Result Sizes Need expected size StarsIn Π σ MovieStar Background CS 245material taken from CS245 contributed Notes by Hector 6 Garcia-Molina (Stanford University, USA) 18 / 18 9

10 Example: One Physical Plan (Pi) Hash join Parameters: join order, memory size, project attributes,... SEQ scan index scan Parameters: Select Condition,... StarsIn MovieStar Background CS 245material taken from CS245 contributed Notes by Hector 6 Garcia-Molina (Stanford University, USA) 19 / 19 Example: Estimate costs Ci of Pi L.Q.P P1 P2. Pn C1 C2. Cn depending on costs, pick best physical plan! Background CS 245material taken from CS245 contributed Notes by Hector 6 Garcia-Molina (Stanford University, USA) 20 / 20 10

11 Textbook: Chapteres 6 and 7 - outline 6.1 Algebra for queries 6.2 Physical operators (Scan,sort, ) Implementing operators +estimating their cost 7.1 Parsing 7.2 Algebraic laws 7.3 Parse tree -> logical query plan 7.4 Estimating result sizes Cost based optimization Background CS 245material taken from CS245 contributed Notes by Hector 6 Garcia-Molina (Stanford University, USA) 21 / 21 Relational algebra optimization Transformation rules (preserve equivalence) What are good transformations? Background CS 245material taken from CS245 contributed Notes by Hector 6 Garcia-Molina (Stanford University, USA) 22 / 22 11

12 Rules: Natural joins & cross products & union R S = S R (R S) T = R (S T) Background CS 245material taken from CS245 contributed Notes by Hector 6 Garcia-Molina (Stanford University, USA) 23 / 23 Note: Carry attribute names in results, so order is not important Can also write as trees, e.g.: T R R S S T Background CS 245material taken from CS245 contributed Notes by Hector 6 Garcia-Molina (Stanford University, USA) 24 / 24 12

13 Rules: Natural joins & cross products & union R S = S R (R S) T = R (S T) R x S = S x R (R x S) x T = R x (S x T) R U S = S U R R U (S U T) = (R U S) U T Background CS 245material taken from CS245 contributed Notes by Hector 6 Garcia-Molina (Stanford University, USA) 25 / 25 Rules: Selects σ p1 p2 (R) = σ p1vp2 (R) = σ p1 [ σ p2 (R)] [ σ p1 (R)] U [ σ p2 (R)] ( applies only to set-union, not to bag-union ) Background CS 245material taken from CS245 contributed Notes by Hector 6 Garcia-Molina (Stanford University, USA) 26 / 26 13

14 Rules: Project Let: X = set of attributes Y = set of attributes XY = X U Y πxy (R) = πx [πy (R)] Background CS 245material taken from CS245 contributed Notes by Hector 6 Garcia-Molina (Stanford University, USA) 27 / 27 Rules: σ + combined Let p = predicate with only R attribs q = predicate with only S attribs m = predicate with only R,S attribs σ p (R S) = σ q (R S) = [σ p (R)] S R [σ q (S)] Background CS 245material taken from CS245 contributed Notes by Hector 6 Garcia-Molina (Stanford University, USA) 28 / 28 14

15 Rules: σ + combined (continued) Some Rules can be Derived: σp q (R S) = σp q m (R S) = σpvq (R S) = Background CS 245material taken from CS245 contributed Notes by Hector 6 Garcia-Molina (Stanford University, USA) 29 / 29 Do one, others for homework: σp q (R S) = [σp (R)] [σq (S)] σp q m (R S) = σm [(σp R) (σq S)] σpvq (R S) = [(σp R) S] U [R (σq S)] Background CS 245material taken from CS245 contributed Notes by Hector 6 Garcia-Molina (Stanford University, USA) 30 / 30 15

16 --> Derivation for first one: σp q (R S) = σp [σq (R S) ] = σp [ R σq (S) ] = [σp (R)] [σq (S)] Background CS 245material taken from CS245 contributed Notes by Hector 6 Garcia-Molina (Stanford University, USA) 31 / 31 Rules: π,σ combined Let x = subset of R attributes z = attributes in predicate P (subset of R attributes) πxz πx[σp (R) ] = πx {σp [ πx (R) ]} Background CS 245material taken from CS245 contributed Notes by Hector 6 Garcia-Molina (Stanford University, USA) 32 / 32 16

17 Rules: π, combined Let x = subset of R attributes y = subset of S attributes z = intersection of R,S attributes πxy (R S) = πxy{[πxz (R) ] [πyz (S) ]} Background CS 245material taken from CS245 contributed Notes by Hector 6 Garcia-Molina (Stanford University, USA) 33 / 33 πxy {σp (R S)} = πxy {σp [πxz (R) πyz (S)]} z = z U {attributes used in P } Background CS 245material taken from CS245 contributed Notes by Hector 6 Garcia-Molina (Stanford University, USA) 34 / 34 17

18 Rules for σ, π combined with X similar... e.g., σp (R X S) =? Background CS 245material taken from CS245 contributed Notes by Hector 6 Garcia-Molina (Stanford University, USA) 35 / 35 Rules σ, U combined: σp(r U S) = σp(r) U σp(s) σp(r - S) = σp(r) - S = σp(r) - σp(s) Background CS 245material taken from CS245 contributed Notes by Hector 6 Garcia-Molina (Stanford University, USA) 36 / 36 18

19 Which are good transformations? σp1 p2 (R) σp1 [σp2 (R)] σp (R S) [σp (R)] S R S S R πx [σp (R)] πx {σp [πxz (R)]} Background CS 245material taken from CS245 contributed Notes by Hector 6 Garcia-Molina (Stanford University, USA) 37 / 37 Conventional wisdom: do projects early Example: R(A,B,C,D,E) x={e} P: (A=3) (B= cat ) πx {σp (R)} vs. πe {σp{πabe(r)}} Background CS 245material taken from CS245 contributed Notes by Hector 6 Garcia-Molina (Stanford University, USA) 38 / 38 19

20 But What if we have A, B indexes? B = cat A=3 Intersect pointers to get pointers to matching tuples Background CS 245material taken from CS245 contributed Notes by Hector 6 Garcia-Molina (Stanford University, USA) 39 / 39 Bottom line: No transformation is always good Usually good: early selections Background CS 245material taken from CS245 contributed Notes by Hector 6 Garcia-Molina (Stanford University, USA) 40 / 40 20

21 In textbook: more transformations Eliminate common sub-expressions Other operations: duplicate elimination Background CS 245material taken from CS245 contributed Notes by Hector 6 Garcia-Molina (Stanford University, USA) 41 / 41 21