Example RABC is a relation TR 10000 T σ A10 R TR 1 3 333473 106 Estimate values

Example rabc is a relation tr 10000 t σ a10 r tr 1 3

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Example R(A,B,C) is a relation. T(R) = 10,000 T ( σ A<10 (R) ) = T(R) × 1 3 3334 73 / 106
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Estimate values in range Example R(A,B,C) is a relation. T(R) = 10,000 The DBMS statistics show that the values of the A attribute lie within the range [8,57] , uniformly distributed. Question: what would be a reasonable estimate of sel A<10 (R) ? Answer We see that 57-8+1 different values of A are possible however only records with values A=8 or A=9 satisfy the filter A<10 . Therefore, sel A<10 (R)= 2 (57 - 8+1) = 2 50 =0.04 And hence, T ( σ A<10 (R) ) = T(R) × sel A<10 (R) = 400 74 / 106
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Result size estimation: 3. Not-equal selection: σ A = c (R) Not-equal selection : σ A = c (R) , for attribute A and constant c : can usually use T( σ A = c (R)) = T(R) for simplicity more accurately, subtract a fraction 1 V(R,A) Fact: σ A = c (R) σ A=c (R) = R σ A = c (R) = R - σ A=c (R) Therefore, sel A = c (R)= V(R,A)-1 V(R,A) T ( σ A = c (R) ) = T(R) * V(R,A)-1 V(R,A) 75 / 106
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Result size estimation:4. Selection conditions with NOT Selection conditions with NOT : σ ¬ p (R) sel ¬ p (R)= 1 - sel p (R) T( σ ¬ p (R)) = T(R) - T( σ p (R)) 76 / 106
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Result size estimation: 5. Selection using several conditions with AND Selection using several conditions with AND : σ P 1 P 2 (R) treat selection as a cascade of several selections Treat σ P 1 P 2 (R) as σ P 1 ( σ P 2 (R) ) the order does not matter, treating this as σ P 2 ( σ P 1 (R) ) gives the same results. Estimated size is original size multiplied by the selectivity factor sel P 1 P 2 (R)= sel P 1 (R) * sel P 2 (R) T( σ P 1 P 2 (R)) = T(R) * sel P 1 (R) * sel P 2 (R) 77 / 106
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Result size estimation: 5. σ P 1 P 2 (R) Example R(A,B,C) is a relation. T(R) = 10,000. V(R,A) = 50 Estimate the size of the result set U = σ A=10 B<20 (R) Answer sel A=10 (R) = 1 50 sel B<20 (R) = 1 3 T(U) = sel A=10 * sel B<20 * T(R) = 1 50 * 1 3 * 10,000 = 66.67 78 / 106
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Result size estimation: 6. Selection using several conditions with OR Selection using several conditions with OR : σ P 1 P 2 (R) P 1 P 2 = ¬ ( ¬ P 1 ∧ ¬ P 2 ) Treat σ P 1 P 2 (R) as σ ¬ ( ¬ P 1 ∧¬ P 2 ) (R) sel P 1 P 2 (R)= 1- ( 1- sel p 1 (R) ) * ( 1- sel P 2 (R) ) T ( σ P 1 P 2 (R) ) = T(R) * sel P 1 P 2 (R) Example R(A,B,C) is a relation. T(R) = 10,000. V(R,A) = 50 Estimate the size of the result set U = σ A=10 B<20 (R) Answer sel A=10 (R) = 1 50 sel B<20 (R) = 1 3 T(U) = T(R) * ( 1 - (1 - 1 50 )(1 - 1 3 ) ) 79 / 106
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Result size estimation: R 1 S In our size estimations for join, we will look at natural join ( 1 ), but other joins is managed similarly equi-join as natural join theta-joins as a cartesian product followed by a selection Assume: R(X,Y) and S(Y,Z) , we join on Y : R(X,Y) 1 S(Y,Z) . Question: Estimate the size of ( R(X,Y) 1 S(Y,Z) ) The challenge is we do not know how the set of values of Y in R relate to the values of Y in S . There are some possibilities: If Y attribute values in R(X,Y) and S(Y,Z) are disjoint - empty join: T ( R(X,Y) 1 S(Y,Z) ) = 0 If Y attribute is a key in S and a foreign key of R , so each tuple in R joins with exactly one tuple in S : T ( R(X,Y) 1 S(Y,Z) ) = T(R) If almost every tuple in R and S has the same Y attribute value - combine all tuples of each relation: T ( R(X,Y) 1 S(Y,Z) ) = T(R) * T(S) Range of T(R 1 S): 0 T(R 1 S) T(R) * T(S) 80 / 106
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Result size estimation: R 1 S : Simplifying Assumptions For our calculations, we will make two assumptions: 1. containment of value sets assumption An attribute Y in a relation R( . . . ,Y) always takes on a prefix of a fixed list of values: y 1 y 2 y 3 y 4 . . .
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  • Fall '19
  • Joseph Rosen
  • Relational model, StarsIn, R 1c S

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