63 lines
1.9 KiB
Plaintext
63 lines
1.9 KiB
Plaintext
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# 2007, M. Spiekermann
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#
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# A SECONDO-Script which creates synthesized data used for
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# experiments with correlated predicates
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let ten = [const rel(tuple([A: int, B: int, C: int, D: int]))
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value ( (0 1 2 3)
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(1 2 3 4)
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(2 3 4 5)
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(3 4 5 6)
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(4 5 6 7)
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(5 6 7 8)
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(6 7 8 9)
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(7 8 9 0)
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(8 9 0 1)
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(9 0 1 2) )];
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#create table thousand
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# as select (A.a) * 100 + (B.a) * 10 + C.a as a
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# from ten as A, ten as B, ten as C order by a asc;
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#
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let thousand = ten feed {A} ten feed {B} ten feed {C} product product extend[No: (.A_A * 100) + (.A_B * 10) + .A_C] project[No] sortby[No asc] consume;
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#
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#-- Create two objects with one million tuples
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#create table m1
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# as select (T.a % 1000) as a, ((T.a + 1) % 1000) as b,
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# ((T.a + 2) % 1000) as c, ((T.a + 3) % 1000) as d
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# from thousand, thousand as T;
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let m1 = thousand feed {R} thousand feed {T} product
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extend[A: .No_T mod 1000]
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extend[B: (.No_T + 1) mod 1000]
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extend[C: (.No_T + 2) mod 1000]
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extend[D: (.No_T + 3) mod 1000]
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project[A, B, C, D]
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consume;
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let m2 = m1;
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let m1_A = m1 createbtree[A];
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# Queries:
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# sql select count(*) from [m1 as r, m2 as s] where [r:a = s:a, s:a=0, s:b=1]
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#
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# Nested Loop (9.43 s)
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# query m1_A m1 exactmatch[0] consume
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# within[fun( x: ANY ) m2 feed filter[.A = 0] {s} loopjoin[x feed] count]
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#
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# Index Nested Loop (47.66 s)
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# m2 feed {s} filter[(.B_s = 1)] filter[(.A_s = 0)] loopjoin[m1_A m1 exactmatch[.A_s] {r} ] count
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#
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# Adaptive (hj = 20.09 s) => Selectivity estimation error 100% !!!
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#
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#
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#secondo('query m2 pfeed[100] puse[. {s} filter[(.B_s = 1)] filter[(.A_s = 0)] ] m1 pjoin1[1; symj: . .. feed head[1000] {1} {r} head[500] {2} symmjoin[(.A_s = ..A_r)] {4}, hj: . .. feed {r} {3} hashjoin[A_s, A_r, 9997] , smj: . .. feed {r} {3} sortmergejoin[A_s, A_r] , ilj: . loopjoin[m1_A .. exactmatch[.A_s] {r} {3} ] ] pdelete count')
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