1227 lines
39 KiB
PL/PgSQL
1227 lines
39 KiB
PL/PgSQL
--
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-- AGGREGATES
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--
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-- avoid bit-exact output here because operations may not be bit-exact.
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SET extra_float_digits = 0;
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SELECT avg(four) AS avg_1 FROM onek;
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SELECT avg(a) AS avg_32 FROM aggtest WHERE a < 100;
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-- In 7.1, avg(float4) is computed using float8 arithmetic.
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-- Round the result to 3 digits to avoid platform-specific results.
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SELECT avg(b)::numeric(10,3) AS avg_107_943 FROM aggtest;
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SELECT avg(gpa) AS avg_3_4 FROM ONLY student;
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SELECT sum(four) AS sum_1500 FROM onek;
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SELECT sum(a) AS sum_198 FROM aggtest;
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SELECT sum(b) AS avg_431_773 FROM aggtest;
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SELECT sum(gpa) AS avg_6_8 FROM ONLY student;
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SELECT max(four) AS max_3 FROM onek;
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SELECT max(a) AS max_100 FROM aggtest;
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SELECT max(aggtest.b) AS max_324_78 FROM aggtest;
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SELECT max(student.gpa) AS max_3_7 FROM student;
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SELECT stddev_pop(b) FROM aggtest;
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SELECT stddev_samp(b) FROM aggtest;
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SELECT var_pop(b) FROM aggtest;
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SELECT var_samp(b) FROM aggtest;
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SELECT stddev_pop(b::numeric) FROM aggtest;
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SELECT stddev_samp(b::numeric) FROM aggtest;
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SELECT var_pop(b::numeric) FROM aggtest;
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SELECT var_samp(b::numeric) FROM aggtest;
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-- population variance is defined for a single tuple, sample variance
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-- is not
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SELECT var_pop(1.0::float8), var_samp(2.0::float8);
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SELECT stddev_pop(3.0::float8), stddev_samp(4.0::float8);
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SELECT var_pop('inf'::float8), var_samp('inf'::float8);
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SELECT stddev_pop('inf'::float8), stddev_samp('inf'::float8);
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SELECT var_pop('nan'::float8), var_samp('nan'::float8);
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SELECT stddev_pop('nan'::float8), stddev_samp('nan'::float8);
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SELECT var_pop(1.0::float4), var_samp(2.0::float4);
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SELECT stddev_pop(3.0::float4), stddev_samp(4.0::float4);
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SELECT var_pop('inf'::float4), var_samp('inf'::float4);
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SELECT stddev_pop('inf'::float4), stddev_samp('inf'::float4);
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SELECT var_pop('nan'::float4), var_samp('nan'::float4);
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SELECT stddev_pop('nan'::float4), stddev_samp('nan'::float4);
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SELECT var_pop(1.0::numeric), var_samp(2.0::numeric);
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SELECT stddev_pop(3.0::numeric), stddev_samp(4.0::numeric);
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SELECT var_pop('inf'::numeric), var_samp('inf'::numeric);
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SELECT stddev_pop('inf'::numeric), stddev_samp('inf'::numeric);
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SELECT var_pop('nan'::numeric), var_samp('nan'::numeric);
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SELECT stddev_pop('nan'::numeric), stddev_samp('nan'::numeric);
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-- verify correct results for null and NaN inputs
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select sum(null::int4) from generate_series(1,3);
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select sum(null::int8) from generate_series(1,3);
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select sum(null::numeric) from generate_series(1,3);
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select sum(null::float8) from generate_series(1,3);
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select avg(null::int4) from generate_series(1,3);
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select avg(null::int8) from generate_series(1,3);
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select avg(null::numeric) from generate_series(1,3);
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select avg(null::float8) from generate_series(1,3);
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select sum('NaN'::numeric) from generate_series(1,3);
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select avg('NaN'::numeric) from generate_series(1,3);
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-- verify correct results for infinite inputs
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SELECT sum(x::float8), avg(x::float8), var_pop(x::float8)
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FROM (VALUES ('1'), ('infinity')) v(x);
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SELECT sum(x::float8), avg(x::float8), var_pop(x::float8)
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FROM (VALUES ('infinity'), ('1')) v(x);
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SELECT sum(x::float8), avg(x::float8), var_pop(x::float8)
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FROM (VALUES ('infinity'), ('infinity')) v(x);
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SELECT sum(x::float8), avg(x::float8), var_pop(x::float8)
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FROM (VALUES ('-infinity'), ('infinity')) v(x);
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SELECT sum(x::float8), avg(x::float8), var_pop(x::float8)
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FROM (VALUES ('-infinity'), ('-infinity')) v(x);
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SELECT sum(x::numeric), avg(x::numeric), var_pop(x::numeric)
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FROM (VALUES ('1'), ('infinity')) v(x);
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SELECT sum(x::numeric), avg(x::numeric), var_pop(x::numeric)
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FROM (VALUES ('infinity'), ('1')) v(x);
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SELECT sum(x::numeric), avg(x::numeric), var_pop(x::numeric)
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FROM (VALUES ('infinity'), ('infinity')) v(x);
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SELECT sum(x::numeric), avg(x::numeric), var_pop(x::numeric)
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FROM (VALUES ('-infinity'), ('infinity')) v(x);
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SELECT sum(x::numeric), avg(x::numeric), var_pop(x::numeric)
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FROM (VALUES ('-infinity'), ('-infinity')) v(x);
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-- test accuracy with a large input offset
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SELECT avg(x::float8), var_pop(x::float8)
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FROM (VALUES (100000003), (100000004), (100000006), (100000007)) v(x);
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SELECT avg(x::float8), var_pop(x::float8)
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FROM (VALUES (7000000000005), (7000000000007)) v(x);
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-- SQL2003 binary aggregates
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SELECT regr_count(b, a) FROM aggtest;
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SELECT regr_sxx(b, a) FROM aggtest;
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SELECT regr_syy(b, a) FROM aggtest;
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SELECT regr_sxy(b, a) FROM aggtest;
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SELECT regr_avgx(b, a), regr_avgy(b, a) FROM aggtest;
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SELECT regr_r2(b, a) FROM aggtest;
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SELECT regr_slope(b, a), regr_intercept(b, a) FROM aggtest;
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SELECT covar_pop(b, a), covar_samp(b, a) FROM aggtest;
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SELECT corr(b, a) FROM aggtest;
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-- check single-tuple behavior
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SELECT covar_pop(1::float8,2::float8), covar_samp(3::float8,4::float8);
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SELECT covar_pop(1::float8,'inf'::float8), covar_samp(3::float8,'inf'::float8);
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SELECT covar_pop(1::float8,'nan'::float8), covar_samp(3::float8,'nan'::float8);
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-- test accum and combine functions directly
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CREATE TABLE regr_test (x float8, y float8);
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INSERT INTO regr_test VALUES (10,150),(20,250),(30,350),(80,540),(100,200);
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SELECT count(*), sum(x), regr_sxx(y,x), sum(y),regr_syy(y,x), regr_sxy(y,x)
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FROM regr_test WHERE x IN (10,20,30,80);
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SELECT count(*), sum(x), regr_sxx(y,x), sum(y),regr_syy(y,x), regr_sxy(y,x)
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FROM regr_test;
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SELECT float8_accum('{4,140,2900}'::float8[], 100);
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SELECT float8_regr_accum('{4,140,2900,1290,83075,15050}'::float8[], 200, 100);
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SELECT count(*), sum(x), regr_sxx(y,x), sum(y),regr_syy(y,x), regr_sxy(y,x)
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FROM regr_test WHERE x IN (10,20,30);
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SELECT count(*), sum(x), regr_sxx(y,x), sum(y),regr_syy(y,x), regr_sxy(y,x)
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FROM regr_test WHERE x IN (80,100);
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SELECT float8_combine('{3,60,200}'::float8[], '{0,0,0}'::float8[]);
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SELECT float8_combine('{0,0,0}'::float8[], '{2,180,200}'::float8[]);
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SELECT float8_combine('{3,60,200}'::float8[], '{2,180,200}'::float8[]);
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SELECT float8_regr_combine('{3,60,200,750,20000,2000}'::float8[],
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'{0,0,0,0,0,0}'::float8[]);
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SELECT float8_regr_combine('{0,0,0,0,0,0}'::float8[],
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'{2,180,200,740,57800,-3400}'::float8[]);
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SELECT float8_regr_combine('{3,60,200,750,20000,2000}'::float8[],
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'{2,180,200,740,57800,-3400}'::float8[]);
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DROP TABLE regr_test;
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-- test count, distinct
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SELECT count(four) AS cnt_1000 FROM onek;
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SELECT count(DISTINCT four) AS cnt_4 FROM onek;
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select ten, count(*), sum(four) from onek
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group by ten order by ten;
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select ten, count(four), sum(DISTINCT four) from onek
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group by ten order by ten;
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-- user-defined aggregates
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SELECT newavg(four) AS avg_1 FROM onek;
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SELECT newsum(four) AS sum_1500 FROM onek;
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SELECT newcnt(four) AS cnt_1000 FROM onek;
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SELECT newcnt(*) AS cnt_1000 FROM onek;
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SELECT oldcnt(*) AS cnt_1000 FROM onek;
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SELECT sum2(q1,q2) FROM int8_tbl;
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-- test for outer-level aggregates
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-- this should work
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select ten, sum(distinct four) from onek a
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group by ten
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having exists (select 1 from onek b where sum(distinct a.four) = b.four);
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-- this should fail because subquery has an agg of its own in WHERE
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select ten, sum(distinct four) from onek a
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group by ten
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having exists (select 1 from onek b
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where sum(distinct a.four + b.four) = b.four);
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-- Test handling of sublinks within outer-level aggregates.
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-- Per bug report from Daniel Grace.
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select
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(select max((select i.unique2 from tenk1 i where i.unique1 = o.unique1)))
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from tenk1 o;
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-- Test handling of Params within aggregate arguments in hashed aggregation.
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-- Per bug report from Jeevan Chalke.
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explain (verbose, costs off)
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select s1, s2, sm
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from generate_series(1, 3) s1,
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lateral (select s2, sum(s1 + s2) sm
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from generate_series(1, 3) s2 group by s2) ss
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order by 1, 2;
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select s1, s2, sm
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from generate_series(1, 3) s1,
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lateral (select s2, sum(s1 + s2) sm
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from generate_series(1, 3) s2 group by s2) ss
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order by 1, 2;
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explain (verbose, costs off)
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select array(select sum(x+y) s
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from generate_series(1,3) y group by y order by s)
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from generate_series(1,3) x;
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select array(select sum(x+y) s
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from generate_series(1,3) y group by y order by s)
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from generate_series(1,3) x;
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--
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-- test for bitwise integer aggregates
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--
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CREATE TEMPORARY TABLE bitwise_test(
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i2 INT2,
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i4 INT4,
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i8 INT8,
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i INTEGER,
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x INT2,
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y BIT(4)
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);
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-- empty case
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SELECT
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BIT_AND(i2) AS "?",
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BIT_OR(i4) AS "?"
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FROM bitwise_test;
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COPY bitwise_test FROM STDIN NULL 'null';
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1 1 1 1 1 B0101
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3 3 3 null 2 B0100
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7 7 7 3 4 B1100
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\.
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SELECT
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BIT_AND(i2) AS "1",
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BIT_AND(i4) AS "1",
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BIT_AND(i8) AS "1",
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BIT_AND(i) AS "?",
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BIT_AND(x) AS "0",
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BIT_AND(y) AS "0100",
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BIT_OR(i2) AS "7",
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BIT_OR(i4) AS "7",
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BIT_OR(i8) AS "7",
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BIT_OR(i) AS "?",
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BIT_OR(x) AS "7",
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BIT_OR(y) AS "1101"
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FROM bitwise_test;
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--
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-- test boolean aggregates
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--
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-- first test all possible transition and final states
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SELECT
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-- boolean and transitions
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-- null because strict
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booland_statefunc(NULL, NULL) IS NULL AS "t",
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booland_statefunc(TRUE, NULL) IS NULL AS "t",
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booland_statefunc(FALSE, NULL) IS NULL AS "t",
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booland_statefunc(NULL, TRUE) IS NULL AS "t",
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booland_statefunc(NULL, FALSE) IS NULL AS "t",
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-- and actual computations
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booland_statefunc(TRUE, TRUE) AS "t",
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NOT booland_statefunc(TRUE, FALSE) AS "t",
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NOT booland_statefunc(FALSE, TRUE) AS "t",
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NOT booland_statefunc(FALSE, FALSE) AS "t";
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SELECT
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-- boolean or transitions
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-- null because strict
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boolor_statefunc(NULL, NULL) IS NULL AS "t",
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boolor_statefunc(TRUE, NULL) IS NULL AS "t",
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boolor_statefunc(FALSE, NULL) IS NULL AS "t",
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boolor_statefunc(NULL, TRUE) IS NULL AS "t",
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boolor_statefunc(NULL, FALSE) IS NULL AS "t",
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-- actual computations
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boolor_statefunc(TRUE, TRUE) AS "t",
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boolor_statefunc(TRUE, FALSE) AS "t",
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boolor_statefunc(FALSE, TRUE) AS "t",
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NOT boolor_statefunc(FALSE, FALSE) AS "t";
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CREATE TEMPORARY TABLE bool_test(
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b1 BOOL,
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b2 BOOL,
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b3 BOOL,
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b4 BOOL);
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-- empty case
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SELECT
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BOOL_AND(b1) AS "n",
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BOOL_OR(b3) AS "n"
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FROM bool_test;
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COPY bool_test FROM STDIN NULL 'null';
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TRUE null FALSE null
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FALSE TRUE null null
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null TRUE FALSE null
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\.
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SELECT
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BOOL_AND(b1) AS "f",
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BOOL_AND(b2) AS "t",
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BOOL_AND(b3) AS "f",
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BOOL_AND(b4) AS "n",
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BOOL_AND(NOT b2) AS "f",
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BOOL_AND(NOT b3) AS "t"
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FROM bool_test;
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SELECT
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EVERY(b1) AS "f",
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EVERY(b2) AS "t",
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EVERY(b3) AS "f",
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EVERY(b4) AS "n",
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EVERY(NOT b2) AS "f",
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EVERY(NOT b3) AS "t"
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FROM bool_test;
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SELECT
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BOOL_OR(b1) AS "t",
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BOOL_OR(b2) AS "t",
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BOOL_OR(b3) AS "f",
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BOOL_OR(b4) AS "n",
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BOOL_OR(NOT b2) AS "f",
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BOOL_OR(NOT b3) AS "t"
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FROM bool_test;
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--
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-- Test cases that should be optimized into indexscans instead of
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-- the generic aggregate implementation.
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--
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-- Basic cases
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explain (costs off)
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select min(unique1) from tenk1;
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select min(unique1) from tenk1;
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explain (costs off)
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select max(unique1) from tenk1;
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select max(unique1) from tenk1;
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explain (costs off)
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select max(unique1) from tenk1 where unique1 < 42;
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select max(unique1) from tenk1 where unique1 < 42;
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explain (costs off)
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select max(unique1) from tenk1 where unique1 > 42;
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select max(unique1) from tenk1 where unique1 > 42;
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-- the planner may choose a generic aggregate here if parallel query is
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-- enabled, since that plan will be parallel safe and the "optimized"
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-- plan, which has almost identical cost, will not be. we want to test
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-- the optimized plan, so temporarily disable parallel query.
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begin;
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set local max_parallel_workers_per_gather = 0;
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explain (costs off)
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select max(unique1) from tenk1 where unique1 > 42000;
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select max(unique1) from tenk1 where unique1 > 42000;
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rollback;
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-- multi-column index (uses tenk1_thous_tenthous)
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explain (costs off)
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select max(tenthous) from tenk1 where thousand = 33;
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select max(tenthous) from tenk1 where thousand = 33;
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explain (costs off)
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select min(tenthous) from tenk1 where thousand = 33;
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select min(tenthous) from tenk1 where thousand = 33;
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-- check parameter propagation into an indexscan subquery
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explain (costs off)
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select f1, (select min(unique1) from tenk1 where unique1 > f1) AS gt
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from int4_tbl;
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select f1, (select min(unique1) from tenk1 where unique1 > f1) AS gt
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from int4_tbl;
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-- check some cases that were handled incorrectly in 8.3.0
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explain (costs off)
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select distinct max(unique2) from tenk1;
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select distinct max(unique2) from tenk1;
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explain (costs off)
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select max(unique2) from tenk1 order by 1;
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select max(unique2) from tenk1 order by 1;
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explain (costs off)
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select max(unique2) from tenk1 order by max(unique2);
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select max(unique2) from tenk1 order by max(unique2);
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explain (costs off)
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select max(unique2) from tenk1 order by max(unique2)+1;
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select max(unique2) from tenk1 order by max(unique2)+1;
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explain (costs off)
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select max(unique2), generate_series(1,3) as g from tenk1 order by g desc;
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select max(unique2), generate_series(1,3) as g from tenk1 order by g desc;
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-- interesting corner case: constant gets optimized into a seqscan
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explain (costs off)
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select max(100) from tenk1;
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select max(100) from tenk1;
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-- try it on an inheritance tree
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create table minmaxtest(f1 int);
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create table minmaxtest1() inherits (minmaxtest);
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create table minmaxtest2() inherits (minmaxtest);
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create table minmaxtest3() inherits (minmaxtest);
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create index minmaxtesti on minmaxtest(f1);
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create index minmaxtest1i on minmaxtest1(f1);
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create index minmaxtest2i on minmaxtest2(f1 desc);
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create index minmaxtest3i on minmaxtest3(f1) where f1 is not null;
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insert into minmaxtest values(11), (12);
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insert into minmaxtest1 values(13), (14);
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insert into minmaxtest2 values(15), (16);
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insert into minmaxtest3 values(17), (18);
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explain (costs off)
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select min(f1), max(f1) from minmaxtest;
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select min(f1), max(f1) from minmaxtest;
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-- DISTINCT doesn't do anything useful here, but it shouldn't fail
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explain (costs off)
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select distinct min(f1), max(f1) from minmaxtest;
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select distinct min(f1), max(f1) from minmaxtest;
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drop table minmaxtest cascade;
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-- check for correct detection of nested-aggregate errors
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select max(min(unique1)) from tenk1;
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select (select max(min(unique1)) from int8_tbl) from tenk1;
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--
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-- Test removal of redundant GROUP BY columns
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--
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create temp table t1 (a int, b int, c int, d int, primary key (a, b));
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create temp table t2 (x int, y int, z int, primary key (x, y));
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create temp table t3 (a int, b int, c int, primary key(a, b) deferrable);
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-- Non-primary-key columns can be removed from GROUP BY
|
|
explain (costs off) select * from t1 group by a,b,c,d;
|
|
|
|
-- No removal can happen if the complete PK is not present in GROUP BY
|
|
explain (costs off) select a,c from t1 group by a,c,d;
|
|
|
|
-- Test removal across multiple relations
|
|
explain (costs off) select *
|
|
from t1 inner join t2 on t1.a = t2.x and t1.b = t2.y
|
|
group by t1.a,t1.b,t1.c,t1.d,t2.x,t2.y,t2.z;
|
|
|
|
-- Test case where t1 can be optimized but not t2
|
|
explain (costs off) select t1.*,t2.x,t2.z
|
|
from t1 inner join t2 on t1.a = t2.x and t1.b = t2.y
|
|
group by t1.a,t1.b,t1.c,t1.d,t2.x,t2.z;
|
|
|
|
-- Cannot optimize when PK is deferrable
|
|
explain (costs off) select * from t3 group by a,b,c;
|
|
|
|
create temp table t1c () inherits (t1);
|
|
|
|
-- Ensure we don't remove any columns when t1 has a child table
|
|
explain (costs off) select * from t1 group by a,b,c,d;
|
|
|
|
-- Okay to remove columns if we're only querying the parent.
|
|
explain (costs off) select * from only t1 group by a,b,c,d;
|
|
|
|
create temp table p_t1 (
|
|
a int,
|
|
b int,
|
|
c int,
|
|
d int,
|
|
primary key(a,b)
|
|
) partition by list(a);
|
|
create temp table p_t1_1 partition of p_t1 for values in(1);
|
|
create temp table p_t1_2 partition of p_t1 for values in(2);
|
|
|
|
-- Ensure we can remove non-PK columns for partitioned tables.
|
|
explain (costs off) select * from p_t1 group by a,b,c,d;
|
|
|
|
drop table t1 cascade;
|
|
drop table t2;
|
|
drop table t3;
|
|
drop table p_t1;
|
|
|
|
--
|
|
-- Test GROUP BY matching of join columns that are type-coerced due to USING
|
|
--
|
|
|
|
create temp table t1(f1 int, f2 bigint);
|
|
create temp table t2(f1 bigint, f22 bigint);
|
|
|
|
select f1 from t1 left join t2 using (f1) group by f1;
|
|
select f1 from t1 left join t2 using (f1) group by t1.f1;
|
|
select t1.f1 from t1 left join t2 using (f1) group by t1.f1;
|
|
-- only this one should fail:
|
|
select t1.f1 from t1 left join t2 using (f1) group by f1;
|
|
|
|
drop table t1, t2;
|
|
|
|
--
|
|
-- Test combinations of DISTINCT and/or ORDER BY
|
|
--
|
|
|
|
select array_agg(a order by b)
|
|
from (values (1,4),(2,3),(3,1),(4,2)) v(a,b);
|
|
select array_agg(a order by a)
|
|
from (values (1,4),(2,3),(3,1),(4,2)) v(a,b);
|
|
select array_agg(a order by a desc)
|
|
from (values (1,4),(2,3),(3,1),(4,2)) v(a,b);
|
|
select array_agg(b order by a desc)
|
|
from (values (1,4),(2,3),(3,1),(4,2)) v(a,b);
|
|
|
|
select array_agg(distinct a)
|
|
from (values (1),(2),(1),(3),(null),(2)) v(a);
|
|
select array_agg(distinct a order by a)
|
|
from (values (1),(2),(1),(3),(null),(2)) v(a);
|
|
select array_agg(distinct a order by a desc)
|
|
from (values (1),(2),(1),(3),(null),(2)) v(a);
|
|
select array_agg(distinct a order by a desc nulls last)
|
|
from (values (1),(2),(1),(3),(null),(2)) v(a);
|
|
|
|
-- multi-arg aggs, strict/nonstrict, distinct/order by
|
|
|
|
select aggfstr(a,b,c)
|
|
from (values (1,3,'foo'),(0,null,null),(2,2,'bar'),(3,1,'baz')) v(a,b,c);
|
|
select aggfns(a,b,c)
|
|
from (values (1,3,'foo'),(0,null,null),(2,2,'bar'),(3,1,'baz')) v(a,b,c);
|
|
|
|
select aggfstr(distinct a,b,c)
|
|
from (values (1,3,'foo'),(0,null,null),(2,2,'bar'),(3,1,'baz')) v(a,b,c),
|
|
generate_series(1,3) i;
|
|
select aggfns(distinct a,b,c)
|
|
from (values (1,3,'foo'),(0,null,null),(2,2,'bar'),(3,1,'baz')) v(a,b,c),
|
|
generate_series(1,3) i;
|
|
|
|
select aggfstr(distinct a,b,c order by b)
|
|
from (values (1,3,'foo'),(0,null,null),(2,2,'bar'),(3,1,'baz')) v(a,b,c),
|
|
generate_series(1,3) i;
|
|
select aggfns(distinct a,b,c order by b)
|
|
from (values (1,3,'foo'),(0,null,null),(2,2,'bar'),(3,1,'baz')) v(a,b,c),
|
|
generate_series(1,3) i;
|
|
|
|
-- test specific code paths
|
|
|
|
select aggfns(distinct a,a,c order by c using ~<~,a)
|
|
from (values (1,3,'foo'),(0,null,null),(2,2,'bar'),(3,1,'baz')) v(a,b,c),
|
|
generate_series(1,2) i;
|
|
select aggfns(distinct a,a,c order by c using ~<~)
|
|
from (values (1,3,'foo'),(0,null,null),(2,2,'bar'),(3,1,'baz')) v(a,b,c),
|
|
generate_series(1,2) i;
|
|
select aggfns(distinct a,a,c order by a)
|
|
from (values (1,3,'foo'),(0,null,null),(2,2,'bar'),(3,1,'baz')) v(a,b,c),
|
|
generate_series(1,2) i;
|
|
select aggfns(distinct a,b,c order by a,c using ~<~,b)
|
|
from (values (1,3,'foo'),(0,null,null),(2,2,'bar'),(3,1,'baz')) v(a,b,c),
|
|
generate_series(1,2) i;
|
|
|
|
-- check node I/O via view creation and usage, also deparsing logic
|
|
|
|
create view agg_view1 as
|
|
select aggfns(a,b,c)
|
|
from (values (1,3,'foo'),(0,null,null),(2,2,'bar'),(3,1,'baz')) v(a,b,c);
|
|
|
|
select * from agg_view1;
|
|
select pg_get_viewdef('agg_view1'::regclass);
|
|
|
|
create or replace view agg_view1 as
|
|
select aggfns(distinct a,b,c)
|
|
from (values (1,3,'foo'),(0,null,null),(2,2,'bar'),(3,1,'baz')) v(a,b,c),
|
|
generate_series(1,3) i;
|
|
|
|
select * from agg_view1;
|
|
select pg_get_viewdef('agg_view1'::regclass);
|
|
|
|
create or replace view agg_view1 as
|
|
select aggfns(distinct a,b,c order by b)
|
|
from (values (1,3,'foo'),(0,null,null),(2,2,'bar'),(3,1,'baz')) v(a,b,c),
|
|
generate_series(1,3) i;
|
|
|
|
select * from agg_view1;
|
|
select pg_get_viewdef('agg_view1'::regclass);
|
|
|
|
create or replace view agg_view1 as
|
|
select aggfns(a,b,c order by b+1)
|
|
from (values (1,3,'foo'),(0,null,null),(2,2,'bar'),(3,1,'baz')) v(a,b,c);
|
|
|
|
select * from agg_view1;
|
|
select pg_get_viewdef('agg_view1'::regclass);
|
|
|
|
create or replace view agg_view1 as
|
|
select aggfns(a,a,c order by b)
|
|
from (values (1,3,'foo'),(0,null,null),(2,2,'bar'),(3,1,'baz')) v(a,b,c);
|
|
|
|
select * from agg_view1;
|
|
select pg_get_viewdef('agg_view1'::regclass);
|
|
|
|
create or replace view agg_view1 as
|
|
select aggfns(a,b,c order by c using ~<~)
|
|
from (values (1,3,'foo'),(0,null,null),(2,2,'bar'),(3,1,'baz')) v(a,b,c);
|
|
|
|
select * from agg_view1;
|
|
select pg_get_viewdef('agg_view1'::regclass);
|
|
|
|
create or replace view agg_view1 as
|
|
select aggfns(distinct a,b,c order by a,c using ~<~,b)
|
|
from (values (1,3,'foo'),(0,null,null),(2,2,'bar'),(3,1,'baz')) v(a,b,c),
|
|
generate_series(1,2) i;
|
|
|
|
select * from agg_view1;
|
|
select pg_get_viewdef('agg_view1'::regclass);
|
|
|
|
drop view agg_view1;
|
|
|
|
-- incorrect DISTINCT usage errors
|
|
|
|
select aggfns(distinct a,b,c order by i)
|
|
from (values (1,1,'foo')) v(a,b,c), generate_series(1,2) i;
|
|
select aggfns(distinct a,b,c order by a,b+1)
|
|
from (values (1,1,'foo')) v(a,b,c), generate_series(1,2) i;
|
|
select aggfns(distinct a,b,c order by a,b,i,c)
|
|
from (values (1,1,'foo')) v(a,b,c), generate_series(1,2) i;
|
|
select aggfns(distinct a,a,c order by a,b)
|
|
from (values (1,1,'foo')) v(a,b,c), generate_series(1,2) i;
|
|
|
|
-- string_agg tests
|
|
select string_agg(a,',') from (values('aaaa'),('bbbb'),('cccc')) g(a);
|
|
select string_agg(a,',') from (values('aaaa'),(null),('bbbb'),('cccc')) g(a);
|
|
select string_agg(a,'AB') from (values(null),(null),('bbbb'),('cccc')) g(a);
|
|
select string_agg(a,',') from (values(null),(null)) g(a);
|
|
|
|
-- check some implicit casting cases, as per bug #5564
|
|
select string_agg(distinct f1, ',' order by f1) from varchar_tbl; -- ok
|
|
select string_agg(distinct f1::text, ',' order by f1) from varchar_tbl; -- not ok
|
|
select string_agg(distinct f1, ',' order by f1::text) from varchar_tbl; -- not ok
|
|
select string_agg(distinct f1::text, ',' order by f1::text) from varchar_tbl; -- ok
|
|
|
|
-- string_agg bytea tests
|
|
create table bytea_test_table(v bytea);
|
|
|
|
select string_agg(v, '') from bytea_test_table;
|
|
|
|
insert into bytea_test_table values(decode('ff','hex'));
|
|
|
|
select string_agg(v, '') from bytea_test_table;
|
|
|
|
insert into bytea_test_table values(decode('aa','hex'));
|
|
|
|
select string_agg(v, '') from bytea_test_table;
|
|
select string_agg(v, NULL) from bytea_test_table;
|
|
select string_agg(v, decode('ee', 'hex')) from bytea_test_table;
|
|
|
|
drop table bytea_test_table;
|
|
|
|
-- FILTER tests
|
|
|
|
select min(unique1) filter (where unique1 > 100) from tenk1;
|
|
|
|
select sum(1/ten) filter (where ten > 0) from tenk1;
|
|
|
|
select ten, sum(distinct four) filter (where four::text ~ '123') from onek a
|
|
group by ten;
|
|
|
|
select ten, sum(distinct four) filter (where four > 10) from onek a
|
|
group by ten
|
|
having exists (select 1 from onek b where sum(distinct a.four) = b.four);
|
|
|
|
select max(foo COLLATE "C") filter (where (bar collate "POSIX") > '0')
|
|
from (values ('a', 'b')) AS v(foo,bar);
|
|
|
|
-- outer reference in FILTER (PostgreSQL extension)
|
|
select (select count(*)
|
|
from (values (1)) t0(inner_c))
|
|
from (values (2),(3)) t1(outer_c); -- inner query is aggregation query
|
|
select (select count(*) filter (where outer_c <> 0)
|
|
from (values (1)) t0(inner_c))
|
|
from (values (2),(3)) t1(outer_c); -- outer query is aggregation query
|
|
select (select count(inner_c) filter (where outer_c <> 0)
|
|
from (values (1)) t0(inner_c))
|
|
from (values (2),(3)) t1(outer_c); -- inner query is aggregation query
|
|
select
|
|
(select max((select i.unique2 from tenk1 i where i.unique1 = o.unique1))
|
|
filter (where o.unique1 < 10))
|
|
from tenk1 o; -- outer query is aggregation query
|
|
|
|
-- subquery in FILTER clause (PostgreSQL extension)
|
|
select sum(unique1) FILTER (WHERE
|
|
unique1 IN (SELECT unique1 FROM onek where unique1 < 100)) FROM tenk1;
|
|
|
|
-- exercise lots of aggregate parts with FILTER
|
|
select aggfns(distinct a,b,c order by a,c using ~<~,b) filter (where a > 1)
|
|
from (values (1,3,'foo'),(0,null,null),(2,2,'bar'),(3,1,'baz')) v(a,b,c),
|
|
generate_series(1,2) i;
|
|
|
|
-- ordered-set aggregates
|
|
|
|
select p, percentile_cont(p) within group (order by x::float8)
|
|
from generate_series(1,5) x,
|
|
(values (0::float8),(0.1),(0.25),(0.4),(0.5),(0.6),(0.75),(0.9),(1)) v(p)
|
|
group by p order by p;
|
|
|
|
select p, percentile_cont(p order by p) within group (order by x) -- error
|
|
from generate_series(1,5) x,
|
|
(values (0::float8),(0.1),(0.25),(0.4),(0.5),(0.6),(0.75),(0.9),(1)) v(p)
|
|
group by p order by p;
|
|
|
|
select p, sum() within group (order by x::float8) -- error
|
|
from generate_series(1,5) x,
|
|
(values (0::float8),(0.1),(0.25),(0.4),(0.5),(0.6),(0.75),(0.9),(1)) v(p)
|
|
group by p order by p;
|
|
|
|
select p, percentile_cont(p,p) -- error
|
|
from generate_series(1,5) x,
|
|
(values (0::float8),(0.1),(0.25),(0.4),(0.5),(0.6),(0.75),(0.9),(1)) v(p)
|
|
group by p order by p;
|
|
|
|
select percentile_cont(0.5) within group (order by b) from aggtest;
|
|
select percentile_cont(0.5) within group (order by b), sum(b) from aggtest;
|
|
select percentile_cont(0.5) within group (order by thousand) from tenk1;
|
|
select percentile_disc(0.5) within group (order by thousand) from tenk1;
|
|
select rank(3) within group (order by x)
|
|
from (values (1),(1),(2),(2),(3),(3),(4)) v(x);
|
|
select cume_dist(3) within group (order by x)
|
|
from (values (1),(1),(2),(2),(3),(3),(4)) v(x);
|
|
select percent_rank(3) within group (order by x)
|
|
from (values (1),(1),(2),(2),(3),(3),(4),(5)) v(x);
|
|
select dense_rank(3) within group (order by x)
|
|
from (values (1),(1),(2),(2),(3),(3),(4)) v(x);
|
|
|
|
select percentile_disc(array[0,0.1,0.25,0.5,0.75,0.9,1]) within group (order by thousand)
|
|
from tenk1;
|
|
select percentile_cont(array[0,0.25,0.5,0.75,1]) within group (order by thousand)
|
|
from tenk1;
|
|
select percentile_disc(array[[null,1,0.5],[0.75,0.25,null]]) within group (order by thousand)
|
|
from tenk1;
|
|
select percentile_cont(array[0,1,0.25,0.75,0.5,1,0.3,0.32,0.35,0.38,0.4]) within group (order by x)
|
|
from generate_series(1,6) x;
|
|
|
|
select ten, mode() within group (order by string4) from tenk1 group by ten;
|
|
|
|
select percentile_disc(array[0.25,0.5,0.75]) within group (order by x)
|
|
from unnest('{fred,jim,fred,jack,jill,fred,jill,jim,jim,sheila,jim,sheila}'::text[]) u(x);
|
|
|
|
-- check collation propagates up in suitable cases:
|
|
select pg_collation_for(percentile_disc(1) within group (order by x collate "POSIX"))
|
|
from (values ('fred'),('jim')) v(x);
|
|
|
|
-- ordered-set aggs created with CREATE AGGREGATE
|
|
select test_rank(3) within group (order by x)
|
|
from (values (1),(1),(2),(2),(3),(3),(4)) v(x);
|
|
select test_percentile_disc(0.5) within group (order by thousand) from tenk1;
|
|
|
|
-- ordered-set aggs can't use ungrouped vars in direct args:
|
|
select rank(x) within group (order by x) from generate_series(1,5) x;
|
|
|
|
-- outer-level agg can't use a grouped arg of a lower level, either:
|
|
select array(select percentile_disc(a) within group (order by x)
|
|
from (values (0.3),(0.7)) v(a) group by a)
|
|
from generate_series(1,5) g(x);
|
|
|
|
-- agg in the direct args is a grouping violation, too:
|
|
select rank(sum(x)) within group (order by x) from generate_series(1,5) x;
|
|
|
|
-- hypothetical-set type unification and argument-count failures:
|
|
select rank(3) within group (order by x) from (values ('fred'),('jim')) v(x);
|
|
select rank(3) within group (order by stringu1,stringu2) from tenk1;
|
|
select rank('fred') within group (order by x) from generate_series(1,5) x;
|
|
select rank('adam'::text collate "C") within group (order by x collate "POSIX")
|
|
from (values ('fred'),('jim')) v(x);
|
|
-- hypothetical-set type unification successes:
|
|
select rank('adam'::varchar) within group (order by x) from (values ('fred'),('jim')) v(x);
|
|
select rank('3') within group (order by x) from generate_series(1,5) x;
|
|
|
|
-- divide by zero check
|
|
select percent_rank(0) within group (order by x) from generate_series(1,0) x;
|
|
|
|
-- deparse and multiple features:
|
|
create view aggordview1 as
|
|
select ten,
|
|
percentile_disc(0.5) within group (order by thousand) as p50,
|
|
percentile_disc(0.5) within group (order by thousand) filter (where hundred=1) as px,
|
|
rank(5,'AZZZZ',50) within group (order by hundred, string4 desc, hundred)
|
|
from tenk1
|
|
group by ten order by ten;
|
|
|
|
select pg_get_viewdef('aggordview1');
|
|
select * from aggordview1 order by ten;
|
|
drop view aggordview1;
|
|
|
|
-- variadic aggregates
|
|
select least_agg(q1,q2) from int8_tbl;
|
|
select least_agg(variadic array[q1,q2]) from int8_tbl;
|
|
|
|
select cleast_agg(q1,q2) from int8_tbl;
|
|
select cleast_agg(4.5,f1) from int4_tbl;
|
|
select cleast_agg(variadic array[4.5,f1]) from int4_tbl;
|
|
select pg_typeof(cleast_agg(variadic array[4.5,f1])) from int4_tbl;
|
|
|
|
-- test aggregates with common transition functions share the same states
|
|
begin work;
|
|
|
|
create type avg_state as (total bigint, count bigint);
|
|
|
|
create or replace function avg_transfn(state avg_state, n int) returns avg_state as
|
|
$$
|
|
declare new_state avg_state;
|
|
begin
|
|
raise notice 'avg_transfn called with %', n;
|
|
if state is null then
|
|
if n is not null then
|
|
new_state.total := n;
|
|
new_state.count := 1;
|
|
return new_state;
|
|
end if;
|
|
return null;
|
|
elsif n is not null then
|
|
state.total := state.total + n;
|
|
state.count := state.count + 1;
|
|
return state;
|
|
end if;
|
|
|
|
return null;
|
|
end
|
|
$$ language plpgsql;
|
|
|
|
create function avg_finalfn(state avg_state) returns int4 as
|
|
$$
|
|
begin
|
|
if state is null then
|
|
return NULL;
|
|
else
|
|
return state.total / state.count;
|
|
end if;
|
|
end
|
|
$$ language plpgsql;
|
|
|
|
create function sum_finalfn(state avg_state) returns int4 as
|
|
$$
|
|
begin
|
|
if state is null then
|
|
return NULL;
|
|
else
|
|
return state.total;
|
|
end if;
|
|
end
|
|
$$ language plpgsql;
|
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create aggregate my_avg(int4)
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(
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stype = avg_state,
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sfunc = avg_transfn,
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finalfunc = avg_finalfn
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);
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create aggregate my_sum(int4)
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(
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stype = avg_state,
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sfunc = avg_transfn,
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finalfunc = sum_finalfn
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);
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-- aggregate state should be shared as aggs are the same.
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select my_avg(one),my_avg(one) from (values(1),(3)) t(one);
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-- aggregate state should be shared as transfn is the same for both aggs.
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select my_avg(one),my_sum(one) from (values(1),(3)) t(one);
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-- same as previous one, but with DISTINCT, which requires sorting the input.
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select my_avg(distinct one),my_sum(distinct one) from (values(1),(3),(1)) t(one);
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-- shouldn't share states due to the distinctness not matching.
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select my_avg(distinct one),my_sum(one) from (values(1),(3)) t(one);
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-- shouldn't share states due to the filter clause not matching.
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select my_avg(one) filter (where one > 1),my_sum(one) from (values(1),(3)) t(one);
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-- this should not share the state due to different input columns.
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select my_avg(one),my_sum(two) from (values(1,2),(3,4)) t(one,two);
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-- exercise cases where OSAs share state
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select
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percentile_cont(0.5) within group (order by a),
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percentile_disc(0.5) within group (order by a)
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from (values(1::float8),(3),(5),(7)) t(a);
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select
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percentile_cont(0.25) within group (order by a),
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percentile_disc(0.5) within group (order by a)
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from (values(1::float8),(3),(5),(7)) t(a);
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-- these can't share state currently
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select
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rank(4) within group (order by a),
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dense_rank(4) within group (order by a)
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from (values(1),(3),(5),(7)) t(a);
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-- test that aggs with the same sfunc and initcond share the same agg state
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create aggregate my_sum_init(int4)
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(
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stype = avg_state,
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sfunc = avg_transfn,
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finalfunc = sum_finalfn,
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initcond = '(10,0)'
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);
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create aggregate my_avg_init(int4)
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(
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stype = avg_state,
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sfunc = avg_transfn,
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finalfunc = avg_finalfn,
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initcond = '(10,0)'
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);
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create aggregate my_avg_init2(int4)
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(
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stype = avg_state,
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sfunc = avg_transfn,
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finalfunc = avg_finalfn,
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initcond = '(4,0)'
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);
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-- state should be shared if INITCONDs are matching
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select my_sum_init(one),my_avg_init(one) from (values(1),(3)) t(one);
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-- Varying INITCONDs should cause the states not to be shared.
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select my_sum_init(one),my_avg_init2(one) from (values(1),(3)) t(one);
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rollback;
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-- test aggregate state sharing to ensure it works if one aggregate has a
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-- finalfn and the other one has none.
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begin work;
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create or replace function sum_transfn(state int4, n int4) returns int4 as
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$$
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declare new_state int4;
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begin
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raise notice 'sum_transfn called with %', n;
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if state is null then
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if n is not null then
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new_state := n;
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return new_state;
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end if;
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return null;
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elsif n is not null then
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state := state + n;
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return state;
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end if;
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return null;
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end
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$$ language plpgsql;
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create function halfsum_finalfn(state int4) returns int4 as
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$$
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begin
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if state is null then
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return NULL;
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else
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return state / 2;
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end if;
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end
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$$ language plpgsql;
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create aggregate my_sum(int4)
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(
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stype = int4,
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sfunc = sum_transfn
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);
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create aggregate my_half_sum(int4)
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(
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stype = int4,
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sfunc = sum_transfn,
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finalfunc = halfsum_finalfn
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);
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-- Agg state should be shared even though my_sum has no finalfn
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select my_sum(one),my_half_sum(one) from (values(1),(2),(3),(4)) t(one);
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rollback;
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-- test that the aggregate transition logic correctly handles
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-- transition / combine functions returning NULL
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-- First test the case of a normal transition function returning NULL
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BEGIN;
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CREATE FUNCTION balkifnull(int8, int4)
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RETURNS int8
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STRICT
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LANGUAGE plpgsql AS $$
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BEGIN
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IF $1 IS NULL THEN
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RAISE 'erroneously called with NULL argument';
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END IF;
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RETURN NULL;
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END$$;
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CREATE AGGREGATE balk(int4)
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(
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SFUNC = balkifnull(int8, int4),
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STYPE = int8,
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PARALLEL = SAFE,
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INITCOND = '0'
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);
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SELECT balk(hundred) FROM tenk1;
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ROLLBACK;
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-- Secondly test the case of a parallel aggregate combiner function
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-- returning NULL. For that use normal transition function, but a
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-- combiner function returning NULL.
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BEGIN ISOLATION LEVEL REPEATABLE READ;
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CREATE FUNCTION balkifnull(int8, int8)
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RETURNS int8
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PARALLEL SAFE
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STRICT
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LANGUAGE plpgsql AS $$
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BEGIN
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IF $1 IS NULL THEN
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RAISE 'erroneously called with NULL argument';
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END IF;
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RETURN NULL;
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END$$;
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CREATE AGGREGATE balk(int4)
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(
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SFUNC = int4_sum(int8, int4),
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STYPE = int8,
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COMBINEFUNC = balkifnull(int8, int8),
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PARALLEL = SAFE,
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INITCOND = '0'
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);
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-- force use of parallelism
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ALTER TABLE tenk1 set (parallel_workers = 4);
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SET LOCAL parallel_setup_cost=0;
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SET LOCAL max_parallel_workers_per_gather=4;
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EXPLAIN (COSTS OFF) SELECT balk(hundred) FROM tenk1;
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SELECT balk(hundred) FROM tenk1;
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ROLLBACK;
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-- test coverage for aggregate combine/serial/deserial functions
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BEGIN ISOLATION LEVEL REPEATABLE READ;
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SET parallel_setup_cost = 0;
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SET parallel_tuple_cost = 0;
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SET min_parallel_table_scan_size = 0;
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SET max_parallel_workers_per_gather = 4;
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SET parallel_leader_participation = off;
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SET enable_indexonlyscan = off;
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-- variance(int4) covers numeric_poly_combine
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-- sum(int8) covers int8_avg_combine
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-- regr_count(float8, float8) covers int8inc_float8_float8 and aggregates with > 1 arg
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EXPLAIN (COSTS OFF, VERBOSE)
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SELECT variance(unique1::int4), sum(unique1::int8), regr_count(unique1::float8, unique1::float8)
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FROM (SELECT * FROM tenk1
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UNION ALL SELECT * FROM tenk1
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UNION ALL SELECT * FROM tenk1
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UNION ALL SELECT * FROM tenk1) u;
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SELECT variance(unique1::int4), sum(unique1::int8), regr_count(unique1::float8, unique1::float8)
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FROM (SELECT * FROM tenk1
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UNION ALL SELECT * FROM tenk1
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UNION ALL SELECT * FROM tenk1
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UNION ALL SELECT * FROM tenk1) u;
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-- variance(int8) covers numeric_combine
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-- avg(numeric) covers numeric_avg_combine
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EXPLAIN (COSTS OFF, VERBOSE)
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SELECT variance(unique1::int8), avg(unique1::numeric)
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FROM (SELECT * FROM tenk1
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UNION ALL SELECT * FROM tenk1
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UNION ALL SELECT * FROM tenk1
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UNION ALL SELECT * FROM tenk1) u;
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SELECT variance(unique1::int8), avg(unique1::numeric)
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FROM (SELECT * FROM tenk1
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UNION ALL SELECT * FROM tenk1
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UNION ALL SELECT * FROM tenk1
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UNION ALL SELECT * FROM tenk1) u;
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ROLLBACK;
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-- test coverage for dense_rank
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SELECT dense_rank(x) WITHIN GROUP (ORDER BY x) FROM (VALUES (1),(1),(2),(2),(3),(3)) v(x) GROUP BY (x) ORDER BY 1;
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-- Ensure that the STRICT checks for aggregates does not take NULLness
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-- of ORDER BY columns into account. See bug report around
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-- 2a505161-2727-2473-7c46-591ed108ac52@email.cz
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SELECT min(x ORDER BY y) FROM (VALUES(1, NULL)) AS d(x,y);
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SELECT min(x ORDER BY y) FROM (VALUES(1, 2)) AS d(x,y);
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-- check collation-sensitive matching between grouping expressions
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select v||'a', case v||'a' when 'aa' then 1 else 0 end, count(*)
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from unnest(array['a','b']) u(v)
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group by v||'a' order by 1;
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select v||'a', case when v||'a' = 'aa' then 1 else 0 end, count(*)
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from unnest(array['a','b']) u(v)
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group by v||'a' order by 1;
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-- Make sure that generation of HashAggregate for uniqification purposes
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-- does not lead to array overflow due to unexpected duplicate hash keys
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-- see CAFeeJoKKu0u+A_A9R9316djW-YW3-+Gtgvy3ju655qRHR3jtdA@mail.gmail.com
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explain (costs off)
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select 1 from tenk1
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where (hundred, thousand) in (select twothousand, twothousand from onek);
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--
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-- Hash Aggregation Spill tests
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--
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set enable_sort=false;
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set work_mem='64kB';
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select unique1, count(*), sum(twothousand) from tenk1
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group by unique1
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having sum(fivethous) > 4975
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order by sum(twothousand);
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set work_mem to default;
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set enable_sort to default;
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--
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-- Compare results between plans using sorting and plans using hash
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-- aggregation. Force spilling in both cases by setting work_mem low.
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--
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set work_mem='64kB';
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create table agg_data_2k as
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select g from generate_series(0, 1999) g;
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analyze agg_data_2k;
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create table agg_data_20k as
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select g from generate_series(0, 19999) g;
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analyze agg_data_20k;
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-- Produce results with sorting.
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set enable_hashagg = false;
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set jit_above_cost = 0;
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explain (costs off)
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select g%10000 as c1, sum(g::numeric) as c2, count(*) as c3
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from agg_data_20k group by g%10000;
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create table agg_group_1 as
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select g%10000 as c1, sum(g::numeric) as c2, count(*) as c3
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from agg_data_20k group by g%10000;
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create table agg_group_2 as
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select * from
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(values (100), (300), (500)) as r(a),
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lateral (
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select (g/2)::numeric as c1,
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array_agg(g::numeric) as c2,
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count(*) as c3
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from agg_data_2k
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where g < r.a
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group by g/2) as s;
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set jit_above_cost to default;
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create table agg_group_3 as
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select (g/2)::numeric as c1, sum(7::int4) as c2, count(*) as c3
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from agg_data_2k group by g/2;
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create table agg_group_4 as
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select (g/2)::numeric as c1, array_agg(g::numeric) as c2, count(*) as c3
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from agg_data_2k group by g/2;
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-- Produce results with hash aggregation
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set enable_hashagg = true;
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set enable_sort = false;
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set jit_above_cost = 0;
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explain (costs off)
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select g%10000 as c1, sum(g::numeric) as c2, count(*) as c3
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from agg_data_20k group by g%10000;
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create table agg_hash_1 as
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select g%10000 as c1, sum(g::numeric) as c2, count(*) as c3
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from agg_data_20k group by g%10000;
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create table agg_hash_2 as
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select * from
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(values (100), (300), (500)) as r(a),
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lateral (
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select (g/2)::numeric as c1,
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array_agg(g::numeric) as c2,
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count(*) as c3
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from agg_data_2k
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where g < r.a
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group by g/2) as s;
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set jit_above_cost to default;
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create table agg_hash_3 as
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select (g/2)::numeric as c1, sum(7::int4) as c2, count(*) as c3
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from agg_data_2k group by g/2;
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create table agg_hash_4 as
|
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select (g/2)::numeric as c1, array_agg(g::numeric) as c2, count(*) as c3
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from agg_data_2k group by g/2;
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set enable_sort = true;
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set work_mem to default;
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-- Compare group aggregation results to hash aggregation results
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(select * from agg_hash_1 except select * from agg_group_1)
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union all
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(select * from agg_group_1 except select * from agg_hash_1);
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(select * from agg_hash_2 except select * from agg_group_2)
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union all
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(select * from agg_group_2 except select * from agg_hash_2);
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(select * from agg_hash_3 except select * from agg_group_3)
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union all
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(select * from agg_group_3 except select * from agg_hash_3);
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(select * from agg_hash_4 except select * from agg_group_4)
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union all
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(select * from agg_group_4 except select * from agg_hash_4);
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drop table agg_group_1;
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drop table agg_group_2;
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drop table agg_group_3;
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drop table agg_group_4;
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drop table agg_hash_1;
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drop table agg_hash_2;
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drop table agg_hash_3;
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drop table agg_hash_4;
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