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 --
 -- Portions Copyright (c) 1996-2019, PostgreSQL Global Development Group
 --
 --
 -- AGGREGATES [Part 4]
 -- https://github.com/postgres/postgres/blob/REL_12_BETA2/src/test/regress/sql/aggregates.sql#L607-L997
 
 -- Test aggregate operator with codegen on and off.
 --CONFIG_DIM1 spark.sql.codegen.wholeStage=true
 --CONFIG_DIM1 spark.sql.codegen.wholeStage=false,spark.sql.codegen.factoryMode=CODEGEN_ONLY
 --CONFIG_DIM1 spark.sql.codegen.wholeStage=false,spark.sql.codegen.factoryMode=NO_CODEGEN
 
 -- [SPARK-27980] Ordered-Set Aggregate Functions
 -- 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;
 -- [SPARK-28661] Hypothetical-Set Aggregate Functions
 -- 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);
 
 -- [SPARK-27980] Ordered-Set Aggregate Functions
 -- 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;
 
 -- [SPARK-27980] Ordered-Set Aggregate Functions
 -- [SPARK-28382] Array Functions: unnest
 -- 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);
 
 -- [SPARK-28669] System Information Functions
 -- 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);
 
 -- test_rank and test_percentile_disc function created by create_aggregate.sql
 -- 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;
 
 -- [SPARK-28661] Hypothetical-Set Aggregate Functions
 -- 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;
 
 -- [SPARK-27980] Ordered-Set Aggregate Functions
 -- 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);
 
 -- [SPARK-28661] Hypothetical-Set Aggregate Functions
 -- 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;
 
 -- [SPARK-28661] Hypothetical-Set Aggregate Functions
 -- 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;
 
 -- [SPARK-28661] Hypothetical-Set Aggregate Functions
 -- divide by zero check
 -- select percent_rank(0) within group (order by x) from generate_series(1,0) x;
 
 -- [SPARK-27980] Ordered-Set Aggregate Functions
 -- 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;
 
 -- least_agg created by create_aggregate.sql
 -- variadic aggregates
 -- select least_agg(q1,q2) from int8_tbl;
 -- select least_agg(variadic array[q1,q2]) from int8_tbl;
 
 
 -- Skip these tests because we do not support create type
 -- 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;
 
 -- create aggregate my_avg(int4)
 -- (
 --    stype = avg_state,
 --    sfunc = avg_transfn,
 --    finalfunc = avg_finalfn
 -- );
 --
 -- create aggregate my_sum(int4)
 -- (
 --    stype = avg_state,
 --    sfunc = avg_transfn,
 --    finalfunc = sum_finalfn
 -- );
 
 -- aggregate state should be shared as aggs are the same.
 -- select my_avg(one),my_avg(one) from (values(1),(3)) t(one);
 
 -- aggregate state should be shared as transfn is the same for both aggs.
 -- select my_avg(one),my_sum(one) from (values(1),(3)) t(one);
 
 -- same as previous one, but with DISTINCT, which requires sorting the input.
 -- select my_avg(distinct one),my_sum(distinct one) from (values(1),(3),(1)) t(one);
 
 -- shouldn't share states due to the distinctness not matching.
 -- select my_avg(distinct one),my_sum(one) from (values(1),(3)) t(one);
 
 -- shouldn't share states due to the filter clause not matching.
 -- select my_avg(one) filter (where one > 1),my_sum(one) from (values(1),(3)) t(one);
 
 -- this should not share the state due to different input columns.
 -- select my_avg(one),my_sum(two) from (values(1,2),(3,4)) t(one,two);
 
 -- [SPARK-27980] Ordered-Set Aggregate Functions
 -- exercise cases where OSAs share state
 -- select
 --   percentile_cont(0.5) within group (order by a),
 --   percentile_disc(0.5) within group (order by a)
 -- from (values(1::float8),(3),(5),(7)) t(a);
 
 -- select
 --   percentile_cont(0.25) within group (order by a),
 --   percentile_disc(0.5) within group (order by a)
 -- from (values(1::float8),(3),(5),(7)) t(a);
 
 -- [SPARK-28661] Hypothetical-Set Aggregate Functions
 -- these can't share state currently
 -- select
 --   rank(4) within group (order by a),
 --   dense_rank(4) within group (order by a)
 -- from (values(1),(3),(5),(7)) t(a);
 
 -- test that aggs with the same sfunc and initcond share the same agg state
 -- create aggregate my_sum_init(int4)
 -- (
 --    stype = avg_state,
 --    sfunc = avg_transfn,
 --    finalfunc = sum_finalfn,
 --    initcond = '(10,0)'
 -- );
 
 -- create aggregate my_avg_init(int4)
 -- (
 --    stype = avg_state,
 --    sfunc = avg_transfn,
 --    finalfunc = avg_finalfn,
 --    initcond = '(10,0)'
 -- );
 
 -- create aggregate my_avg_init2(int4)
 -- (
 --    stype = avg_state,
 --    sfunc = avg_transfn,
 --    finalfunc = avg_finalfn,
 --    initcond = '(4,0)'
 -- );
 
 -- state should be shared if INITCONDs are matching
 -- select my_sum_init(one),my_avg_init(one) from (values(1),(3)) t(one);
 
 -- Varying INITCONDs should cause the states not to be shared.
 -- select my_sum_init(one),my_avg_init2(one) from (values(1),(3)) t(one);
 
 -- rollback;
 
 -- test aggregate state sharing to ensure it works if one aggregate has a
 -- finalfn and the other one has none.
 -- begin work;
 
 -- create or replace function sum_transfn(state int4, n int4) returns int4 as
 -- $$
 -- declare new_state int4;
 -- begin
 --      raise notice 'sum_transfn called with %', n;
 --      if state is null then
 --              if n is not null then
 --                      new_state := n;
 --                      return new_state;
 --              end if;
 --              return null;
 --      elsif n is not null then
 --              state := state + n;
 --              return state;
 --      end if;
 --
 --      return null;
 -- end
 -- $$ language plpgsql;
 
 -- create function halfsum_finalfn(state int4) returns int4 as
 -- $$
 -- begin
 --      if state is null then
 --              return NULL;
 --      else
 --              return state / 2;
 --      end if;
 -- end
 -- $$ language plpgsql;
 
 -- create aggregate my_sum(int4)
 -- (
 --    stype = int4,
 --    sfunc = sum_transfn
 -- );
 
 -- create aggregate my_half_sum(int4)
 -- (
 --    stype = int4,
 --    sfunc = sum_transfn,
 --    finalfunc = halfsum_finalfn
 -- );
 
 -- Agg state should be shared even though my_sum has no finalfn
 -- select my_sum(one),my_half_sum(one) from (values(1),(2),(3),(4)) t(one);
 
 -- rollback;
 
 
 -- test that the aggregate transition logic correctly handles
 -- transition / combine functions returning NULL
 
 -- First test the case of a normal transition function returning NULL
 -- BEGIN;
 -- CREATE FUNCTION balkifnull(int8, int4)
 -- RETURNS int8
 -- STRICT
 -- LANGUAGE plpgsql AS $$
 -- BEGIN
 --     IF $1 IS NULL THEN
 --        RAISE 'erroneously called with NULL argument';
 --     END IF;
 --     RETURN NULL;
 -- END$$;
 
 -- CREATE AGGREGATE balk(int4)
 -- (
 --     SFUNC = balkifnull(int8, int4),
 --     STYPE = int8,
 --     PARALLEL = SAFE,
 --     INITCOND = '0'
 -- );
 
 -- SELECT balk(hundred) FROM tenk1;
 
 -- ROLLBACK;
 
 -- Secondly test the case of a parallel aggregate combiner function
 -- returning NULL. For that use normal transition function, but a
 -- combiner function returning NULL.
 -- BEGIN ISOLATION LEVEL REPEATABLE READ;
 -- CREATE FUNCTION balkifnull(int8, int8)
 -- RETURNS int8
 -- PARALLEL SAFE
 -- STRICT
 -- LANGUAGE plpgsql AS $$
 -- BEGIN
 --     IF $1 IS NULL THEN
 --        RAISE 'erroneously called with NULL argument';
 --     END IF;
 --     RETURN NULL;
 -- END$$;
 
 -- CREATE AGGREGATE balk(int4)
 -- (
 --     SFUNC = int4_sum(int8, int4),
 --     STYPE = int8,
 --     COMBINEFUNC = balkifnull(int8, int8),
 --     PARALLEL = SAFE,
 --     INITCOND = '0'
 -- );
 
 -- force use of parallelism
 -- ALTER TABLE tenk1 set (parallel_workers = 4);
 -- SET LOCAL parallel_setup_cost=0;
 -- SET LOCAL max_parallel_workers_per_gather=4;
 
 -- EXPLAIN (COSTS OFF) SELECT balk(hundred) FROM tenk1;
 -- SELECT balk(hundred) FROM tenk1;
 
 -- ROLLBACK;
 
 -- test coverage for aggregate combine/serial/deserial functions
 -- BEGIN ISOLATION LEVEL REPEATABLE READ;
 
 -- SET parallel_setup_cost = 0;
 -- SET parallel_tuple_cost = 0;
 -- SET min_parallel_table_scan_size = 0;
 -- SET max_parallel_workers_per_gather = 4;
 -- SET enable_indexonlyscan = off;
 
 -- [SPARK-28663] Aggregate Functions for Statistics
 -- variance(int4) covers numeric_poly_combine
 -- sum(int8) covers int8_avg_combine
 -- regr_count(float8, float8) covers int8inc_float8_float8 and aggregates with > 1 arg
 -- EXPLAIN (COSTS OFF, VERBOSE)
 --   SELECT variance(unique1::int4), sum(unique1::int8), regr_count(unique1::float8, unique1::float8) FROM tenk1;
 
 -- SELECT variance(unique1::int4), sum(unique1::int8), regr_count(unique1::float8, unique1::float8) FROM tenk1;
 
 -- ROLLBACK;
 
 -- [SPARK-28661] Hypothetical-Set Aggregate Functions
 -- test coverage for dense_rank
 -- 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;
 
 
 -- [SPARK-28664] ORDER BY in aggregate function
 -- Ensure that the STRICT checks for aggregates does not take NULLness
 -- of ORDER BY columns into account. See bug report around
 -- 2a505161-2727-2473-7c46-591ed108ac52@email.cz
 -- SELECT min(x ORDER BY y) FROM (VALUES(1, NULL)) AS d(x,y);
 -- SELECT min(x ORDER BY y) FROM (VALUES(1, 2)) AS d(x,y);
 
 -- [SPARK-28382] Array Functions: unnest
 -- check collation-sensitive matching between grouping expressions
 -- select v||'a', case v||'a' when 'aa' then 1 else 0 end, count(*)
 --   from unnest(array['a','b']) u(v)
 --  group by v||'a' order by 1;
 -- select v||'a', case when v||'a' = 'aa' then 1 else 0 end, count(*)
 --   from unnest(array['a','b']) u(v)
 --  group by v||'a' order by 1;
 
 -- Make sure that generation of HashAggregate for uniqification purposes
 -- does not lead to array overflow due to unexpected duplicate hash keys
 -- see CAFeeJoKKu0u+A_A9R9316djW-YW3-+Gtgvy3ju655qRHR3jtdA@mail.gmail.com
 -- explain (costs off)
 --   select 1 from tenk1
 --    where (hundred, thousand) in (select twothousand, twothousand from onek);

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