====
---- QUERY
# This query will do a full table scan, doing a simple aggregation on all cols with
# a simple predicate
select count(*),
  sum(id), count(bool_col), sum(tinyint_col), sum(smallint_col),
  sum(int_col), sum(bigint_col), max(float_col), max(double_col),
  max(date_string_col), max(string_col), max(timestamp_col)
from alltypesagg
where id % 2 = 0 and day is not null
---- RESULTS
5000,24995000,5000,20000,245000,2495000,24950000,1097.800048828125,10079.8,'01/10/10','998',2010-01-10 18:00:55.300000000
---- TYPES
BIGINT, BIGINT, BIGINT, BIGINT, BIGINT, BIGINT, BIGINT, FLOAT, DOUBLE, STRING, STRING, TIMESTAMP
====
---- QUERY
# This query will do a join, projecting one string col from each table.
# This is interesting because the join contains string cols which causes the scanners
# to do different memory handling.
select sum(t1.id), sum(t1.int_col),max(t1.date_string_col), max(t2.string_col)
from alltypesagg t1
inner join alltypesagg t2
  on t1.id = t2.id and t1.day is not null and t2.day is not null
---- RESULTS
49995000,4995000,'01/10/10','999'
---- TYPES
BIGINT, BIGINT, STRING, STRING
====
---- QUERY
# This query does a top-n on non-string cols.  This is different because without
# string cols, scanners will handle io buffers differently.  They don't need to
# be passed up the execution tree.
select id, bool_col, int_col
from alltypesagg where day is not null
order by 1 desc, 2 desc, 3 desc
limit 10
---- RESULTS
9999,false,999
9998,true,998
9997,false,997
9996,true,996
9995,false,995
9994,true,994
9993,false,993
9992,true,992
9991,false,991
9990,true,990
---- TYPES
INT, BOOLEAN, INT
====