Two tables like
table1
+----+-------+-----+
| id | sname | sal |
+----+-------+-----+
| 1 | X | 100 |
| 2 | Y | 200 |
| 3 | Z | 400 |
+----+-------+-----+
Table2
+----+-------+-----+
| id | sname | sal |
+----+-------+-----+
| 1 | A | 500 |
| 2 | B | 200 |
| 3 | C | 400
| 4 A 100
+----+-------+-----+
Both the tables having relation ship id column
i need calculate the sum sal group by table1.sname at the same time those who are matched to table2
the output like
+-------+-------+---------------------
| Table1.sname | Table2.sname | sum |
+-------+-------+-----+ ----------------
| A | W | 600 |
| B | Y | 200 |
| B | F | 300 |
| C | Z | 400 |
+-------+-------+----------------------
select sum(sal),a.sname,b.sname
from table1 a,
(select id,sname from table2 group by sname,id) as b
where a.id=b.id
group by a.sname,b.sname;
but its not given proper o/p
your question is little ambiguous...but maybe you want this.
query
select Table11.id, Table1.sname, Table2.sname, (Table1.sal+Table2.sal) as Sum
from Table1, Table2
where Table1.id = Table2.id;
result
Table1.id | Table2.sname | Table2.sname | sum
-----------+--------------+--------------+-----
1 | a | d | 500
2 | b | e | 700
3 | c | f | 900
Related
Here's a crude example I've made up to illustrate what I want to achieve:
table1:
| Shop | Product | QuantityInStock |
| a | Prod1 | 13 |
| a | Prod3 | 13 |
| b | Prod2 | 13 |
| b | Prod3 | 13 |
| b | Prod4 | 13 |
table1 becomes:
| Shop | Product | QuantityInStock |
| a | Prod1 | 13 |
| a | Prod2 | 0 | -- new
| a | Prod3 | 13 |
| a | Prod4 | 0 | -- new
| b | Prod1 | 0 | -- new
| b | Prod2 | 13 |
| b | Prod3 | 13 |
| b | Prod4 | 13 |
In this example, I want to represent every Shop/Product combination
every Shop {a,b} to have a row with every Product {Prod1, Prod2, Prod3, Prod4}
QuantityInStock=13 has no significance, I just wanted a placeholder number :)
Use a calendar table cross join approach:
SELECT s.Shop, p.Product, COALESCE(t1.QuantityInStock, 0) AS QuantityInStock
FROM (SELECT DISTINCT Shop FROM table1) s
CROSS JOIN (SELECT DISTINCT Product FROM table1) p
LEFT JOIN table1 t1
ON t1.Shop = s.Shop AND
t1.Product = p.Product
ORDER BY
s.Shop,
p.Product;
The idea here is to generate an intermediate table containing of all shop/product combinations via a cross join. Then, we left join this to table1. Any shop/product combinations which do not have a match in the actual table are assigned a zero stock quantity.
I have three main tables meetings, persons, hobbies with two relational tables.
Table meetings
+---------------+
| id | subject |
+----+----------+
| 1 | Kickoff |
| 2 | Relaunch |
| 3 | Party |
+----+----------+
Table persons
+------------+
| id | name |
+----+-------+
| 1 | John |
| 2 | Anna |
| 3 | Linda |
+----+-------+
Table hobbies
+---------------+
| id | name |
+----+----------+
| 1 | Soccer |
| 2 | Tennis |
| 3 | Swimming |
+----+----------+
Relation Table meeting_person
+-----------------+-----------+
| id | meeting_id | person_id |
+----+------------+-----------+
| 1 | 1 | 1 |
| 2 | 1 | 2 |
| 3 | 1 | 3 |
| 4 | 2 | 1 |
| 5 | 2 | 2 |
| 6 | 3 | 1 |
+----+------------+-----------+
Relation Table person_hobby
+----------------+----------+
| id | person_id | hobby_id |
+----+-----------+----------+
| 1 | 1 | 1 |
| 2 | 1 | 2 |
| 3 | 1 | 3 |
| 4 | 2 | 1 |
| 5 | 2 | 2 |
| 6 | 3 | 1 |
+----+-----------+----------+
Now I want to to find the common hobbies of all person attending each meeting.
So the desired result would be:
+------------+-----------------+------------------------+
| meeting_id | persons | common_hobbies |
| | (Aggregated) | (Aggregated) |
+------------+-----------------+------------------------+
| 1 | John,Anna,Linda | Soccer |
| 2 | John,Anna | Soccer,Tennis |
| 3 | John | Soccer,Tennis,Swimming |
+------------+-----------------+------------------------+
My current work in progress is:
select
m.id as "meeting_id",
(
select string_agg(distinct p.name, ',')
from meeting_person mp
inner join persons p on mp.person_id = p.id
where m.id = mp.meeting_id
) as "persons",
string_agg(distinct h2.name , ',') as "common_hobbies"
from meetings m
inner join meeting_person mp2 on m.id = mp2.meeting_id
inner join persons p2 on mp2.person_id = p2.id
inner join person_hobby ph2 on p2.id = ph2.person_id
inner join hobbies h2 on ph2.hobby_id = h2.id
group by m.id
But this query lists not the common_hobbies but all hobbies which are at least once mentioned.
+------------+-----------------+------------------------+
| meeting_id | persons | common_hobbies |
+------------+-----------------+------------------------+
| 1 | John,Anna,Linda | Soccer,Tennis,Swimming |
| 2 | John,Anna | Soccer,Tennis,Swimming |
| 3 | John | Soccer,Tennis,Swimming |
+------------+-----------------+------------------------+
Does anyone have any hints for me, on how I could solve this problem?
Cheers
This problem can be solved by implement custom aggregation function (found it here):
create or replace function array_intersect(anyarray, anyarray)
returns anyarray language sql
as $$
select
case
when $1 is null then $2
when $2 is null then $1
else
array(
select unnest($1)
intersect
select unnest($2))
end;
$$;
create aggregate array_intersect_agg (anyarray)
(
sfunc = array_intersect,
stype = anyarray
);
So, the solution can be next:
select
meeting_id,
array_agg(ph.name) persons,
array_intersect_agg(hobby) common_hobbies
from meeting_person mp
join (
select p.id, p.name, array_agg(h.name) hobby
from person_hobby ph
join persons p on ph.person_id = p.id
join hobbies h on h.id = ph.hobby_id
group by p.id, p.name
) ph on ph.id = mp.person_id
group by meeting_id;
Look the example fiddle
Result:
meeting_id | persons | common_hobbies
-----------+-----------------------+--------------------------
1 | {John,Anna,Linda} | {Soccer}
3 | {John} | {Soccer,Tennis,Swimming}
2 | {John,Anna} | {Soccer,Tennis}
I have a table as such (tbl):
+----+------+-----+
| pk | attr | val |
+----+------+-----+
| 0 | ohif | 4 |
| 1 | foha | 56 |
| 2 | slns | 2 |
| 3 | faso | 11 |
+----+------+-----+
And another table in n-to-1 relationship with tbl (tbl2):
+----+-----+
| pk | rel |
+----+-----+
| 0 | 0 |
| 1 | 1 |
| 2 | 0 |
| 3 | 2 |
| 4 | 2 |
| 5 | 3 |
| 6 | 1 |
| 7 | 2 |
+----+-----+
(tbl2.rel -> tbl.pk.)
I would like to select only the rows from tbl which are in relationship with at least n rows from tbl2.
I.e., for n = 2, I want this table:
+----+------+-----+
| pk | attr | val |
+----+------+-----+
| 0 | ohif | 4 |
| 1 | foha | 56 |
| 2 | slns | 2 |
+----+------+-----+
This is the solution I came up with:
SELECT DISTINCT ON (tbl.pk) tbl.*
FROM (
SELECT tbl.pk
FROM tbl
RIGHT OUTER JOIN tbl2 ON tbl2.rel = tbl.pk
GROUP BY tbl.pk
HAVING COUNT(tbl2.*) >= 2 -- n
) AS tbl_candidates
LEFT OUTER JOIN tbl ON tbl_candidates.pk = tbl.pk
Can it be done without selecting the candidates with a subquery and re-joining the table with itself?
I'm on Postgres 10. A standard SQL solution would be better, but a Postgres solution is acceptable.
OK, just join once, as below:
select
t1.pk,
t1.attr,
t1.val
from
tbl t1
join
tbl2 t2 on t1.pk = t2.rel
group by
t1.pk,
t1.attr,
t1.val
having(count(1)>=2) order by t1.pk;
pk | attr | val
----+------+-----
0 | ohif | 4
1 | foha | 56
2 | slns | 2
(3 rows)
Or just join once and use CTE(with clause), as below:
with tmp as (
select rel from tbl2 group by rel having(count(1)>=2)
)
select b.* from tmp t join tbl b on t.rel = b.pk order by b.pk;
pk | attr | val
----+------+-----
0 | ohif | 4
1 | foha | 56
2 | slns | 2
(3 rows)
Is the SQL clearer?
I have this table in my database:
| id | desc |
|-------------|
| 1 | A |
| 2 | B |
| NULL | C |
| 3 | D |
| NULL | D |
| NULL | E |
| 4 | F |
---------------
And I want to transform this table into a table that replace nulls by consecutive negative ids:
| id | desc |
|-------------|
| 1 | A |
| 2 | B |
| -1 | C |
| 3 | D |
| -2 | D |
| -3 | E |
| 4 | F |
---------------
Anyone knows how can I do this in hive?
Below approach works
select coalesce(id,concat('-',ROW_NUMBER() OVER (partition by id))) as id,desc from database_name.table_name;
I have one table where I dump all records from different sources (x, y, z) like below
+----+------+--------+
| id | source |
+----+--------+
| 1 | x |
| 2 | y |
| 3 | x |
| 4 | x |
| 5 | y |
| 6 | z |
| 7 | z |
| 8 | x |
| 9 | z |
| 10 | z |
+----+--------+
Then I have one mapping table where I map values between sources based on my usecase like below
+----+-----------+
| id | mapped_id |
+----+-----------+
| 1 | 2 |
| 1 | 9 |
| 3 | 7 |
| 4 | 10 |
| 5 | 1 |
+----+-----------+
I want merged results where I can see only unique results like
+-----+------------+
| id | mapped_ids |
+-----+------------+
| 1 | 2,9,5 |
| 3 | 7 |
| 4 | 10 |
| 6 | null |
| 8 | null |
+-----+------------+
I am trying different options but could not figure this out, is there way I can write joins to do this. I have to use the mapping table where associations are stored and identify unique records along with records which are not mapped anywhere.
My understanding is, you want to see all dump_table IDs that do not appear in the mapping_id column and then aggregate the mapped_ids for those that are left:
select d1.id,
array_agg(m1.mapped_id order by m1.mapped_id) filter (where m1.mapped_id is not null) as mapped_ids
from dump_table d1
left join mapping_table m1 using (id)
where not exists (select *
from mapping_table m2
where m2.mapped_id = d1.id)
group by d1.id;
Online example: https://rextester.com/JQZ17650
Try something like this:
SELECT id, name, ARRAY_AGG(mapped_id) AS mapped_ids
FROM table1 AS t1
LEFT JOIN table2 AS t2 USING (id)
GROUP BY id, name