I have three different tables that look like that:
Table 1
| id | city|
|----|-----|
| 1 | A |
| 1 | B |
| 2 | C |
Table 2
| id | city|
|----|-----|
| 2 | B |
| 1 | B |
| 3 | C |
Table 3
| id | city|
|----|-----|
| 1 | A |
| 1 | B |
| 2 | A |
I need to create one column for each table, and the dummies values if it's present.
| id | city| is_tbl_1 | is_tbl_2 | is_tbl_3 |
|----|-----|-----------|-------------|------------|
| 1 | A | 1 | 0 | 1 |
| 1 | B | 1 | 1 | 1 |
| 2 | A | 0 | 0 | 1 |
| 2 | C | 1 | 0 | 0 |
| 2 | B | 0 | 1 | 0 |
| 3 | C | 0 | 1 | 0 |
I have tried to add the columns is_tbl# myself on three different selects, UNION all the three tables and group, but it looks ugly, is there a better way to do it?
You can outer-join the 3 tables on id and city, then group by the id and city, and finally count the number of non-null values of the city columns :
SELECT
COALESCE (t1.id, t2.id, t3.id) AS id
, COALESCE (t1.city, t2.city, t3.city) AS city
, count(*) FILTER (WHERE t1.city IS NOT NULL) AS is_tbl_1
, count(*) FILTER (WHERE t2.city IS NOT NULL) AS is_tbl_2
, count(*) FILTER (WHERE t3.city IS NOT NULL) AS is_tbl_3
FROM
t1 AS t1
FULL OUTER JOIN
t2 AS t2 ON t1.id = t2.id AND t1.city = t2.city
FULL OUTER JOIN
t3 AS t3 ON t1.id = t3.id AND t1.city = t3.city
GROUP BY
1,2
ORDER BY
1,2
Related
Having two tables (table1, table2) with the same column names (generation, parent), the desired output would be the combination of all columns of both tables. Thereby the rows of table2 should join table1 so that the rows of table2 are matching those of table1 on generation column. The parent number should be ordered ascending for the entries in table1 as well as in table2. The number of rows of the query results should be equal of those of table1.
Given the following tables
table1:
| generation | parent |
|:----------:|:------:|
| 0 | 1 |
| 0 | 2 |
| 0 | 3 |
| 1 | 3 |
| 1 | 2 |
| 1 | 1 |
| 2 | 2 |
| 2 | 1 |
| 2 | 3 |
table2:
| generation | parent |
|:----------:|:------:|
| 1 | 3 |
| 1 | 1 |
| 1 | 3 |
| 2 | 1 |
| 2 | 2 |
| 2 | 3 |
The following queries are thought for creating and populating two sample tables as shown above:
create table table1(generation integer, parent integer);
insert into table1 (generation, parent) values(0,1),(0,2),(0,3),(1,3),(1,2),(1,1),(2,2),(2,1),(2,3);
create table table2(generation integer, parent integer);
insert into table2 (generation, parent) values(1,3),(1,1),(1,3),(2,1),(2,2),(2,3);
the imagined query should lead to the following desired result:
| table1_generation | table1_parent | table2_generation | table2_parent |
|:-----------------:|:-------------:|:-----------------:|:-------------:|
| 0 | 1 | | |
| 0 | 2 | | |
| 0 | 3 | | |
| 1 | 1 | 1 | 1 |
| 1 | 2 | 1 | 3 |
| 1 | 3 | 1 | 3 |
| 2 | 1 | 2 | 1 |
| 2 | 2 | 2 | 2 |
| 2 | 3 | 2 | 3 |
Current query looks as follows:
with
p as (
select
generation,
parent
from
table1
order by
generation,
parent
), o as(
select
generation,
parent
from
table2
order by
generation,
parent
)
select
p.generation as table1_generation,
p.parent as table1_parent,
o.generation as table2_generation,
o.parent as table2_parent
from
p
left join o on
o.generation=p.generation;
Which leads to the following result:
| table1_generation | table1_parent | table2_generation | table2_parent |
|:-----------------:|:-------------:|:-----------------:|:-------------:|
| 0 | 1 | | |
| 0 | 2 | | |
| 0 | 3 | | |
| 1 | 1 | 1 | 1 |
| 1 | 1 | 1 | 3 |
| 1 | 1 | 1 | 3 |
| 1 | 2 | 1 | 1 |
| 1 | 2 | 1 | 3 |
| 1 | 2 | 1 | 3 |
| 1 | 3 | 1 | 1 |
| 1 | 3 | 1 | 3 |
| 1 | 3 | 1 | 3 |
| 2 | 1 | 2 | 1 |
| 2 | 1 | 2 | 2 |
| 2 | 1 | 2 | 3 |
| 2 | 2 | 2 | 1 |
| 2 | 2 | 2 | 2 |
| 2 | 2 | 2 | 3 |
| 2 | 3 | 2 | 1 |
| 2 | 3 | 2 | 2 |
| 2 | 3 | 2 | 3 |
This link led to the conclusion, that any join command might not what is necessary here ... But union does only append rows... so for me it is absolutely unclear, how the desired result can be achieved o.O
Any help is highly appreciated. Thanks in advance!
The main misunderstanding on this question arose from the fact that you mentioned join, which is a very precisely mathematically defined concept based on the Cartesian product and can be applied to any two sets. So the current output is clear.
But as you wrote in the title, you want to put two tables side by side. You take advantage of the fact that they have the same number of rows (triples).
This select returns the output you want.
I made artificial join columns, row_number() OVER (order by generation, parent) as rnum, and moved the second table using the addition of three. I hope this helps you:
with
p as (
select
row_number() OVER (order by generation, parent) as rnum,
generation,
parent
from
table1
order by
generation,
parent
), o as(
select
row_number() OVER (order by generation, parent) as rnum,
generation,
parent
from
table2
order by
generation,
parent
)
select
p.generation as table1_generation,
p.parent as table1_parent,
o.generation as table2_generation,
o.parent as table2_parent
from
p
left join o on
o.rnum+3=p.rnum
order by 1,2,3,4;
Output:
table1_generation
table1_parent
table2_generation
table2_parent
0
1
(null)
(null)
0
2
(null)
(null)
0
3
(null)
(null)
1
1
1
1
1
2
1
3
1
3
1
3
2
1
2
1
2
2
2
2
2
3
2
3
I'm fairly new to Postgresql and my problem can be simplified to the following:
Suppose that I have 2 tables:
Table A:
id | join_value | filter_data1 | filter_data2
---------------------------------------------
1 | 1 | "Yes" | 1
2 | 1 | "Yes" | 3
3 | 2 | "No" | 0
Table B:
id | join_value | filter_data1 | filter_data2 | date
---------------------------------------------------------
1 | 3 | "Yes" | 0 | 1/3/2021
2 | 1 | "Yes" | 17 | 1/3/2021
3 | 1 | "No" | -1 | 1/2/2021
4 | 1 | "Yes" | 32 | 1/2/2021
5 | 1 | "Yes" | 40 | 1/3/2021
I would like to filter these tables on the filter data and then join them on the join value. The catch is that I would then like to only grab the values that have a date == MAX(date). Here is an example of a query that I have attempted.
SELECT * FROM
(SELECT * FROM A
WHERE filter_data1 = "Yes"
AND filter_data2 > 2)
AS a_tab
JOIN
(SELECT * FROM B
WHERE filter_data1 = "Yes"
AND filter_data2 > 16)
AS b_tab
ON a_tab.join_value = b_tab.join_value;
This would give me the following table:
id | join_value | filter_data1 | filter_data2 | id | filter_data1 | filter_data2 | date
------------------------------------------------------------------------------------------
2 | 1 | "Yes" | 3 | 2 | "Yes" | 17 | 1/3/2021
2 | 1 | "Yes" | 3 | 4 | "Yes" | 32 | 1/2/2021
2 | 1 | "Yes" | 3 | 5 | "Yes" | 40 | 1/3/2021
But the problem is, I would like to also do a 'WHERE date = MAX(date)'
The resulting table would be this:
id | join_value | filter_data1 | filter_data2 | id | filter_data1 | filter_data2 | date
------------------------------------------------------------------------------------------
2 | 1 | "Yes" | 3 | 2 | "Yes" | 17 | 1/3/2021
2 | 1 | "Yes" | 3 | 5 | "Yes" | 40 | 1/3/2021
Does anyone have any ideas how to accomplish this?
At first, let me give you a hint, how you can write your existing select query in a way that it is better readable:
SELECT
a.*, b.*
FROM a
INNER JOIN b ON b.join_value = a.join_value
WHERE a.filter_data1 = 'YES' AND a.filter_data2 > 2
AND b.filter_data1 = 'YES' AND b.filter_data2 > 16
Now I am going to add another column to this query, that holds the maximum value of the date column of the output. Therefore, we can use a WINDOW FUNCTION:
SELECT
a.*, b.*, MAX(b.date) OVER ()
FROM a
INNER JOIN b ON b.join_value = a.join_value
WHERE a.filter_data1 = 'YES' AND a.filter_data2 > 2
AND b.filter_data1 = 'YES' AND b.filter_data2 > 16
As the WINDOW FUNCTION is the part of the query, that is computed in the last step, we cannot add a condition here. So we use this query as a subquery and add the condition to the top-level-query:
SELECT
*
FROM (
SELECT
a.*, b.*, MAX(b.date) OVER () AS max_date
FROM a
INNER JOIN b ON b.join_value = a.join_value
WHERE a.filter_data1 = 'YES' AND a.filter_data2 > 2
AND b.filter_data1 = 'YES' AND b.filter_data2 > 16
) t
WHERE t.date = t.max_date
This should give you the required results.
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 a table which contains Null values. I need to replace them with a previous non-Null value.
This is an example of data which I have:
date | category | start_period | period_number |
------------------------------------------------------
2018-01-01 | A | 1 | 1 |
2018-01-02 | A | 0 | Null |
2018-01-03 | A | 0 | Null |
2018-01-04 | A | 0 | Null |
2018-01-05 | B | 1 | 2 |
2018-01-06 | B | 0 | Null |
2018-01-07 | B | 0 | Null |
2018-01-08 | A | 1 | 3 |
2018-01-09 | A | 0 | Null |
2018-01-10 | A | 0 | Null |
The result should look like this:
date | category | start_period | period_number |
------------------------------------------------------
2018-01-01 | A | 1 | 1 |
2018-01-02 | A | 0 | 1 |
2018-01-03 | A | 0 | 1 |
2018-01-04 | A | 0 | 1 |
2018-01-05 | B | 1 | 2 |
2018-01-06 | B | 0 | 2 |
2018-01-07 | B | 0 | 2 |
2018-01-08 | A | 1 | 3 |
2018-01-09 | A | 0 | 3 |
2018-01-10 | A | 0 | 3 |
I tried the following query, but in this case, only the first Null value will be replaced.
select
date,
category,
start_period,
case
when period_number isnull then lag(period_number) over()
else period_number
end as period_number
from period_table;
Also, I tried to use first_value() window function, but I don't know how to set up the correct window.
Any help is highly appreciated.
You can join table with itself and get desired value. Assuming your date column is the primary key or unique.
update your_table upd set period_number = tbl.period_number
from
(
select b.date, max(b2.date) as d2 from your_table b
inner join d_batch_tab b2 on b2.date< b.date and b2.period_number is not null
group by b.date
)t
inner join your_table tbl on tbl.date = t.d2
where t.date= upd.date
If you don't need to update the table but only a select statement then
select yt.date, yt.category, yt.start_period, tbl.period_number
from your_table yt
inner join
(
select b.date, max(b2.date) as d2 from your_table b
inner join d_batch_tab b2 on b2.date< b.date and b2.period_number is not null
group by b.date
)t on yt.date = t.date
inner join your_table tbl on tbl.date = t.d2
If you replace your case statement with:
(
select
_.period_number
from
period_table as _
where
_.period_number is not null
and _.category = period_table.category
and _.date <= period_table.date
order by
_.date desc
limit 1
) as period_number
Then it should have the intended effect. It's nowhere near as elegant as a window function but I don't think window functions are quite flexible enough for your specific use case here (Or at least, if they are, I don't know how to flex them that much)
Examples of windows function and frame clause:
select
date,category,score
,FIRST_VALUE(score) OVER (
PARTITION BY category
ORDER BY date RANGE BETWEEN UNBOUNDED
PRECEDING AND CURRENT ROW
) as last_score
from testing.rec_test
order by date, category
select
date,category,score
,LAST_VALUE(score) OVER (
PARTITION BY category
ORDER BY date RANGE BETWEEN CURRENT ROW AND UNBOUNDED FOLLOWING
) as last_score
from testing.rec_test
order by date, category