I've got mytable1 with row_number integer and list_of_ids int[] column
mytable2 with id integer and company text columns
Example entry for mytable1
1 | {633681,1278392,2320888,2200426}
2 | {2443842,2959599,3703823,3330376,915750,941736}
Example entry for mytable2
633681 | apple
1278392 | charmander
2320888 | apple
2200426 | null
2443842 | batman
I need to feed back values from mytable2 into mytable1. This way the expected output would be
1 | {633681,1278392,2320888,2200426} | 2 apple, 1 charmander, 1 null
2 | {2443842,2959599,3703823,3330376,915750,941736} | 1 batman etc...
You need to unnest the lists of ids, join mytable2 using unnested ids and finally aggregate back the data to get a single row for a row_number.
select
row_number,
list_of_ids,
string_agg(format('%s %s', count, company), ', ' order by count desc, company)
from (
select
row_number,
list_of_ids,
coalesce(company, '<null>') as company,
count(*)
from (
select row_number, list_of_ids, unnest(list_of_ids) as id
from mytable1
) t1
join mytable2 t2 using(id)
group by 1, 2, 3
) s
group by 1, 2
Db<>fiddle.
Related
Here's what I'm trying to do. Let's say I have this table t:
key_id | id | record_date | other_cols
1 | 18 | 2011-04-03 | x
2 | 18 | 2012-05-19 | y
3 | 18 | 2012-08-09 | z
4 | 19 | 2009-06-01 | a
5 | 19 | 2011-04-03 | b
6 | 19 | 2011-10-25 | c
7 | 19 | 2012-08-09 | d
For each id, I want to select the row containing the minimum record_date. So I'd get:
key_id | id | record_date | other_cols
1 | 18 | 2011-04-03 | x
4 | 19 | 2009-06-01 | a
The only solutions I've seen to this problem assume that all record_date entries are distinct, but that is not this case in my data. Using a subquery and an inner join with two conditions would give me duplicate rows for some ids, which I don't want:
key_id | id | record_date | other_cols
1 | 18 | 2011-04-03 | x
5 | 19 | 2011-04-03 | b
4 | 19 | 2009-06-01 | a
How about something like:
SELECT mt.*
FROM MyTable mt INNER JOIN
(
SELECT id, MIN(record_date) AS MinDate
FROM MyTable
GROUP BY id
) t ON mt.id = t.id AND mt.record_date = t.MinDate
This gets the minimum date per ID, and then gets the values based on those values. The only time you would have duplicates is if there are duplicate minimum record_dates for the same ID.
I could get to your expected result just by doing this in mysql:
SELECT id, min(record_date), other_cols
FROM mytable
GROUP BY id
Does this work for you?
To get the cheapest product in each category, you use the MIN() function in a correlated subquery as follows:
SELECT categoryid,
productid,
productName,
unitprice
FROM products a WHERE unitprice = (
SELECT MIN(unitprice)
FROM products b
WHERE b.categoryid = a.categoryid)
The outer query scans all rows in the products table and returns the products that have unit prices match with the lowest price in each category returned by the correlated subquery.
I would like to add to some of the other answers here, if you don't need the first item but say the second number for example you can use rownumber in a subquery and base your result set off of that.
SELECT * FROM
(
SELECT
ROW_NUM() OVER (PARTITION BY Id ORDER BY record_date, other_cols) as rownum,
*
FROM products P
) INNER
WHERE rownum = 2
This also allows you to order off multiple columns in the subquery which may help if two record_dates have identical values. You can also partition off of multiple columns if needed by delimiting them with a comma
This does it simply:
select t2.id,t2.record_date,t2.other_cols
from (select ROW_NUMBER() over(partition by id order by record_date)as rownum,id,record_date,other_cols from MyTable)t2
where t2.rownum = 1
If record_date has no duplicates within a group:
think of it as of filtering. Simpliy get (WHERE) one (MIN(record_date)) row from the current group:
SELECT * FROM t t1 WHERE record_date = (
select MIN(record_date)
from t t2 where t2.group_id = t1.group_id)
If there could be 2+ min record_date within a group:
filter out non-min rows (see above)
then (AND) pick only one from the 2+ min record_date rows, within the given group_id. E.g. pick the one with the min unique key:
AND key_id = (select MIN(key_id)
from t t3 where t3.record_date = t1.record_date
and t3.group_id = t1.group_id)
so
key_id | group_id | record_date | other_cols
1 | 18 | 2011-04-03 | x
4 | 19 | 2009-06-01 | a
8 | 19 | 2009-06-01 | e
will select key_ids: #1 and #4
SELECT p.* FROM tbl p
INNER JOIN(
SELECT t.id, MIN(record_date) AS MinDate
FROM tbl t
GROUP BY t.id
) t ON p.id = t.id AND p.record_date = t.MinDate
GROUP BY p.id
This code eliminates duplicate record_date in case there are same ids with same record_date.
If you want duplicates, remove the last line GROUP BY p.id.
This a old question, but this can useful for someone
In my case i can't using a sub query because i have a big query and i need using min() on my result, if i use sub query the db need reexecute my big query. i'm using Mysql
select t.*
from (select m.*, #g := 0
from MyTable m --here i have a big query
order by id, record_date) t
where (1 = case when #g = 0 or #g <> id then 1 else 0 end )
and (#g := id) IS NOT NULL
Basically I ordered the result and then put a variable in order to get only the first record in each group.
The below query takes the first date for each work order (in a table of showing all status changes):
SELECT
WORKORDERNUM,
MIN(DATE)
FROM
WORKORDERS
WHERE
DATE >= to_date('2015-01-01','YYYY-MM-DD')
GROUP BY
WORKORDERNUM
select
department,
min_salary,
(select s1.last_name from staff s1 where s1.salary=s3.min_salary ) lastname
from
(select department, min (salary) min_salary from staff s2 group by s2.department) s3
I have two tables. Table 1 contains content_id's that meets a certain criteria. Table 2 contains the content_id, content, and related user_id. They share a content_id field. I would like to produce a list of who has the most entries in Table 1.
Example
Table 1
content_id {1, 2, 3, 4, 5, 6}
Table 2
content_id|user_id { 1|2 , 2|3 , 3|2 , 4|1 , 5|3, 6|2 }
Desired results
user 2 has 3 entries
user 3 has 2 entries
user 1 has 1 entry
I imagine I need to INNER JOIN the two tables by content_id and then somehow use COUNT or similar?
Assuming you want to "filter" by the content of t1, one possibility is:
create table t1 (content_id int);
insert into t1 values (2, 3, 4, 5, 6);
-- note I ommitted 1 so not all values are present
create table t2 (content_id int, user_id int);
insert into t2 (values (1,2), (2,3) , (3,2) , (4,1) , (5,3), (6,2) );
select user_id, count(*) from t2 where exists (select 1 from t1 where content_id=t2.content_id) group by user_id;
-- output:
user_id | count
---------+-------
3 | 2
2 | 2
1 | 1
(3 rows)
-- OR
select user_id, count(*) from (select * from t2 except select 1 as user_id, content_id from t1) AS filtered group by user_id;
-- output:
user_id | count
---------+-------
3 | 2
2 | 2
1 | 1
(3 rows)
But other answers are already doing this too.
Here is the code snippet that will produce your desired result:
Select
tb2.user_id,count(tb2.content_id)
From table1 tb1
Inner join table2 tb2
on tb1.content_id=tb2.content_id
group by tb2.user_id
Are you looking for a simple group by?
select user_id, count(*)
from table2
group by user_id;
EDIT:
If you want to restrict the content ids, I recommend exists:
select t2.user_id, count(*)
from table2 t2
where exists (select 1
from table1 t1
where t1.content_id = t2.content_id
)
group by user_id;
I hope this what you looking for and help you
select user_id, count(`content_id`) from table2 t2
where exists (select t1.content_id from table1 t1
where t1.content_id=t2.content_id)
group by user_id order BY count(`content_id`) DESC;
+---------+---------------------+
| user_id | count(`content_id`) |
+---------+---------------------+
| 2 | 3 |
| 3 | 2 |
| 1 | 1 |
+---------+---------------------+
How to do selection to get JSON array in one cell when doing INNER JOIN when there are more than 1 values to join?
ex Tables:
T1:
id | name
1 Tom
2 Dom
T2:
user_id | product
1 Milk
2 Cookies
2 Banana
Naturally I do SELECT * FROM T1 INNER JOIN T2 ON T1.id = T2.user_id.
But then I get:
id | Name | product
1 Tom Milk
2 Dom Cookies
2 Dom Banana
But I want to get:
id | Name | product
1 Tom [{"product":"Milk}]
2 Dom [{"product":"Cookies"}, {"product":"Banana"}]
If I do something with agg functions, then I need to put everything else in GROUP BY, where I have at least 10 arguments. And whole query takes more than 5 minutes.
My T1 is around 4000 rows and T2 around 300 000 rows, each associated with some row in T1.
Is there a better way?
Using LATERAL you can solve it as given example below:
-- The query
SELECT *
FROM table1 t1,
LATERAL ( SELECT jsonb_agg(
jsonb_build_object( 'product', product )
)
FROM table2
WHERE user_id = t1.id
) t2( product );
-- Result
id | name | product
----+------+-------------------------------------------------
1 | Tom | [{"product": "Milk"}]
2 | Dom | [{"product": "Cookies"}, {"product": "Banana"}]
(2 rows)
-- Test data
CREATE TABLE IF NOT EXISTS table1 (
id int,
"name" text
);
INSERT INTO table1
VALUES ( 1, 'Tom' ),
( 2, 'Dom' );
CREATE TABLE IF NOT EXISTS table2 (
user_id int,
product text
);
INSERT INTO table2
VALUES ( 1, 'Milk' ),
( 2, 'Cookies' ),
( 2, 'Banana' );
I have a problems this mornig , I have tried many solutions and nothing gave me the expected result.
I have a table that looks like this :
+----+----------+-------+
| ID | COL2 | DATE |
+----+----------+-------+
| 1 | 1 | 2001 |
| 1 | 2 | 2002 |
| 1 | 3 | 2003 |
| 1 | 4 | 2004 |
| 2 | 1 | 2001 |
| 2 | 2 | 2002 |
| 2 | 3 | 2003 |
| 2 | 4 | 2004 |
+----+----------+-------+
And I have a query that returns a result like this :
I have the unique ID and for this ID I want to take the last date of the ID
+----+----------+-------+
| ID | COL2 | DATE |
+----+----------+-------+
| 1 | 4 | 2004 |
| 2 | 4 | 2004 |
+----+----------+-------+
But I don't have any idea how I can do that.
I tried Join , CROSS APPLY ..
If you have some idea ,
Thank you
Clement FAYARD
declare #t table (ID INT,Col2 INT,Date INT)
insert into #t(ID,Col2,Date)values (1,1,2001)
insert into #t(ID,Col2,Date)values (1,2,2001)
insert into #t(ID,Col2,Date)values (1,3,2001)
insert into #t(ID,Col2,Date)values (1,4,2001)
insert into #t(ID,Col2,Date)values (2,1,2002)
insert into #t(ID,Col2,Date)values (2,2,2002)
insert into #t(ID,Col2,Date)values (2,3,2002)
insert into #t(ID,Col2,Date)values (2,4,2002)
;with cte as(
select
*,
rn = row_number() over(partition by ID order by Col2 desc)
from #t
)
select
ID,
Col2,
Date
from cte
where
rn = 1
SELECT ID,MAX(Col2),MAX(Date) FROM tableName GROUP BY ID
If col2 and date allways the highest value in combination than you can try
SELECT ID, MAX(COL2), MAX(DATE)
FROM Table1
GROUP BY ID
But it is not realy good.
The alternative is a subquery with:
SELECT yourtable.ID, sub1.COL2, sub1.DATE
FROM yourtable
INNER JOIN -- try with CROSS APPLY for performance AND without ON 1=1
(SELECT TOP 1 COL2, DATE
FROM yourtable sub2
WHERE sub2.ID = topquery.ID
ORDER BY COL2, DATE) sub1 ON 1=1
You didn't tell what's the name of your table so I'll assume below it is tbl:
SELECT m.ID, m.COL2, m.DATE
FROM tbl m
LEFT JOIN tbl o ON m.ID = o.ID AND m.DATE < o.DATE
WHERE o.DATE is NULL
ORDER BY m.ID ASC
Explanation:
The query left joins the table tbl aliased as m (for "max") against itself (alias o, for "others") using the column ID; the condition m.DATE < o.DATE will combine all the rows from m with rows from o having a greater value in DATE. The row having the maximum value of DATE for a given value of ID from m has no pair in o (there is no value greater than the maximum value). Because of the LEFT JOIN this row will be combined with a row of NULLs. The WHERE clause selects only these rows that have NULL for o.DATE (i.e. they have the maximum value of m.DATE).
Check the SQL Antipatterns: Avoiding the Pitfalls of Database Programming book for other SQL tips.
In order to do this you MUST exclude COL2 Your query should look like this
SELECT ID, MAX(DATE)
FROM table_name
GROUP BY ID
The above query produces the Maximum Date for each ID.
Having COL2 with that query does not makes sense, unless you want the maximum date for each ID and COL2
In that case you can run:
SELECT ID, COL2, MAX(DATE)
GROUP BY ID, COL2;
When you use aggregation functions(like max()), you must always group by all the other columns you have in the select statement.
I think you are facing this problem because you have some fundemental flaws with the design of the table. Usually ID should be a Primary Key (Which is Unique). In this table you have repeated IDs. I do not understand the business logic behind the table but it seems to have some flaws to me.
Here's what I'm trying to do. Let's say I have this table t:
key_id | id | record_date | other_cols
1 | 18 | 2011-04-03 | x
2 | 18 | 2012-05-19 | y
3 | 18 | 2012-08-09 | z
4 | 19 | 2009-06-01 | a
5 | 19 | 2011-04-03 | b
6 | 19 | 2011-10-25 | c
7 | 19 | 2012-08-09 | d
For each id, I want to select the row containing the minimum record_date. So I'd get:
key_id | id | record_date | other_cols
1 | 18 | 2011-04-03 | x
4 | 19 | 2009-06-01 | a
The only solutions I've seen to this problem assume that all record_date entries are distinct, but that is not this case in my data. Using a subquery and an inner join with two conditions would give me duplicate rows for some ids, which I don't want:
key_id | id | record_date | other_cols
1 | 18 | 2011-04-03 | x
5 | 19 | 2011-04-03 | b
4 | 19 | 2009-06-01 | a
How about something like:
SELECT mt.*
FROM MyTable mt INNER JOIN
(
SELECT id, MIN(record_date) AS MinDate
FROM MyTable
GROUP BY id
) t ON mt.id = t.id AND mt.record_date = t.MinDate
This gets the minimum date per ID, and then gets the values based on those values. The only time you would have duplicates is if there are duplicate minimum record_dates for the same ID.
I could get to your expected result just by doing this in mysql:
SELECT id, min(record_date), other_cols
FROM mytable
GROUP BY id
Does this work for you?
To get the cheapest product in each category, you use the MIN() function in a correlated subquery as follows:
SELECT categoryid,
productid,
productName,
unitprice
FROM products a WHERE unitprice = (
SELECT MIN(unitprice)
FROM products b
WHERE b.categoryid = a.categoryid)
The outer query scans all rows in the products table and returns the products that have unit prices match with the lowest price in each category returned by the correlated subquery.
I would like to add to some of the other answers here, if you don't need the first item but say the second number for example you can use rownumber in a subquery and base your result set off of that.
SELECT * FROM
(
SELECT
ROW_NUM() OVER (PARTITION BY Id ORDER BY record_date, other_cols) as rownum,
*
FROM products P
) INNER
WHERE rownum = 2
This also allows you to order off multiple columns in the subquery which may help if two record_dates have identical values. You can also partition off of multiple columns if needed by delimiting them with a comma
This does it simply:
select t2.id,t2.record_date,t2.other_cols
from (select ROW_NUMBER() over(partition by id order by record_date)as rownum,id,record_date,other_cols from MyTable)t2
where t2.rownum = 1
If record_date has no duplicates within a group:
think of it as of filtering. Simpliy get (WHERE) one (MIN(record_date)) row from the current group:
SELECT * FROM t t1 WHERE record_date = (
select MIN(record_date)
from t t2 where t2.group_id = t1.group_id)
If there could be 2+ min record_date within a group:
filter out non-min rows (see above)
then (AND) pick only one from the 2+ min record_date rows, within the given group_id. E.g. pick the one with the min unique key:
AND key_id = (select MIN(key_id)
from t t3 where t3.record_date = t1.record_date
and t3.group_id = t1.group_id)
so
key_id | group_id | record_date | other_cols
1 | 18 | 2011-04-03 | x
4 | 19 | 2009-06-01 | a
8 | 19 | 2009-06-01 | e
will select key_ids: #1 and #4
SELECT p.* FROM tbl p
INNER JOIN(
SELECT t.id, MIN(record_date) AS MinDate
FROM tbl t
GROUP BY t.id
) t ON p.id = t.id AND p.record_date = t.MinDate
GROUP BY p.id
This code eliminates duplicate record_date in case there are same ids with same record_date.
If you want duplicates, remove the last line GROUP BY p.id.
This a old question, but this can useful for someone
In my case i can't using a sub query because i have a big query and i need using min() on my result, if i use sub query the db need reexecute my big query. i'm using Mysql
select t.*
from (select m.*, #g := 0
from MyTable m --here i have a big query
order by id, record_date) t
where (1 = case when #g = 0 or #g <> id then 1 else 0 end )
and (#g := id) IS NOT NULL
Basically I ordered the result and then put a variable in order to get only the first record in each group.
The below query takes the first date for each work order (in a table of showing all status changes):
SELECT
WORKORDERNUM,
MIN(DATE)
FROM
WORKORDERS
WHERE
DATE >= to_date('2015-01-01','YYYY-MM-DD')
GROUP BY
WORKORDERNUM
select
department,
min_salary,
(select s1.last_name from staff s1 where s1.salary=s3.min_salary ) lastname
from
(select department, min (salary) min_salary from staff s2 group by s2.department) s3