I have a table that has 2 columns. One is a type column and the other is a value amount column. There are only 2 types/ I would like to select columns of this table into another table with 2 combined columns based on type and value. For example, the table may have order with 2 of the types in 2 rows. It would be inserted into the 2nd table as one row.
Example:
Table 1
| ID | OrderID | Type | Value |
|:-----|:--------:|:------------:|-------:|
| 1 | 300 | bike | 100 |
| 2 | 300 | skateboard | 150 |
| 3 | 700 | bike | 200 |
| 4 | 700 | skateboard | 50 |
| 5 | 800 | bike | 150 |
| 6 | 800 | skateboard | 100 _
What is the TSQL to have it inserted into the 2nd table with these values?
Table 2
| ID | OrderID | BikeValue | SkateboardValue |
|:----|:--------:|:----------:|-----------------:|
| 1 | 300 | 100 | 150 |
| 2 | 700 | 200 | 50 |
| 3 | 800 | 150 | 100 |
Just make it simple for yourself. Do two SQL statements. One to insert and another to update.
INSERT INTO Table2 (OrderID, BikeValue)
SELECT Table1.OrderID, Table1.Value
FROM Table1 (NOLOCK)
WHERE Table1.Type = 'bike'
UPDATE Table2 SET Table2.SkateboardValue = Table1.Value
FROM Table2
INNER JOIN Table1 ON Table1.OrderID = Table2.OrderID
WHERE Table1.Type = 'skateboard'
Related
I have a table for player stats like so:
player_id | game_id | rec | rec_yds | td | pas_att | pas_yds | ...
--------------------------------------------------------
1 | 3 | 1 | 5 | 0 | 3 | 20 |
2 | 3 | 0 | 8 | 1 | 7 | 20 |
3 | 3 | 3 | 9 | 0 | 0 | 0 |
4 | 3 | 5 | 15 | 0 | 0 | 0 |
I want to return the max values for every column in the table except player_id and game_id.
I know I can return the max of one single column by doing something like so:
SELECT MAX(rec) FROM stats
However, this table has almost 30 columns, so I would just be repeating the query below, for all 30 stats, just replacing the name of the stat.
SELECT MAX(rec) as rec FROM stats
This would get tedious real quick, and wont scale.
Is there any way to kind of loop over columns, get every column in the table and return the max value like so:
player_id | game_id | rec | rec_yds | td | pas_att | pas_yds | ...
--------------------------------------------------------
4 | 3 | 5 | 15 | 1 | 7 | 20 |
You can get the maximum of multiple columns in a single query:
SELECT
MAX(rec) AS rec_max,
MAX(rec_yds) AS rec_yds_max,
MAX(td) AS td_max,
MAX(pas_att) AS pas_att_max,
MAX(pas_yds) AS pas_yds_max
FROM stats
However, there is no way to dynamically get an arbitrary number of columns. You could dynamically build the query by loading all column names of the table, then apply conditions such as "except player_id and game_id", but that cannot be done within the query itself.
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 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
I need help with updating table from another table in Postgres Db.
Long story short we ended up with corrupted data in db, and now I need to update one table with values from another.
I have table with this data table wfc:
| step_id | command_id | commands_order |
|---------|------------|----------------|
| 1 | 1 | 0 |
| 1 | 2 | 1 |
| 1 | 3 | 2 |
| 1 | 4 | 3 |
| 1 | 1 | 0 |
| 2 | 2 | 0 |
| 2 | 3 | 1 |
| 2 | 3 | 1 |
| 2 | 4 | 3 |
and I want to update values in command_order column from another table, so I can have result like this:
| step_id | command_id | commands_order|
|---------|------------|---------------|
| 1 | 1 | 0 |
| 1 | 2 | 1 |
| 1 | 3 | 2 |
| 1 | 4 | 3 |
| 1 | 1 | 4 |
| 2 | 2 | 0 |
| 2 | 3 | 1 |
| 2 | 3 | 2 |
| 2 | 4 | 3 |
It was looking like easy task, but problem is to update rows for same command_id, it is writing same value in commands_order
SQL that I tried is:
UPDATE wfc
SET commands_order = CAST(sq.input_step_id as INTEGER)
FROM (
SELECT wfp.step_id, wfp.input_command_id, wfp.input_step_id
from wfp
order by wfp.step_id, wfp.input_step_id
) AS sq
WHERE (wfc.step_id=sq.step_id AND wfc.command_id=CAST(sq.input_command_id as INTEGER));
SQL Fiddle http://sqlfiddle.com/#!15/4efff4/4
I am pretty stuck with this, please help.
Thanks in advance.
Assuming you are trying to number the rows in the order in which they were created, and as long as you understand that ctid will chnage on update and with VACCUUM FULL, you can do the following:
select step_id, command_id, rank - 1 as command_order
from (select step_id, command_id, ctid as wfc_ctid, rank() over
(partition by step_id order by ctid)
from wfc) as wfc_ordered;
This will give you the wfc table with the ordering that you want. If you do update the original table, the ctids will change, so it's probably safer to create a copy of the table with the above query.
I have this table named Samples. The Date column values are just symbolic date values.
+----+------------+-------+------+
| Id | Product_Id | Price | Date |
+----+------------+-------+------+
| 1 | 1 | 100 | 1 |
| 2 | 2 | 100 | 2 |
| 3 | 3 | 100 | 3 |
| 4 | 1 | 100 | 4 |
| 5 | 2 | 100 | 5 |
| 6 | 3 | 100 | 6 |
...
+----+------------+-------+------+
I want to group by product_id such that I have the 1'th sample in descending date order and a new colomn added with the Price of the 7'th sample row in each product group. If the 7'th row does not exist, then the value should be null.
Example:
+----+------------+-------+------+----------+
| Id | Product_Id | Price | Date | 7thPrice |
+----+------------+-------+------+----------+
| 4 | 1 | 100 | 4 | 120 |
| 5 | 2 | 100 | 5 | 100 |
| 6 | 3 | 100 | 6 | NULL |
+----+------------+-------+------+----------+
I belive I can achieve the table without the '7thPrice' with the following
SELECT * FROM (
SELECT ROW_NUMBER() OVER (PARTITION BY Product_Id ORDER BY date DESC) r, * FROM Samples
) T WHERE T.r = 1
Any suggestions?
You can try something like this. I used your query to create a CTE. Then joined rank1 to rank7.
;with sampleCTE
as
(SELECT ROW_NUMBER() OVER (PARTITION BY Product_Id ORDER BY date DESC) r, * FROM Samples)
select *
from
(select * from samplecte where r = 1) a
left join
(select * from samplecte where r=7) b
on a.product_id = b.product_id