I have table1 and tbl_cat. I want to update value of x where animal is cat
table1
id id_animal animal x
2 1 cat 3
3 2 cat 5
4 1 dog 7
5 2 dog 8
6 3 dog 9
tbl_cat
id x
1 10
2 30
Result Expectation:
table1
id id_animal animal x
2 1 cat 10
3 2 cat 30
4 1 dog 7
5 2 dog 8
6 3 dog 9
I use this query, but it's not work:
update table1
set table1.x = tbl_cat.x
from table1 inner join tbl_cat
on (table1.id_animal=tbl_cat.id)
where table1.animal='cat'
The correct syntax in Postgres is:
update table1
set table1.x = tbl_cat.x
from tbl_cat
where table1.id_animal = tbl_cat.id and
table1.animal = 'cat';
For some inexplicable reason, the three major databases that support join in update clauses (MySQL, SQL Server, and Postgres) all have different syntax. Your syntax is the SQL Server syntax.
Related
Input:
Name GroupId Processed NewGroupId NgId
Mike 1 N 9 NULL
Mikes 1 N 9 NULL
Miken 5 Y 9 5
Mikel 5 Y 9 5
Output:
Name GroupId Processed NewGroupId NgId
Mike 1 N 9 5
Mikes 1 N 9 5
Miken 5 Y 9 5
Mikel 5 Y 9 5
below query worked in sql server, due to correlated subquery same is not working in spark sql.
Is there any alternate either with spark sql or pyspark dataframe.
SELECT Name,groupid,IsProcessed,ngid,
CASE WHEN ngid IS NULL THEN
COALESCE((SELECT top 1 ngid FROM temp D
WHERE D.NewGroupId = T.NewGroupId AND
D.ngid IS NOT NULL ), null)
ELSE ngid
END AS ngid
FROM temp T
worked with below in sparksql.
spark.sql("select LKUP,groupid,IsProcessed,NewGroupId ,coalesce((select Max(D.ngid) from test2 D where D.NewGroupId = T.NewGroupId AND D.ngidis not null),null) as ngid from test2 T")
Any help with the following would be much appreciated!
I have two tables: table1 is a summary table whilst table2 is a list of all data points. I want to be able to summarise the information in table2 for each row in table1.
table1:flip `grp`constraint!(`a`b`c`d; 10 10 20 20);
table2:flip `grp`cat`constraint`val!(`a`a`a`a`a`b`b`b;`cl1`cl1`cl1`cl2`cl2`cl2`cl2`cl1; 10 10 10 10 10 10 20 10; 1 2 3 4 5 6 7 8);
function:{[grpL;constraintL;catL] first exec total: sum val from table2 where constraint=constraintL, grp=grpL,cat=catL};
update cl1:function'[grp;constraint;`cl1], cl2:function'[grp;constraint;`cl2] from table1;
The fourth line of this code achieves what I want for the two categories:cl1 and cl2
In table1 I want to name a new column with the name of the category (cl1, cl2, etc.) and I want the values in that column to be the output from running the function over that column.
However, I have hundreds of different categories, so don't want to have to list them out manually as in the fourth line. How would I pass in a list of categories, e.g. below?
`cl1`cl2`cl3
Sticking to your approach, you would just have to make your update statement functional and then iterate over the columns like so:
{![`table1;();0b;(1#x)!enlist ((';function);`grp;`constraint;1#x)]} each `cl1`cl2
Assuming you can amend table1 in place. If you must retain the original table1 then you can pass it by value though it will consume more memory
{![x;();0b;(1#y)!enlist ((';function);`grp;`constraint;1#y)]}/[table1;`cl1`cl2]
Another approach would be to aggregate, pivot and join though it's not necessarily a better solution as you get nulls rather than zeros
a:select sum val by cat,grp,constraint from table2
p:exec (exec distinct cat from a)#cat!val by grp,constraint from a
table1 lj p
There are several different methods you can look into.
The easiest method would be a functional update - http://code.kx.com/wiki/JB:QforMortals2/queries_q_sql#Functional_update
Below, though, should somewhat prove more useful, quicker and neater:
Your problem can be split into 2 parts. For the first part, you are looking to create a sum of each category by grp and constraint within table2. As for the second part, you are looking to join these results (the lookups) onto the corresponding records from table1.
You can create the necessary groups using by
q)exec val,cat by grp,constraint from table2
grp constraint| val cat
--------------| ------------------------------
a 10 | 1 2 3 4 5 `cl1`cl1`cl1`cl2`cl2
b 10 | 6 8 `cl2`cl1
b 20 | ,7 ,`cl2
Note though, this will only create nested lists of the columns in your select query
Next is to sum each of the cat groups
q)exec sum each val group cat by grp,constraint from table2
grp constraint|
--------------| ------------
a 10 | `cl1`cl2!6 9
b 10 | `cl2`cl1!6 8
b 20 | (,`cl2)!,7
Then, to create the cat's columns you can use a pivot like syntax - http://code.kx.com/wiki/Pivot
q)cats:asc exec distinct cat from table2
q)exec cats#sum each val group cat by grp,constraint from table2
grp constraint| cl1 cl2
--------------| -------
a 10 | 6 9
b 10 | 8 6
b 20 | 7
Now you can use this lookup table and index into each row from table1
q)(exec cats#sum each val group cat by grp,constraint from table2)[table1]
cl1 cl2
-------
6 9
8 6
To fill the nulls with zeros, use the carat symbol - http://code.kx.com/wiki/Reference/Caret
q)0^(exec cats#sum each val group cat by grp,constraint from table2)[table1]
cl1 cl2
-------
6 9
8 6
0 0
0 0
And now you can join on each row from table1 to your results using join-each
q)table1,'0^(exec cats#sum each val group cat by grp,constraint from table2)[table1]
grp constraint cl1 cl2
----------------------
a 10 6 9
b 10 8 6
c 20 0 0
d 20 0 0
HTH, Sean
This approach is the easiest way to pass in a list of categories
{table1^flip x!function'[table1`grp;table1`constraint;]each x}`cl1`cl2
I am having a problem with my query. I have 2 tables:
Table 1 is AutoCompany it has fields company and CodeCar. CodeCar can be 3 or 4 depending on the type of car that company has.
table 1: AutoCompany
company| CodeCar|
jora 3
jora 4
jora 3
ghita 3
ghita 3
ghita 4
gheorghe 4
gheorghe 3
gheorghe 3
Table 2 CodeCarCompanies has the codes:
car | codeCar
mers 3
vW 4
I need to select the companies with the count of the occurance of the 2 codeCars
resulting in something like this:
company | MERS| VW
jora 2 1
ghita 2 1
gheorghe 2 1
My attempt so far:
SELECT COUNT(dbo.AutoComany) AS MERS, dbo.Company, COUNT(dbo.AutoComany.
[CodeCar]) AS VW,
FROM dbo.AutoComany FULL OUTER JOIN
dbo.AutoComany ON dbo.АВТОМОБ.КодПредпр = AutoCompany.company
WHERE (dbo.CodeCarComapnies.[CodeCar] = 3)
GROUP BY dbo..company, dbo.CodeCarComapnies.[CodeCar]
HAVING (dbo.CodeCarComapnies.[CodeCar] = 4)
In MS Access, I think you want:
SELECT codecarcomapnies.car,
Count(autocompany.codecar) AS CountOfCodeCar
FROM autocompany
INNER JOIN codecarcomapnies
ON autocompany.codecar = codecarcomapnies.codecar
WHERE autocompany.codecar IN ( 3, 4 )
GROUP BY codecarcomapnies.car;
The above was built using the MS Access query design window and the Sum Σ button
Edit re Comment
SELECT Sum(IIf([autocompany].[codecar]=3,1,0)) AS mers,
Sum(IIf([autocompany].[codecar]=4,1,0)) AS vw
FROM autocompany
Or
TRANSFORM Count(autocompany.CodeCar) AS CountOfCodeCar
SELECT "Total" AS Total
FROM autocompany
INNER JOIN CodeCarComapnies
ON autocompany.CodeCar = CodeCarComapnies.codeCar
WHERE autocompany.CodeCar In (3,4)
GROUP BY "Total"
PIVOT CodeCarComapnies.car
I would like to query a sql table from below
ID Val
-------------
1 5
1 7
1 8
1 9
2 5
2 7
2 9
3 1
3 5
that would return the following set of results
query > select distinct ID from dbo.table where val in (5,7,9)
result
--------
ID
1
2
I run into a problem where a single row can match only one val from the subset and not all of them...
Assuming the rows are distinct:
SELECT ID
FROM your_table
WHERE Val IN (5,7,9)
GROUP BY ID
HAVING COUNT(*) = 3
I would like a query that will show a sum of columns with a default value for missing data. For example assume I have a table as follows:
type_lookup:
id name
-----------
1 self
2 manager
3 peer
And a table as follows
data:
id type_lookup_id value
--------------------------
1 1 1
2 1 4
3 2 9
4 2 1
5 2 9
6 1 5
7 2 6
8 1 2
9 1 1
After running a query I would like a result set as follows:
type_lookup_id value
----------------------
1 13
2 25
3 0
I would like all rows in type_lookup table to be included in the result set - even if they don't appear in the data table.
It's a bit hard to read your data layout, but something like the following should do the trick:
SELECT tl.type_lookup_id, tl.name, sum(da.type_lookup_id) how_much
from type_lookup tl
left outer join data da
on da.type_lookup_id = tl.type_lookup_id
group by tl.type_lookup_id, tl.name
order by tl.type_lookup_id
[EDIT]
...subsequently edited by changing count() to sum().