Let's say I have data like this :
| id | code | name | number |
-----------------------------------------------
| 1 | 20 | A | 10 |
| 2 | 20 | B | 20 |
| 3 | 10 | C | 30 |
| 4 | 10 | D | 80 |
I would like to group rows by code value, but get real rows back (not some aggregate function).
I know that just
select *
from table
group by code
won't work because database don't know which row to return where code is the same.
So my question is how to tell database to select (for example) the lower number column so in my case
| id | code | name | number |
-----------------------------------------------
| 1 | 20 | A | 10 |
| 3 | 10 | C | 30 |
P.S.
I know how to do this by PARTITION but this is only allowed in Oracle databases and can't be created in JPA criteria builder (what is my ultimate goal).
Why You don't use code like this?
SELECT
id,
code,
name,
number
FROM
(
SELECT
*,
ROW_NUMBER() OVER (PARTITION BY code ORDER BY number ASC) AS RowNo
FROM table
) s
WHERE s.RowNo = 1
You can look at this site;
Data Partitioning
Related
I have data in SQL as follows:
Actual Table
+-------------+--------+------+
| Id | Weight | Type |
+-------------+--------+------+
| 00011223344 | 35 | A |
| 00011223344 | 10 | A |
| 12311223344 | 100 | B |
| 00034343434 | 25 | A |
| 00034343434 | 25 | A |
| 99934343434 | 200 | C |
| 88855667788 | 100 | D |
+-------------+--------+------+
Column ID will always have length of 11 and has data type varchar. I need to create a column Actual Weight and Actual ID from the table above.
Actual Id is dependent on column ID. If the ID starts with 000 than we need to find ID from column ID that does not starts with 000 but characters after that (i.e. 8 characters from right) are similar. Matched ID would be the Actual Id. For example if we look at first 3 ids first 2 starts with 000 and another ID that does not starts with 000 and contains similar 8 characters from right can be found in 3rd row i.e. 12311223344 therefore in derived column Actual ID the first 2 rows would have Actual Id as 12311223344.
Actual Weight is dependent on values in 2 columns ID and Weight. We need to group column Id based on the criteria mentioned above if for any Id that does not starts with 000 but contains another entry that does starts with 000. Then we need to recalculate Weight for Id that does not starts with 000 by adding all Weights of ones starting with 000 and taking difference with one that does not starts with 000.
Example if we look at first 3 rows, in 3rd row we have Id starting with 123 and having entries that have 8 digits from right similar to this one except they start with 000 instead of 123 (i.e. row 1 and 2). For cases starting with 000 Actual Weight would be similar to Weight but for the one starting with 123 Actual Weight would be 100-(35+10)
I am looking for a query that can create these 2 derived column without need of creating any other table/view.
Desired Output
+-------------+-------------+--------+---------------+------+
| Id | Actual ID | Weight | Actual Weight | Type |
+-------------+-------------+--------+---------------+------+
| 00011223344 | 12311223344 | 35 | 35 | A |
| 00011223344 | 12311223344 | 10 | 10 | A |
| 12311223344 | 12311223344 | 100 | 55 | B |
| 00034343434 | 99934343434 | 25 | 25 | A |
| 00034343434 | 99934343434 | 25 | 25 | A |
| 99934343434 | 99934343434 | 200 | 150 | C |
| 88855667788 | 88855667788 | 100 | 100 | D |
+-------------+-------------+--------+---------------+------+
Hmmmm . . . If I'm following this:
select t.*,
(case when id like '000%' then weight
else weight - sum(case when id like '000%' then weight else 0 end) over (partition by actual_id)
end) as actual_weight
from (select t.*,
max(id) over (partition by stuff(id, 1, 3, '')) as actual_id
from t
) t;
Here is a db<>fiddle.
I have the following table:
|-----|-----|
| i d | val |
|-----|-----|
| 1 | 1 |
|-----|-----|
| 2 | 4 |
|-----|-----|
| 3 | 3 |
|-----|-----|
| 4 | 7 |
|-----|-----|
Can I get the following output:
|-----|
| sum |
|-----|
| 1 |
|-----|
| 5 |
|-----|
| 8 |
|-----|
| 1 5 |
|-----|
using a single SQLite3 SELECT-query? I know it could be easily achieved using variables, but SQLite3 lacks those. Maybe some recursive query? Thanks.
No.
In a relational database table rows do not have any order. If you specify an order for the rows, then it's possible to write a query.
Now, you could add an extra column to sort the rows. For example:
| val | sort
|-----|-----
| 1 | 10
| 4 | 20
| 3 | 30
| 7 | 40
The query could be:
select
sum(val) over(order by sort)
from my_table
For the updated question, you can write:
select
sum(val) over(order by id)
from my_table
By using the order of the id column and if you want only the sum column, you can do this:
select (select sum(val) from tablename where id <= t.id) sum
from tablename t
I have a GROUP BY Query which appears to use non-aggregated data not in the GROUP BY clause, which I thought would not work.
I was asked to write a query which converted the following data:
| item | type | cost | category |
|------|------|------|----------|
| 1 | X | 10 | A |
| 1 | Y | 20 | A |
| 2 | X | 30 | B |
| 2 | Y | 40 | B |
| 3 | X | 50 | C |
| 3 | Y | 60 | C |
| 4 | X | 70 | D |
| 4 | Y | 80 | D |
into this:
| item | x | y | category |
|------|----|----|----------|
| 1 | 10 | 20 | A |
| 2 | 30 | 40 | B |
| 3 | 50 | 60 | C |
| 4 | 70 | 80 | D |
Note:
The incoming data is clearly not normalised
The item is meant to be unique, but it is repeated for each type value
The category is the same for rows of the same item
I ended up with the following solution:
SELECT
item,
sum(CASE WHEN type='X' THEN cost END) as X,
sum(CASE WHEN type='Y' THEN cost END) as Y,
category
FROM data
GROUP BY item,category;
What surprised me is that it worked. What surprised me more is that it works for PostgreSQL, MariaDB (ANSI Mode), Microsoft SQL and SQLite.
Note:
- I have included category in the GROUP BY simply to allow it to appear in the SELECT clause.
- I have used the sum() function, even though there will only be one value, also simply to included it in the SELECT clause.
I thought I would not be able to use type column in the SELECT column because it is not in the GROUP BY and it is not aggregated. Indeed, if I try to select it by itself, the query will fail.
The question is, how is it that I can use the type column with the CASE operator, when I can’t use it by itself?
Your usage of the "ungrouped" columns is perfectly fine.
The rule is: "Every expression in the SELECT list must either be an aggregat function or it must part of the GROUP BY".
The column type is used inside an aggregate. sum(CASE WHEN type='X' THEN cost END) as X is not really different to sum(cost) or max(type).
This becomes more obvious if you use the standard SQL filter option:
sum(CASE WHEN type='X' THEN cost END)
is the same as:
sum(cost) filter (where type = 'X')
However only very few DBMS support this standard.
I have a "responses" table in my postgres database that looks like
| id | question_id |
| 1 | 1 |
| 2 | 2 |
| 3 | 1 |
| 4 | 2 |
| 5 | 2 |
I want to produce a table with the response and question id, as well as the id of the previous response with that same question id, as such
| id | question_id | lag_resp_id |
| 1 | 1 | |
| 2 | 2 | |
| 3 | 1 | 1 |
| 4 | 2 | 2 |
| 5 | 2 | 4 |
Obviously pulling "lag(responses.id) over (order by responses.id)" will pull the previous response id regardless of question_id. I attempted the below subquery, but I know it is wrong since I am basically making a table of all lag ids for each question id in the subquery.
select
responses.question_id,
responses.id as response_id,
(select
lag(r2.id, 1) over (order by r2.id)
from
responses as r2
where
r2.question_id = responses.question_id
)
from
responses
I don't know if I'm on the right track with the subquery, or if I need to do something more advanced (which may involve "partition by", which I do not know how to use).
Any help would be hugely appreciated.
Use partition by. There is no need for a correlated subquery here.
select id,question_id,
lag(id) over (partition by question_id order by id) lag_resp_id
from responses
I am new to sparksql and i was trying to experiment certain queries with that.
This is the query i am trying to execute
sqlContext.sql(SELECT id , category ,AVG(mark) FROM data GROUP BY id, category)
I am not getting proper output when i run the query.
instead of actual value of category i am getting some value as 1,2,3.
I am stuck at this weird error for long time
but when i do simple select statement and one group by its working perfectly
sqlContext.sql(SELECT id , category FROM data)
sqlContext.sql(SELECT id ,AVG(mark) FROM data GROUP BY id)
What is wrong? Does SPARKSQL has something to do with multiple group by.
right now i am running this complex query
sqlContext.sql(SELECT data.id , data.category, AVG(id_avg.met_avg) FROM (SELECT id, AVG(mark) AS met_avg FROM data GROUP BY id) AS id_avg, data GROUP BY data.category, data.id)
This works, but taking a longer time to execute.
Please Help
Sample data:
|id | category | marks
| 1 | a | 40
| 2 | b | 44
| 3 | a | 50
| 4 | b | 40
| 1 | a | 30
The output should be:
|id | category | avg
| 1 | a | 35
| 2 | b | 44
| 3 | a | 50
| 4 | b | 40
Please try this query:
SELECT
data.id
, data.category
, AVG(mark)
FROM data
GROUP BY
data.id
, data.category
Based on this sample data:
|id | category | marks
| 1 | a | 40
| 2 | b | 44
| 3 | a | 50
| 4 | b | 40
| 1 | a | 30
The output WILL be this:
|id | category | avg
| 1 | a | 35
| 2 | b | 44
| 3 | a | 50
| 4 | b | 40
and, the following expected row cannot be produced using group by:
| 5 | a | 30
That is a bug in sparksql.
Try using the next version. Its fixed.
i got the proper output by using spark-1.0.2
it worked with pure scala code also. Try either of them :)