This is my database:
| ID | Repeat_Times |
| ------| -------------|
| 99 | 3 |
| 100 | 4 |
| 99 | 5 |
The results I need:
ID
Repeat_Times
99
8
100
4
I'd just take a pivot in Excel, what should I use in SQL?
I assume that the table name is "repeat_table", so in general you can do the query as below to get that expected result
SELECT ID, SUM(Repeat_Times) AS Repeat_Times FROM repeat_table GROUP BY ID;
Related
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
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
I have a query like the below:
SELECT value
FROM people
GROUP BY id
With people table structure like:
... | id | value
----------------
... | 1 | 5.43
... | 1 | 4.92
... | 1 | 1.22
... | 2 | 2.11
... | 2 | 1.00
... | 3 | 4.33
... | 4 | 9.12
... | 5 | 4.43
... | 5 | 5.09
... |...| ...
This would return a result set like the below:
id | value
----------
1 | 5.43
2 | 2.11
3 | 4.33
4 | 9.12
5 | 4.43
...| ...
It only takes the first value per id, but I want to aggregate them. eg. the value of the grouped id = 1 would be 3.86. I'm not sure the SQL for this, or even if it is possible. Any ideas?
Do you mean average?
SELECT id,avg(value)
FROM people
GROUP BY id
Looks like you're trying to get an average.
SELECT id, avg(value)
FROM people
GROUP BY id
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 :)
This should be a simple one, but say I have a table with data like this:
| ID | Date | Value |
| 1 | 01/01/2013 | 40 |
| 2 | 03/01/2013 | 20 |
| 3 | 10/01/2013 | 30 |
| 4 | 14/02/2013 | 60 |
| 5 | 15/03/2013 | 10 |
| 6 | 27/03/2013 | 70 |
| 7 | 01/04/2013 | 60 |
| 8 | 01/06/2013 | 20 |
What I want is the sum of values per week of the year, showing ALL weeks.. (for use in an excel graph)
What my query gives me, is only the weeks that are actually in the database.
With SQL you cannot return rows that don't exist in some table. To get the effect you want you could create a table called WeeksInYear with only one field WeekNumber that is an Int. Populate the table with all the week numbers. Then JOIN that table to this one.
The query would then look something like the following:
SELECT w.WeekNumber, SUM(m.Value)
FROM MyTable as m
RIGHT OUTER JOIN WeeksInYear AS w
ON DATEPART(wk, m.date) = w.WeekNumber
GROUP BY w.WeekNumber
The missing weeks will not have any data in MyTable and show a 0.