What I have
id | value
1 | foo
2 | foo
3 | bah
4 | bah
5 | bah
6 | jezz
7 | jezz
8 | jezz
9 | pas
10 | log
What I need:
Enumerate rows as in the following example
id | value | enumeration
1 | foo | 1
2 | foo | 1
3 | bah | 2
4 | bah | 2
5 | bah | 2
6 | jezz | 3
7 | jezz | 3
8 | jezz | 3
9 | pas | 4
10 | log | 5
I've tried row_number with over partition. But this leads to another kind of enumeration.
Thanks for any help
You can use rank() or dense_rank() for that case:
Click: demo:db<>fiddle
SELECT
*,
dense_rank() OVER (ORDER BY value)
FROM
mytable
rank() generates an ordered number to every element of a group, but it creates gaps (if there were 3 elements in the first group, the second group starting at row 4 would get the number 4). dense_rank() avoids these gaps.
Note, this orders the table by the value column alphabetically. So, the result will be: blah == 1, foo == 2, jezz == 3, log == 4, pas == 5.
If you want to keep your order, you need an additional order criterion. In your case you could use the id column to create such a column, if no other is available:
Click: demo:db<>fiddle
First, use first_value() to find the lowest id per value group:
SELECT
*,
first_value(id) OVER (PARTITION BY value ORDER BY id)
FROM
mytable
This first value (foo == 1, blah == 3, ...) can be used to keep the original order when calculating the dense_rank():
SELECT
id,
value,
dense_rank() OVER (ORDER BY first_value)
FROM (
SELECT
*,
first_value(id) OVER (PARTITION BY value ORDER BY id)
FROM
mytable
) s
Related
How to increase value when source value is changed?
I have tried rank, dense_rank, row_number without success =(
id | src | how to get this?
--------
1 | 1 | 1
2 | 1 | 1
3 | 7 | 2
4 | 1 | 3
5 | 3 | 4
6 | 3 | 4
7 | 1 | 5
NOTICE: src is guaranteed to be in this order you see
is there simple way to do this?
You can achieve this by nesting two window functions - the first to get whether the src value changed from the previous row, the second to sum the number of changes. Unfortunately Postgres doesn't allow nesting window functions directly, but you can work around that with a subquery:
SELECT
id,
src,
sum(incr) OVER (ORDER BY id)
FROM (
SELECT
*,
(lag(src) OVER (ORDER BY id) IS DISTINCT FROM src)::int AS incr
FROM example
) AS _;
(online demo)
I have a table called example that looks as follows:
ID | MIN | MAX |
1 | 1 | 5 |
2 | 34 | 38 |
I need to take each ID and loop from it's min to max, incrementing by 2 and thus get the following WITHOUT using INSERT statements, thus in a SELECT:
ID | INDEX | VALUE
1 | 1 | 1
1 | 2 | 3
1 | 3 | 5
2 | 1 | 34
2 | 2 | 36
2 | 3 | 38
Any ideas of how to do this?
The set-returning function generate_series does exactly that:
SELECT
id,
generate_series(1, (max-min)/2+1) AS index,
generate_series(min, max, 2) AS value
FROM
example;
(online demo)
The index can alternatively be generated with RANK() (example, see also #a_horse_with_no_name's answer) if you don't want to rely on the parallel sets.
Use generate_series() to generate the numbers and a window function to calculate the index:
select e.id,
row_number() over (partition by e.id order by g.value) as index,
g.value
from example e
cross join generate_series(e.min, e.max, 2) as g(value);
I have a table with a list of names and indices. For example like this:
ID | Name | Index
1 | Value 1 | 3
2 | Value 2 | 4
...
N | Value N | NN
I need to create a new table, where every value from field "Name" will be repeat repeated as many times as the "Index" field is specified. For example like this:
ID | Name_2 | ID_2
1 | Value 1 | 1
2 | Value 1 | 2
3 | Value 1 | 3
4 | Value 2 | 1
5 | Value 2 | 2
6 | Value 2 | 3
7 | Value 2 | 4
...
N | Value N | 1
N+1| Value N | 2
...
I have no idea how to write a cycle to get such result. Please, give me an advice.
Here is solution to repeat the rows based on a column value
declare #order table ( Id int, name varchar(20), indx int)
Insert into #order
(Id, name, indx)
VALUES
(1,'Value1',3),
(2,'Value2',4),
(3,'Value3',2)
;WITH cte AS
(
SELECT * FROM #order
UNION ALL
SELECT cte.[ID], cte.name, (cte.indx - 1) indx
FROM cte INNER JOIN #order t
ON cte.[ID] = t.[ID]
WHERE cte.indx > 1
)
SELECT ROW_NUMBER() OVER(ORDER BY name ASC) AS Id, name as [name_2], 1 as [Id_2]
FROM cte
ORDER BY 1
Consider the following table structure:
CREATE TABLE residences (id int, price int, categories jsonb);
INSERT INTO residences VALUES
(1, 3, '["monkeys", "hamsters", "foxes"]'),
(2, 5, '["monkeys", "hamsters", "foxes", "foxes"]'),
(3, 7, '[]'),
(4, 11, '["turtles"]');
SELECT * FROM residences;
id | price | categories
----+-------+-------------------------------------------
1 | 3 | ["monkeys", "hamsters", "foxes"]
2 | 5 | ["monkeys", "hamsters", "foxes", "foxes"]
3 | 7 | []
4 | 11 | ["turtles"]
Now I would like to know how many residences there are for each category, as well as their sum of prices. The only way I found was to do this was using a sub-query:
SELECT category, SUM(price), COUNT(*) AS residences_no
FROM
residences a,
(
SELECT DISTINCT(jsonb_array_elements(categories)) AS category
FROM residences
) b
WHERE a.categories #> category
GROUP BY category
ORDER BY category;
category | sum | residences_no
------------+-----+---------------
"foxes" | 8 | 2
"hamsters" | 8 | 2
"monkeys" | 8 | 2
"turtles" | 11 | 1
Using jsonb_array_elements without subquery would return three residences for foxes because of the duplicate entry in the second row. Also the price of the residence would be inflated by 5.
Is there any way to do this without using the sub-query, or any better way to accomplish this result?
EDIT
Initially I did not mention the price column.
select category, count(distinct (id, category))
from residences, jsonb_array_elements(categories) category
group by category
order by category;
category | count
------------+-------
"foxes" | 2
"hamsters" | 2
"monkeys" | 2
"turtles" | 1
(4 rows)
You have to use a derived table to aggregate another column (all prices at 10):
select category, count(*), sum(price) total
from (
select distinct id, category, price
from residences, jsonb_array_elements(categories) category
) s
group by category
order by category;
category | count | total
------------+-------+-------
"foxes" | 2 | 20
"hamsters" | 2 | 20
"monkeys" | 2 | 20
"turtles" | 1 | 10
(4 rows)
I have a table in SQL Server 2008 R2 which contains product orders. For the most part, it is one entry per product
ID | Prod | Qty
------------
1 | A | 1
4 | B | 1
7 | A | 1
8 | A | 1
9 | A | 1
12 | C | 1
15 | A | 1
16 | A | 1
21 | B | 1
I want to create a view based on the table which looks like this
ID | Prod | Qty
------------------
1 | A | 1
4 | B | 1
9 | A | 3
12 | C | 1
16 | A | 2
21 | B | 1
I've written a query using a table expression, but I am stumped on how to make it work. The sql below does not actually work, but is a sample of what I am trying to do. I've written this query multiple different ways, but cannot figure out how to get the right results. I am using row_number to generate a sequential id. From that, I can order and compare consecutive rows to see if the next row has the same product as the previous row since ReleaseId is sequential, but not necessarily contiguous.
;with myData AS
(
SELECT
row_number() over (order by a.ReleaseId) as 'Item',
a.ReleaseId,
a.ProductId,
a.Qty
FROM OrdersReleased a
UNION ALL
SELECT
row_number() over (order by b.ReleaseId) as 'Item',
b.ReleaseId,
b.ProductId,
b.Qty
FROM OrdersReleased b
INNER JOIN myData c ON b.Item = c.Item + 1 and b.ProductId = c.ProductId
)
SELECT * from myData
Usually you drop the ID out of something like this, since it is a summary.
SELECT a.ProductId,
SUM(a.Qty) AS Qty
FROM OrdersReleased a
GROUP BY a.ProductId
ORDER BY a.ProductId
-- if you want to do sub query you can do it as a column (if you don't have a very large dataset).
SELECT a.ProductId,
SUM(a.Qty) AS Qty,
(SELECT COUNT(1)
FROM OrdersReleased b
WHERE b.ReleasedID - 1 = a.ReleasedID
AND b.ProductId = b.ProductId) as NumberBackToBack
FROM OrdersReleased a
GROUP BY a.ProductId
ORDER BY a.ProductId