i have a table like this
code Quantity
1 5
1 6
2 2
2 1-
3 4
.
.
how can made it like this
code Quantity remain
1 5 5
1 6 11
2 2 2
2 1- 1
3 4 4
.
.
Your query presumes an ordering of the rows. I will assume you have such a column.
Assuming the values are numbers (1- ???), then you can simply use a cumulative sum:
select t.*,
sum(quantity) over (partition by code order by ?) as remaining
from t;
The ? is for the column that specifies the ordering.
You can do a window sum, but you need a column to unambiguously order the records within groups sharing the same code. I assumed that this column is called id.
select t.*, sum(quantity) over(partition by code order by id) remain from mytable t
Related
I've got this table ratings:
id
user_id
type
value
0
0
Rest
4
1
0
Bar
3
2
0
Cine
2
3
0
Cafe
1
4
1
Rest
4
5
1
Bar
3
6
1
Cine
2
7
1
Cafe
5
8
2
Rest
4
9
2
Bar
3
10
3
Cine
2
11
3
Cafe
5
I want to have a table with a row for every pair (user_id, type) for the top 3 rated types through all users (ranked by sum(value) across the whole table).
Desired result:
user_id
type
value
0
Rest
4
0
Cafe
1
0
Bar
3
1
Rest
4
1
Cafe
5
1
Bar
3
2
Rest
4
3
Cafe
5
2
Bar
3
I was able to do this with two queries, one to get the top 3 and then another to get the rows where the type matches the top 3 types.
Does someone know how to fit this into a single query?
Get rows per user for the 3 highest ranking types, where types are ranked by the total sum of their value across the whole table.
So it's not exactly about the top 3 types per user, but about the top 3 types overall. Not all users will have rows for the top 3 types, even if there would be 3 or more types for the user.
Strategy:
Aggregate to get summed values per type (type_rnk).
Take only the top 3. (Break ties ...)
Join back to main table, eliminating any other types.
Order result by user_id, type_rnk DESC
SELECT r.user_id, r.type, r.value
FROM ratings r
JOIN (
SELECT type, sum(value) AS type_rnk
FROM ratings
GROUP BY 1
ORDER BY type_rnk DESC, type -- tiebreaker
LIMIT 3 -- strictly the top 3
) v USING (type)
ORDER BY user_id, type_rnk DESC;
db<>fiddle here
Since multiple types can have the same ranking, I added type to the sort order to break ties alphabetically by their name (as you did not specify otherwise).
Turns out, we don't need window functions - the ones with OVER and, optionally, PARTITION for this. (Since you asked in a comment).
I think you just want row_number(). Based on your results, you seem to want three rows per type, with the highest value:
select t.*
from (select t.*,
row_number() over (partition by type order by value desc) as seqnum
from t
) t
where seqnum <= 3;
Your description suggests that you might just want this per user, which is a slight tweak:
select t.*
from (select t.*,
row_number() over (partition by user order by value desc) as seqnum
from t
) t
where seqnum <= 3;
I have table something like:
GROUP
NAME
Value_1
Value_2
1
ABC
0
0
1
DEF
4
4
50
XYZ
6
6
50
QWE
6
7
100
XYZ
26
2
100
QWE
26
2
What I would like to do is to groupby group and select the name with highest value_1. If their value_1 are the same, compare and select the max with value_2. If they're still the same, select the first one.
The output will be something like:
GROUP
NAME
Value_1
Value_2
1
DEF
4
4
50
QWE
6
7
100
XYZ
26
2
The challenge for me here is I don't know how many categories in NAME so a simple case when is not working. Thanks for help
You can use window functions to solve the bulk of your problem:
select t.*
from (select t.*,
row_number() over (partition by group order by value1 desc, value2 desc) as seqnum
from t
) t
where seqnum = 1;
The one caveat is the condition:
If they're still the same, select the first one.
SQL tables represent unordered (multi-) sets. There is no "first" one unless a column specifies the ordering. The best you can do is choose an arbitrary value when all the other values are the same.
That said, you might have another column that has an ordering. If so, add that as a third key to the order by.
Consider the following table:
ID GroupId Rank
1 1 1
2 1 2
3 1 1
4 2 10
5 2 1
6 3 1
7 4 5
I need an sql (for MS-SQL) select query selecting a single Id for each group with the lowest rank. Each group needs to only return a single ID, even if there are two with the same rank (as 1 and 2 do in the above table). I've tried to select the min value, but the requirement that only one be returned, and the value to be returned is the ID column, is throwing me.
Does anyone know how to do this?
Use row_number():
select t.*
from (select t.*,
row_number() over (partition by groupid order by rank) as seqnum
from t
) t
where seqnum = 1;
I have a table of consecutive ids (integers, 1 ... n), and values (integers), like this:
Input Table:
id value
-- -----
1 1
2 1
3 2
4 3
5 1
6 1
7 1
Going down the table i.e. in order of increasing id, I want to count how many times in a row the same value has been seen consecutively, i.e. the position in a run:
Output Table:
id value position in run
-- ----- ---------------
1 1 1
2 1 2
3 2 1
4 3 1
5 1 1
6 1 2
7 1 3
Any ideas? I've searched for a combination of windowing functions including lead and lag, but can't come up with it. Note that the same value can appear in the value column as part of different runs, so partitioning by value may not help solve this. I'm on Hive 1.2.
One way is to use a difference of row numbers approach to classify consecutive same values into one group. Then a row number function to get the desired positions in each group.
Query to assign groups (Running this will help you understand how the groups are assigned.)
select t.*
,row_number() over(order by id) - row_number() over(partition by value order by id) as rnum_diff
from tbl t
Final Query using row_number to get positions in each group assigned with the above query.
select id,value,row_number() over(partition by value,rnum_diff order by id) as pos_in_grp
from (select t.*
,row_number() over(order by id) - row_number() over(partition by value order by id) as rnum_diff
from tbl t
) t
I have the following table structure.
ITEM TOTAL
----------- -----------------
ID | TITLE ID |ITEMID|VALUE
1 A 1 2 6
2 B 2 1 4
3 C 3 3 3
4 D 4 3 8
5 E 5 1 2
6 F 6 5 4
7 4 5
8 2 8
9 2 7
10 1 3
11 2 2
12 3 6
I am using Apache Derby DB. I need to perform the average calculation in SQL. I need to show the list of item IDs and their average total of the last 3 records.
That is, for ITEM.ID 1, I will go to TOTAL table and select the last 3 records of the rows which are associated with the ITEMID 1. And take average of them. In Derby database, I am able to do this for a given item ID but I cannot make it without giving a specific ID. Let me show you what I've done it.
SELECT ITEM.ID, AVG(VALUE) FROM ITEM, TOTAL WHERE TOTAL.ITEMID = ITEM.ID GROUP BY ITEM.ID
This SQL gives the average of all items in a list. But this calculates for all values of the total tables. I need last 3 records only. So I changed the SQL to this:
SELECT AVG(VALUE) FROM (SELECT ROW_NUMBER() OVER() AS ROWNUM, TOTAL.* FROM TOTAL WHERE ITEMID = 1) AS TR WHERE ROWNUM > (SELECT COUNT(ID) FROM TOTAL WHERE ITEMID = 1) - 3
This works if I supply the item ID 1 or 2 etc. But I cannot do this for all items without giving an item ID.
I tried to do the same thing in ORACLE using partition and it worked. But derby does not support partitioning. There is WINDOW but I could not make use of it.
Oracle one
SELECT ITEMID, AVG(VALUE) FROM(SELECT ITEMID, VALUE, COUNT(*) OVER (PARTITION BY ITEMID) QTY, ROW_NUMBER() OVER (PARTITION BY ITEMID ORDER BY ID) IDX FROM TOTAL ORDER BY ITEMID, ID) WHERE IDX > QTY -3 GROUP BY ITEMID ORDER BY ITEMID
I need to use derby DB for its portability.
The desired output is this
RESULT
-----------------
ITEMID | AVERAGE
1 (9/3)
2 (17/3)
3 (17/3)
4 (5/1)
5 (4/1)
6 NULL
As you have noticed, Derby's support for the SQL 2003 "OLAP Operations" support is incomplete.
There was some initial work (see https://wiki.apache.org/db-derby/OLAPOperations), but that work was only partially completed.
I don't believe anyone is currently working on adding more functionality to Derby in this area.
So yes, Derby has a row_number function, but no, Derby does not (currently) have partition by.