I am having some trouble with the below query. I do understand I need to group by ID and Category, but I only want to group by ID while keeping the rest of the columns based on Rank being max. Is there a way to only group by certain columns?
select ID, Category, max(rank)
from schema.table1
group by ID
Input:
ID Category Rank
111 3 4
111 1 5
123 5 3
124 7 2
Current Output
ID Category Rank
111 3 4
111 9 1
123 5 3
124 7 2
Desired Output
ID Category Rank
111 1 5
123 5 3
124 7 2
You can use:
select *
from table1
where (id, rank) in (select id, max(rank) from table1 group by id)
Result:
ID CATEGORY RANK
---- --------- ----
111 1 5
123 5 3
124 7 2
Or you can use the ROW_NUMBER() window function. For example:
select *
from (
select *,
row_number() over(partition by id order by rank desc) as rn
from table1
) x
where rn = 1
See running example at db<>fiddle.
You can try using - row_number()
select * from
(
select ID, Category,rank, row_number() over(partition by id order by rank desc) as rn
from schema.table1
)A where rn=1
Related
For example, N is 10 and a table looks like
id
1
2
3
4
5
6
7
10
11
12
13
108
109
111
112
113
Need to find first N rows that have unique value with mod(id, N).
Expected result is
mod10
1
2
3
4
5
6
7
10
108
109
I've tried something like
select *
from
(
select id, id % 10 as seq_id
from accounts order by id
) as s1
group by s1.seq_id limit 10;`
but not working.
You can use window function here -
SELECT id
FROM (SELECT id, ROW_NUMBER() OVER(PARTITION BY id % 10 ORDER BY id) RN
FROM table_name
) X
WHERE RN = 1
ORDER BY id
You can try the below one - using row_number()
DEMO
with cte as
(
select id, row_number() over(partition by seq_id order by id) as rn
from
(
select id, id % 10 as seq_id from tablename
)A
)
select id from cte where rn=1 order by id
OUTPUT:
id
1
2
3
4
5
6
7
10
108
109
Input :
id name value1 value2 date
1 A 1 1 2019-01-01
1 A 2 2 2019-02-15
1 A 3 3 2019-01-15
1 A 1 1 2019-07-13
2 B 1 2 2019-01-01
2 B 1 3 2019-02-15
2 B 2 1 2019-07-13
3 C 2 4 2019-02-15
3 C 1 2 2019-01-01
3 C 1 9 2019-07-13
3 C 3 1 2019-02-15
Expected Output :
id name value1 value2 date
1 A 1 Avg(value2) 2019-07-13
2 B 2 Avg(value2) 2019-07-13
3 C 1 Avg(value2) 2019-07-13
You can use window functions. rank() over() can be used to identify the first record in each group, and avg() over() will give you a window average of value2 in each group:
select id, name, value1, avg_value2 value2, date
from (
select
t.*,
avg(value2) over(partition by id, name) avg_value2,
rank() over(partition by id, name order by date desc) rn
from mytable t
) t
where rn = 1
sort your data in the right way, use the window function row_number() as identifier and select the first entry of every partition.
with temp_data as
(
select
row_number() over (partition by debug.tbl_data.id order by debug.tbl_data.date desc) as index,
*,
avg(debug.tbl_data.value2)over (partition by debug.tbl_data.id) as data_avg
from debug.tbl_data
order by id asc, debug.tbl_data.date desc
)
select
*
from temp_data
where index = 1
You seem to want the most common value of value1. In statistics, this is called the "mode". You can do this as:
select id, name,
mode() within group (order by value1) as value1_mode,
avg(value2),
max(date)
from t
group by id, name;
I have a table with values
id sales date
1 5 "2015-01-04"
1 3 "2015-01-03"
1 1 "2015-01-01"
1 1 "2015-01-01"
2 7 "2015-01-05"
2 6 "2015-01-04"
2 4 "2015-01-03"
3 11 "2015-01-08"
3 10 "2015-01-07"
3 9 "2015-01-06"
3 8 "2015-01-05"
I want to select top two values of each id as shown in desired output.
Desired output:
id sales date
1 5 "2015-01-04"
1 3 "2015-01-03"
2 7 "2015-01-05"
2 6 "2015-01-04"
3 11 "2015-01-08"
3 10 "2015-01-07"
My attempt:
can someone help me with this. Thank you in advance!
select transactions.salesperson_id, transactions.id, transactions.date
from transactions
ORDER BY transactions.salesperson_id ASC, transactions.date DESC;
This can be done using window functions:
select id, sales, "date"
from (
select id, sales, "date",
dense_rank() over (partition by id order by "date" desc) as rnk
from transactions
) t
where rnk <= 2;
If there are multiple rows on the same date this might return more than two rows for the same ID. If you don't want that, use row_number() instead of dense_rank()
row_number() will get what you want.
select * from
(select row_number() over (partition by id order by date) as rn, sales, date from transactions) t1
where t1.rn <= 2
Tbl1
---------------------------------------------------------
Id Date Qty ReOrder
---------------------------------------------------------
1 1-1-18 1 3
2 2-1-18 0 3
3 3-1-18 2 3
4 4-1-18 3< >3
5 5-1-18 2 3
6 6-1-18 0 3
7 7-1-18 1 3
8 8-1-18 0 3
---------------------------------------------------------
I want the result like below
---------------------------------------------------------
Id Date Qty ReOrder
---------------------------------------------------------
1 1-1-18 1 3
5 5-1-18 2 3
---------------------------------------------------------
if ReOrder not same with Qty then date will be same upto after reorder=Qty
You can use cumulative approach with row_number() function :
select top (1) with ties *
from (select *, max(case when qty = reorder then 'v' end) over (order by id desc) grp
from table
) t
order by row_number() over(partition by grp order by id);
Unfortunately this will require SQL Server, But you can also do:
select *
from (select *, row_number() over(partition by grp order by id) seq
from (select *, max(case when qty = reorder then 'v' end) over (order by id desc) grp
from table
) t
) t
where seq = 1;
I have a table like this
Id scid name namesuffix nameId namesuffixid fullname
--------------------------------------------------------
1 1 a a 100 100 a
2 1 a b 100 101 ab
3 1 b c 101 102 abc
4 1 c d 102 103 abcd
5 2 e e 104 104 e
6 2 e f 104 105 ef
7 2 f g 105 106 efg
8 3 i i 107 107 i
9 3 i j 107 108 ij
10 3 j k 108 109 ijk
11 3 k l 109 110 ijkl
12 3 l m 110 111 ijklm
for each scid (group by scid)
select firstRow fullName
Last row fullName
Expected output
id scid fullname
-------------------
1 1 a
4 1 abcd
5 2 e
7 2 efg
8 3 i
12 3 ijklm
I tried first_value and last_value analytic functions, but the rows are repeating, didn't get expected result.
Any help appreciated.
Another option is to use ROW_NUMBER() and COUNT
select
id, scid, fullname
from (
select
*, row_number() over (partition by scid order by id) rn
, count(*) over (partition by scid) cnt
from
myTable
) t
where
rn = 1
or rn = cnt
You could use FIRST_VALUE and LAST_VALUE as you proposed:
SELECT scid,
FIRST_VALUE(id) OVER(PARTITION BY scid ORDER BY id
ROWS UNBOUNDED PRECEDING) AS id,
FIRST_VALUE(fullname) OVER(PARTITION BY scid ORDER BY id
ROWS UNBOUNDED PRECEDING) AS fullname
FROM tab_name
UNION
SELECT scid,
LAST_VALUE(id) OVER(PARTITION BY scid ORDER BY id
RANGE BETWEEN CURRENT ROW AND UNBOUNDED FOLLOWING) AS id,
LAST_VALUE(fullname) OVER(PARTITION BY scid ORDER BY id
RANGE BETWEEN CURRENT ROW AND UNBOUNDED FOLLOWING) AS fullname
FROM tab_name
ORDER BY scid, id;
Demo
There are other ways to do this without window funtions:
select t.*
from t join
(select min(id) as min_id, max(id) as max_id
from t
group by sc_id
) tt
on t.id in (min_id, max_id);
I only suggest this because there are many ways to do what you want. If performance is an issue, you may want to experiment with different methods.