Both of these tables already exist, so not looking for a dynamic situation. The goal is to consolidate the data rows horizontally, but have them to the leftmost "data" field available. There will never be a 4th entry.
I am using Microsoft SQL Server
Table1:
ID|Data
--------
A | 1
A | 2
B | 3
C | 4
C | 5
C | 6
Table2:
ID | Data 1 | Data 2 | Data 3
------------------------------
A | | |
B | | |
C | | |
Desired Result of Table2:
ID | Data 1 | Data 2 | Data 3
------------------------------
A | 1 | 2 |
B | 3 | |
C | 6 | 7 | 8
You can use row_number:
select id,
max(case when rn = 1 then data end) as data_1,
max(case when rn = 2 then data end) as data_2,
max(case when rn = 3 then data end) as data_3
from (
select t.*,
row_number() over (
partition by id order by data
) as rn
from your_table t
) t
group by id;
Related
I have a table referrals:
id | user_id_owner | firstname | is_active | user_type | referred_at
----+---------------+-----------+-----------+-----------+-------------
3 | 2 | c | t | agent | 3
5 | 3 | e | f | customer | 5
4 | 1 | d | t | agent | 4
2 | 1 | b | f | agent | 2
1 | 1 | a | t | agent | 1
And another table activations
id | user_id_owner | referral_id | amount_earned | activated_at | app_id
----+---------------+-------------+---------------+--------------+--------
2 | 2 | 3 | 3.0 | 3 | a
4 | 1 | 1 | 6.0 | 5 | b
5 | 4 | 4 | 3.0 | 6 | c
1 | 1 | 2 | 2.0 | 2 | b
3 | 1 | 2 | 5.0 | 4 | b
6 | 1 | 2 | 7.0 | 8 | a
I am trying to generate another table from the two tables that has only unique values for referrals.id and returns as one of the columns the count for each apps as best_selling_app_count.
Here is the query I ran:
with agents
as
(select
referrals.id,
referral_id,
amount_earned,
referred_at,
activated_at,
activations.app_id
from referrals
left outer join activations
on (referrals.id = activations.referral_id)
where referrals.user_id_owner = 1),
distinct_referrals_by_id
as
(select
id,
count(referral_id) as activations_count,
sum(coalesce(amount_earned, 0)) as amount_earned,
referred_at,
max(activated_at) as last_activated_at
from
agents
group by id, referred_at),
distinct_referrals_by_app_id
as
(select id, app_id as best_selling_app,
count(app_id) as best_selling_app_count
from agents
group by id, app_id )
select *, dense_rank() over (order by best_selling_app_count desc) best_selling_app_rank
from distinct_referrals_by_id
inner join distinct_referrals_by_app_id
on (distinct_referrals_by_id.id = distinct_referrals_by_app_id.id);
Here is the result I got:
id | activations_count | amount_earned | referred_at | last_activated_at | id | best_selling_app | best_selling_app_count | best_selling_app_rank
----+-------------------+---------------+-------------+-------------------+----+------------------+------------------------+-----------------------
2 | 3 | 14.0 | 2 | 8 | 2 | b | 2 | 1
1 | 1 | 6.0 | 1 | 5 | 1 | b | 1 | 2
2 | 3 | 14.0 | 2 | 8 | 2 | a | 1 | 2
4 | 1 | 3.0 | 4 | 6 | 4 | c | 1 | 2
The problem with this result is that the table has a duplicate id of 2. I only need unique values for the id column.
I tried a workaround by harnessing distinct that gave desired result but I fear the query results may not be reliable and consistent.
Here is the workaround query:
with agents
as
(select
referrals.id,
referral_id,
amount_earned,
referred_at,
activated_at,
activations.app_id
from referrals
left outer join activations
on (referrals.id = activations.referral_id)
where referrals.user_id_owner = 1),
distinct_referrals_by_id
as
(select
id,
count(referral_id) as activations_count,
sum(coalesce(amount_earned, 0)) as amount_earned,
referred_at,
max(activated_at) as last_activated_at
from
agents
group by id, referred_at),
distinct_referrals_by_app_id
as
(select
distinct on(id), app_id as best_selling_app,
count(app_id) as best_selling_app_count
from agents
group by id, app_id
order by id, best_selling_app_count desc)
select *, dense_rank() over (order by best_selling_app_count desc) best_selling_app_rank
from distinct_referrals_by_id
inner join distinct_referrals_by_app_id
on (distinct_referrals_by_id.id = distinct_referrals_by_app_id.id);
I need a recommendation on how best to achieve this.
I am trying to generate another table from the two tables that has only unique values for referrals.id and returns as one of the columns the count for each apps as best_selling_app_count.
Your question is really complicated with a very complicated SQL query. However, the above is what looks like the actual question. If so, you can use:
select r.*,
a.app_id as most_common_app_id,
a.cnt as most_common_app_id_count
from referrals r left join
(select distinct on (a.referral_id) a.referral_id, a.app_id, count(*) as cnt
from activations a
group by a.referral_id, a.app_id
order by a.referral_id, count(*) desc
) a
on a.referral_id = r.id;
You have not explained the other columns that are in your result set.
Consider the following dataset:
+---------------------+
| ID | NAME | VALUE |
+---------------------+
| 1 | a | 0.2 |
| 1 | b | 8 |
| 1 | c | 3.5 |
| 1 | d | 2.2 |
| 2 | b | 4 |
| 2 | c | 0.5 |
| 2 | d | 6 |
| 3 | a | 2 |
| 3 | b | 4 |
| 3 | c | 3.6 |
| 3 | d | 0.2 |
+---------------------+
I'm tying to develop a sql select statement that returns the top or distinct ID where NAME 'a' and 'b' both exist and both of the corresponding VALUE's are >= '1'. Thus, the desired output would be:
+---------------------+
| ID | NAME | VALUE |
+---------------------+
| 3 | a | 2 |
+----+-------+--------+
Appreciate any assistance anyone can provide.
You can try to use MIN window function and some condition to make it.
SELECT * FROM (
SELECT *,
MIN(CASE WHEN NAME = 'a' THEN [value] end) OVER(PARTITION BY ID) aVal,
MIN(CASE WHEN NAME = 'b' THEN [value] end) OVER(PARTITION BY ID) bVal
FROM T
) t1
WHERE aVal >1 and bVal >1 and aVal = [Value]
sqlfiddle
This seems like a group by and having query:
select id
from t
where name in ('a', 'b')
having count(*) = 2 and
min(value) >= 1;
No subqueries or joins are necessary.
The where clause filters the data to only look at the "a" and "b" records. The count(*) = 2 checks that both exist. If you can have duplicates, then use count(distinct name) = 2.
Then, you want the minimum value to be 1, so that is the final condition.
I am not sure why your desired results have the "a" row, but if you really want it, you can change the select to:
select id, 'a' as name,
max(case when name = 'a' then value end) as value
you can use in and sub-query
select top 1 * from t
where t.id in
(
select id from t
where name in ('a','b')
group by id
having sum(case when value>1 then 1 else 0)>=2
)
order by id
I'm trying to find an efficient way to derive the column Expected below from only Id and State. What I want is for the number Expected to increase each time State is 0 (ordered by Id).
+----+-------+----------+
| Id | State | Expected |
+----+-------+----------+
| 1 | 0 | 1 |
| 2 | 1 | 1 |
| 3 | 0 | 2 |
| 4 | 1 | 2 |
| 5 | 4 | 2 |
| 6 | 2 | 2 |
| 7 | 3 | 2 |
| 8 | 0 | 3 |
| 9 | 5 | 3 |
| 10 | 3 | 3 |
| 11 | 1 | 3 |
+----+-------+----------+
I have managed to accomplish this with the following SQL, but the execution time is very poor when the data set is large:
WITH Groups AS
(
SELECT Id, ROW_NUMBER() OVER (ORDER BY Id) AS GroupId FROM tblState WHERE State=0
)
SELECT S.Id, S.[State], S.Expected, G.GroupId FROM tblState S
OUTER APPLY (SELECT TOP 1 GroupId FROM Groups WHERE Groups.Id <= S.Id ORDER BY Id DESC) G
Is there a simpler and more efficient way to produce this result? (In SQL Server 2012 or later)
Just use a cumulative sum:
select s.*,
sum(case when state = 0 then 1 else 0 end) over (order by id) as expected
from tblState s;
Other method uses subquery :
select *,
(select count(*)
from table t1
where t1.id < t.id and state = 0
) as expected
from table t;
This question already has answers here:
Oracle10g SQL pivot
(2 answers)
Closed 5 years ago.
I am transposing key value pairs from a table and facing an issue.
I am using Oracle 12C database.
Test data looks like this. table is tab1
+---------------------------+
| Name | VAL | ID | grp_id|
+---------------------------+
| a | 3 | 1 | 1 |
| b | 5 | 2 | 1 |
| c | 8 | 3 | 1 |
| c | 9 | 4 | 2 |
+---------------------------+
My expected result is
+-------------------------+
| grp_id| a | b | c |
+-------------------------+
| 1 | 3 | 5 | 8 |
| 2 | null | null | 9 |
+-------------------------+
What I did so far is
with t as(
select row_number() over (partition by grp_id order by grp_id) rn,
name,
grp_id,
lead(val,0) over (partition by grp_id order by grp_id) as a,
lead(val,1) over (partition by grp_id order by grp_id) as b,
lead(val,2) over (partition by grp_id order by grp_id) as c
from tab1 where grp_id in (1,2) and name in ('a', 'b','c')
)
select grp_id,a,b,c from t where rn=1;
When data is consistent and for all grp_id-s key value pairs are the same then this query works fine, But in case when some keys are missing for one grp_id then I get a result like the following which is wrong and not what I expect
+----------------------------+
| grp_id| a | b | c |
+----------------------------+
| 1 | 3 | 5 | 8 |
| 2 | 9 | null | null |
+----------------------------+
How can I improve the query to work correctly? And I want to avoid using pivot
I would do this using conditional aggregation:
select grp_id,
max(case when name = 'a' then val end) as a,
max(case when name = 'b' then val end) as b,
max(case when name = 'c' then val end) as c
from tab1
group by grp_id;
grp_id is already defined so I see no need for analytic functions.
I have a table with data like the following
key | A | B | C
---------------------------
1 | x | 0 | 1
2 | x | 2 | 0
3 | x | NULL | 4
4 | y | 7 | 1
5 | y | 3 | NULL
6 | z | NULL | 4
And I want to merge the rows together based on column A with largest primary key being the 'tie breaker' between values that are not NULL
Result
key | A | B | C
---------------------------
1 | x | 2 | 4
2 | y | 3 | 1
3 | z | NULL | 4
What would be the best way to achieve this assuming my data is actually 40 columns and 1 million rows with an unknown level of duplications?
Using ROW_NUMBER and conditional aggregation:
SQL Fiddle
WITH cte AS(
SELECT *,
rnB = ROW_NUMBER() OVER(PARTITION BY A ORDER BY CASE WHEN B IS NULL THEN 0 ELSE 1 END DESC, [key] DESC),
rnC = ROW_NUMBER() OVER(PARTITION BY A ORDER BY CASE WHEN C IS NULL THEN 0 ELSE 1 END DESC, [key] DESC)
FROM tbl
)
SELECT
[key] = ROW_NUMBER() OVER(ORDER BY A),
A,
B = MAX(CASE WHEN rnB = 1 THEN B END),
C = MAX(CASE WHEN rnC = 1 THEN C END)
FROM cte
GROUP BY A