Formatting the results of a query - sql

Let's say I have the following table:
first second
A 1
A 1
A 2
B 1
B 2
C 1
C 1
If I run the following query:
select first, second, count(second) from tbl group by first, second
It will produce a table with the following information:
first second count(second)
A 1 2
A 2 1
B 1 1
B 2 1
C 1 2
How can I write the query so that I am given the information with the options from the second column as columns and the values for those columns being the count like this:
first 1 2
A 2 1
B 1 1
C 2 0

You can use CASE:
SELECT "first",
SUM(CASE WHEN "second" = 1 THEN 1 ELSE 0 END) AS "1",
SUM(CASE WHEN "second" = 2 THEN 1 ELSE 0 END) AS "2"
FROM tbl
GROUP BY "first"

Related

SQL Query to get multiple resultant on single column

I have a table that looks something like this:
id name status
2 a 1
2 a 2
2 a 3
2 a 2
2 a 1
3 b 2
3 b 1
3 b 2
3 b 1
and the resultant i want is:
id name total count count(status3) count(status2) count(status1)
2 a 5 1 2 2
3 b 4 0 2 2
please help me get this result somehow, i can just get id, name or one of them at a time, don't know how to put a clause to get this table at once.
Here's a simple solution using group by and case when.
select id
,count(*) as 'total count'
,count(case status when 3 then 1 end) as 'count(status1)'
,count(case status when 2 then 1 end) as 'count(status3)'
,count(case status when 1 then 1 end) as 'count(status2)'
from t
group by id
id
total count
count(status3)
count(status2)
count(status1)
2
5
1
2
2
3
4
0
2
2
Fiddle
Here's a way to solve it using pivot.
select *
from (select status,id, count(*) over (partition by id) as "total count" from t) tmp
pivot (count(status) for status in ([1],[2],[3])) pvt
d
total count
1
2
3
3
4
2
2
0
2
5
2
2
1
Fiddle

Hive - Group by with respect to following values

I have a table with rows:
id
a
b
0
1
1
1
1
2
2
2
1
3
1
1
I need to get sum of field "b" values grouped by "a" with respect to changes in "a".
For my example i want to get:
a
b
1
3
2
1
1
1

Best way to by column and aggregation on another column

I want to create a rank column using existing rank and binary columns. Suppose for example a table with ID, RISK, CONTACT, DATE. The existing rank is RISK, say 1,2,3,NULL, with 3 being the highest. The binary-valued is CONTACT with 0,1 or FAILURE/SUCESS. I want to create a new RANK that will order by RISK once a certain number of successful contacts has been exceeded.
For example, suppose the constraint is a minimum of 2 successful contacts. Then the rank should be created as follows in the two instances below:
Instance 1. Three ID, all have a min of two successful contacts. In that case the rank mirrors the risk:
ID risk contact date rank
1 3 S 1 3
1 3 S 2 3
1 3 F 3 3
1 3 F 4 3
2 2 S 1 2
2 2 S 2 2
2 2 F 3 2
2 2 F 4 2
3 1 S 1 1
3 1 S 2 1
3 1 S 3 1
Instance 2. Suppose ID=1 has only one successful contact. In that case it is relegated to the lowest rank, rank=1, while ID=2 gets the highest value, rank=3, and ID=3 maps to rank=2 because it satisfies the constraint but has a lower risk value than ID=2:
ID risk contact date rank
1 3 S 1 1
1 3 F 2 1
1 3 F 3 1
1 3 F 4 1
2 2 S 1 3
2 2 S 2 3
2 2 F 3 3
2 2 F 4 3
3 1 S 1 2
3 1 S 2 2
3 1 S 3 2
This is SQL, specifically Hive. Thanks in advance.
Edit - I think Gordon Linoff's code does it correctly. In the end, I used three interim tables. The code looks like that:
First,
--numerize risk, contact
select A.* ,
case when A.risk = 'H' then 3
when A.risk = 'M' then 2
when A.risk = 'L' then 1
when A.risk is NULL then NULL
when A.risk = 'NULL' then NULL
else -999 end as RISK_RANK,
case when A.contact = 'Successful' then 1
else NULL end as success
Second,
-- sum_successes_by_risk
select A.* ,
B.sum_successes_by_risk
from T as A
inner join
(select A.person, A.program, A.risk, sum(a.success) as sum_successes_by_risk
from T as A
group by A.person, A.program, A.risk
) as B
on A.program = B.program
and A.person = B.person
and A.risk = B.risk
Third,
--Create table that contains only max risk category
select A.* ,
B.max_risk_rank
from T as A
inner join
(select A.person, max(A.risk_rank) as max_risk_rank
from T as A
group by A.person
) as B
on A.person = B.person
and A.risk_rank = B.max_risk_rank
This is hard to follow, but I think you just want window functions:
select t.*,
(case when sum(case when contact = 'S' then 1 else 0 end) over (partition by id) >= 2
then risk
else 1
end) as new_risk
from t;

SQL Server : how can I get difference between counts of total rows and those with only data

I have a table with data as shown below (the table is built every day with current date, but I left off that field for ease of reading).
This table keeps track of people and the doors they enter on a daily basis.
Table entrance_t:
id entrance entered
------------------------
1 a 0
1 b 0
1 c 0
1 d 0
2 a 1
2 b 0
2 c 0
2 d 0
3 a 0
3 b 1
3 c 1
3 d 1
My goal is to report on people and count entrances not used(grouping on people), but ONLY if they entered(entered=1).
So using the above table, I would like the results of query to be...
id count
----------
2 3
3 1
(id=2 did not use 3 of the entrances and id=3 did not use 1)
I tried queries(some with inner joins on two instances of same table) and I can get the entrances not used, but it's always for everybody. Like this...
id count
----------
1 4
2 3
3 1
How do I not display results id=1 since they did not enter at all?
Thank you,
You could use conditional aggregation:
SELECT id, count(CASE WHEN entered = 0 THEN 1 END) AS cnt
FROM entrance_t
GROUP BY id
HAVING count(CASE WHEN entered = 1 THEN 1 END) > 0;
DBFiddle Demo

How to update one table based on aggregate query form another table

Say I have two tables.
Table A
id
A_status
parent_id_B
Table B
id
B_status
So for each id in B can have many records in A.
Now my question is, I need to set B_status to 1 when all child entries in Table A with same parent_id_B has A_status =1, else set B_status = 2
Ex:
Table A:
id A_status parent_id_B
1 1 1
2 1 1
3 1 2
4 1 3
5 1 3
Table B:
id B_status
1 0
2 0
3 0
Expected result:
Table B:
id B_status
1 1
2 1
3 1
Now consider another scenario
Table A:
id A_status parent_id_B
1 1 1
2 1 1
3 2 2
4 2 3
5 1 3
Table B:
id B_status
1 0
2 0
3 0
Expected result:
Table B:
id B_status
1 1
2 2
3 2
I need this to work only on sqlite. Thanks
I believe this can be done like so:
UPDATE TableB
SET B_Status =
(SELECT MAX(A_Status) FROM TableA WHERE TableA.Parent_ID_B = TableB.ID);
SqlFiddle with your second case here
In a more general case (without relying on direct mapping of A's status, you can also use a CASE ... WHEN in the mapping:
UPDATE TableB
SET B_Status =
CASE WHEN (SELECT MAX(A_Status)
FROM TableA
WHERE TableA.Parent_ID_B = TableB.ID) = 1
THEN 1
ELSE 2
END;
Edit (in the case where there are more than the original number of states):
I believe you'll need to determine 2 facts about each row, e.g.
Whether there is are any rows in table A with a status other than 1 for each B
And there must at least be one row for the same B
Or, whether the count of rows of A in state 1 = the count of all rows in A for the B.
Here's the first option:
UPDATE TableB
SET B_Status =
CASE WHEN
EXISTS
(SELECT 1
FROM TableA
WHERE TableA.Parent_ID_B = TableB.ID
AND TableA.A_Status <> 1)
OR NOT EXISTS(SELECT 1
FROM TableA
WHERE TableA.Parent_ID_B = TableB.ID)
THEN 2
ELSE 1
END;
Updated Fiddle