I have two tables. Data in the first table is:
ID Username
1 Dan
2 Eli
3 Sean
4 John
Second Table Data:
user_id Status_id
1 2
1 3
4 1
3 2
2 3
1 1
3 3
3 3
3 3
. .
goes on goes on
These are my both tables.
I want to find the frequency of individual users doing 'status_id'
My expected result is:
username status_id(1) status_id(2) status_id(3)
Dan 1 1 1
Eli 0 0 1
Sean 0 1 2
John 1 0 0
My current code is:
SELECT b.username , COUNT(a.status_id)
FROM masterdb.auth_user b
left outer join masterdb.xmlform_joblist a
on a.user1_id = b.id
GROUP BY b.username, b.id, a.status_id
This gives me the separate count but in a single row without mentioning which status_id each column represents
This is called pivot and it works in two steps:
extracts the data for the specific field using a CASE statement
aggregates the data on users, to make every field value lie on the same record for each user
SELECT Username,
SUM(CASE WHEN status_id = 1 THEN 1 END) AS status_id_1,
SUM(CASE WHEN status_id = 2 THEN 1 END) AS status_id_2,
SUM(CASE WHEN status_id = 3 THEN 1 END) AS status_id_3
FROM t2
INNER JOIN t1
ON t2.user_id = t1._ID
GROUP BY Username
ORDER BY Username
Check the demo here.
Note: This solution assumes that there are 3 status_id values. If you need to generalize on the amount of status ids, you would require a dynamic query. In any case, it's better to avoid dynamic queries if you can.
Related
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;
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
Good day all.
below is an image relating to what I am attempting to achieve.
In one table there is two fields one is an ID and one is a Type.
I figured a picture paints a thousand words, so check the below
I have tried a few things with case and other things but none worked.
There is a couple of things to note: We cannot use temporary tables, inserts or deletes due to certain limitations.
Data Sample:
ID Type
3 bad
2 zeal
4 tro
3 pol
2 tro
2 lata
4 wrong
3 dead
2 wrong
3 dead
4 wrong
3 lata
2 bad
2 zeal
First of all you need a table containing the type groups:
type typegroup
bad 1
tro 1
zeal 1
dead 2
lata 2
wrong 2
pol 3
Then join, group by type group in order to get one result line per type group and count.
select
tg.typegroup,
count(case when id = 2 then 1 end) as id2,
count(case when id = 3 then 1 end) as id3
count(case when id = 4 then 1 end) as id4
from typegroups tg
join mytable m on m.type = tg.type
group by tg.typegroup
order by tg.typegroup;
UPDATE: Of course you can create such table on-the-fly.
...
from
(
select 'bad' as type, 1 as typegroup
union all
select 'tro' as type, 1 as typegroup
union all
...
) tg
join mytable m on m.type = tg.type
...
And you can move this to a WITH clause if you prefer so.
I have 2 tables named user and statistics
user table has 3 columns: id, name and category
statistics table has 3 columns: id, idUser (relational), cal
something like this:
user
Id name category
1 name1 1
2 name2 2
3 name3 3
statistics
Id idUser cal
1 1 1
2 1 1
3 1 1
4 2 1
5 2 1
How can I apply a query that sum the cal column by each category of users and give me something like this:
category totalcal
1 3
2 2
3 0
You want to do a left join to keep all the categories. The rest is just aggregation:
select u.category, coalesce(sum(s.cal), 0) as cal
from users u left join
statistics s
on u.id = s.idUser
group by u.category;
Use LEFT JOIN to get 0 sum for the category=3:
SELECT
user.category
,SUM(statistics.cal) AS totalcal
FROM
user
LEFT JOIN statistics ON statistics.idUser = user.Id
GROUP BY
user.category
Here SUM would return NULL for category=3. To get 0 instead of NULL you can use COALESCE(SUM(statistics.cal), 0).
Suppose My Database is like this :
MemberName MemberID ResultsEligibilityID
Thuso 2 1
Thuso 2 1
Maubane 3 2
Maubane 3 1
CDeveloper 5 2
CDeveloper 5 2
Now is it possible to write a query to display (The Below output) based on this:
if both ResultsEligibilityID for a single Member is 1 then Eligibile,
Otherwise Non-Eligible.
OUTPUT
MemberName MemberID ResultsEligibilityID Results
Thuso 2 1 Eligible
Maubane 3 2 Non-Eligible
CDeveloper 5 2 Non-Eligible
Thanks in advance for the help.
Please try:
select
MemberName,
MemberID,
MAX(ResultsEligibilityID) ResultsEligibilityID ,
(case when sum(case when ResultsEligibilityID=1 then 1 else 0 end)= COUNT(*)
then 'Eligible' else 'Non-Eligible' end) Results
From
YourTable
group by MemberName,MemberID