Trying to use this query for a procedure where a client ask for a loan:
select loan_id,
CASE WHEN status = 'document_sent' then date ELSE NULL END as document_sent,
CASE WHEN status = 'document_rejected' then date ELSE NULL END as document_rejected
from table
and status in ('document_sent', 'document_rejected')
order by 2 asc, 3 asc
And this is the result:
loan_id
document_sent
doc_rejected
123
2021-03-01 14:52
123
2021-03-01 14:57
123
2021-03-01 15:33
123
2021-03-01 14:54
123
2021-03-01 15:00
123
2021-03-01 15:39
I would like to have something like this:
loan_id
document_sent
doc_rejected
123
2021-03-01 14:52
2021-03-01 14:54
123
2021-03-01 14:57
2021-03-01 15:00
123
2021-03-01 15:33
2021-03-01 15:39
Is it possible? Thanks
If we don't make any assumptions about the absence/presence of each type of record:
select
coalesce(a.loan_id,b.loan_id) as loan_id
, ds.date as document_sent
, dr.date as document_rejected
from
(select * from tbl where status='document_sent') ds
full outer join
(select * from tbl where status='document_rejected') dr
on ds.loan_id=dr.loan_id
If you know that one or the other status is always present, then it can be a little simplified (can be turned into left join), or if both records are expected to be there it can be simplified to:
select
a.loan_id
, ds.date as document_sent
, dr.date as document_rejected
from
tbl ds
inner join
tbl dr
on ds.loan_id=dr.loan_id
and ds.status='document_sent'
and dr.status='document_rejected'
If `full outer join is not available:
select
coalesce(a.loan_id,b.loan_id) as loan_id
, ds.date as document_sent
, dr.date as document_rejected
from
(select * from tbl where status='document_sent') ds
left join
(select * from tbl where status='document_rejected') dr
on ds.loan_id=dr.loan_id
union all
select
coalesce(a.loan_id,b.loan_id) as loan_id
, ds.date as document_sent
, dr.date as document_rejected
from
(select * from tbl where status='document_sent') ds
right join
(select * from tbl where status='document_rejected') dr
on ds.loan_id=dr.loan_id
where ds.loan_id is null
Thanks #nbk for pointing out.
You could also use MIN/MAX (although we don't want to find min/max of anything, we want to take advantage of their behaviour that 1.they accept dates, and 2. they ignore null values, 3.they are used with GROUP BY to group rows together):
select
loan_id
, min(case when status='document_sent'
then ds.date else NULL end) as document_sent
, min(case when status='document_rejected'
then ds.date else NULL end) as document_rejected
from
tbl
group by id
Related
I need to calculate the difference between odds based on the value in the 'updated' column at the moment I take odds where the updated value is a min and minus it from odds where the updated value is max. It works perfect but I've just realized that in some columns happens to be 0 sometimes and I was wondering if it's possible to select the minimum still based on the updated column and only values where higher than 0.
That's how the table looks like
fixture_id
H_odds
D_odds
A_odds
ev_tstamp
updated
120000
1.40
1.50
1.30
132000
12
120000
1.10
1.10
1.10
132000
11
120000
1.20
0
1.60
132000
10
And that's what I would like to get back
fixture_id
H_odds
D_odds
A_odds
ev_tstamp
updated
dif_h
dif_d
dif_a
120000
1.40
1.50
1.30
132000
12
0.2
0.4
-0.3
That's what I'm getting back at the moment
fixture_id
H_odds
D_odds
A_odds
ev_tstamp
updated
dif_h
dif_d
dif_a
120000
1.40
1.50
1.30
132000
12
0.2
1.5
-0.3
The code I'm using
select
t_max.*,
(t_max.H_odds - t_min.H_odds) as dif_h,
(t_max.D_odds - t_min.D_odds) as dif_d,
(t_max.A_odds - t_min.A_odds) as dif_a
from
(
select
fixture_id,
min(updated) min_updated,
max(updated) max_updated
from
test
group by
fixture_id
) as t1
join test as t_min on (t_min.fixture_id = t1.fixture_id and t_min.updated = t1.min_updated)
join test as t_max on (t_max.fixture_id = t1.fixture_id and t_max.updated = t1.max_updated)
Consider the following:
DROP TABLE IF EXISTS my_table;
CREATE TABLE my_table
(fixture_id INT NOT NULL
,updated INT NOT NULL
,outcome ENUM('Home win','Draw','Away win') NOT NULL
,odds DECIMAL(5,2) NOT NULL
,PRIMARY KEY(fixture_id,outcome,updated)
);
INSERT INTO my_table VALUES
(120,12,'Home win',1.40),
(120,11,'Home win',1.10),
(120,10,'Home win',1.20),
(120,12,'Draw',1.50),
(120,11,'Draw',1.10),
(120,12,'Away win',1.30),
(120,11,'Away win',1.10),
(120,10,'Away win',1.60);
Latest odds:
SELECT x.*
FROM my_table x
JOIN
( SELECT fixture_id
, outcome
, MAX(updated) min_updated
FROM my_table x
GROUP
BY fixture_id
, outcome
) y
ON y.fixture_id = x.fixture_id
AND y.outcome = x.outcome
AND y.min_updated = x.updated;
Earliest odds:
Earliest odds:
SELECT x.*
FROM my_table x
JOIN
( SELECT fixture_id
, outcome
, MIN(updated) min_updated
FROM my_table x
GROUP
BY fixture_id
, outcome
) y
ON y.fixture_id = x.fixture_id
AND y.outcome = x.outcome
AND y.min_updated = x.updated;
Delta:
SELECT a.*
, a.odds - b.odds delta
FROM
( SELECT x.*
FROM my_table x
JOIN
( SELECT fixture_id
, outcome
, MAX(updated) min_updated
FROM my_table x
GROUP
BY fixture_id
, outcome
) y
ON y.fixture_id = x.fixture_id
AND y.outcome = x.outcome
AND y.min_updated = x.updated
) a
JOIN
( SELECT x.*
FROM my_table x
JOIN
( SELECT fixture_id
, outcome
, MIN(updated) min_updated
FROM my_table x
GROUP
BY fixture_id
, outcome
) y
ON y.fixture_id = x.fixture_id
AND y.outcome = x.outcome
AND y.min_updated = x.updated
) b
ON b.fixture_id = a.fixture_id
AND b.outcome = a.outcome;
Result:
+------------+---------+----------+------+-------+
| fixture_id | updated | outcome | odds | delta |
+------------+---------+----------+------+-------+
| 120 | 12 | Home win | 1.40 | 0.20 |
| 120 | 12 | Draw | 1.50 | 0.40 |
| 120 | 12 | Away win | 1.30 | -0.30 |
+------------+---------+----------+------+-------+
This solution only works on MySQL 8+.
I would suggest window functions. The following treats each odds column separately . . . and it does not make any assumptions about the odds increasing or decreasing with each update:
select fixture_id, ev_tstamp, max(updated),
max(case when update = max_h_update then h_odds end) as max_h,
max(case when update = max_d_update then h_odds end) as max_d,
max(case when update = max_a_update then h_odds end) as max_a,
(max(case when update = max_h_update then h_odds end) -
max(case when update = min_h_update then h_odds end)
) as h_diff,
(max(case when update = max_d_update then d_odds end) -
max(case when update = min_d_update then d_odds end)
) as d_diff,
(max(case when update = max_a_update then a_odds end) -
max(case when update = min_a_update then a_odds end)
) as a_diff
from (select t.*,
max(case when h_odds <> 0 then update end) over (partition by fixture_id) as max_h_update,
min(case when h_odds <> 0 then update end) over (partition by fixture_id) as min_h_update,
max(case when d_odds <> 0 then update end) over (partition by fixture_id) as max_h_update,
min(case when d_odds <> 0 then update end) over (partition by fixture_id) as min_h_update,
max(case when a_odds <> 0 then update end) over (partition by fixture_id) as max_a_update,
min(case when a_odds <> 0 then update end) over (partition by fixture_id) as min_a_update
from test t
) t
group by fixture_id, ev_tstamp;
I just modify the code little bit to calculate the difference only for specific group of odds (avg) so it look like bellow. It worked just once though, it took over 15 seconds to process and the other times I tried it didn't work due to time out error. Just to clarify in my structure the market column is the 'outcome' column from your example.
explain SELECT a.*
, a.odds - b.odds delta
FROM
( SELECT x.*
FROM average_odds x
JOIN
( SELECT fix_id
, market
, MAX(updated) min_updated
FROM average_odds x where odds_type=avg
GROUP BY fix_id
, market
) y
ON y.fix_id = x.fix_id
AND y.market = x.market
AND y.min_updated = x.updated
) a
JOIN
( SELECT x.*
FROM average_odds x
JOIN
( SELECT fix_id
, market
, MIN(updated) min_updated
FROM average_odds x where odds_type=avg
GROUP BY fix_id
, market
) y
ON y.fix_id = x.fix_id
AND y.market = x.market
AND y.min_updated = x.updated
) b
ON b.fix_id = a.fix_id
AND b.market = a.market
ORDER BY `delta` ASC
That's the explain table
ID
S TYPE
table..
parti
type
pos_keys
KEY
key len
ref
rows
filtered
extra
1
PRIMARY
derived3>
null
all
null
null
null
null
17466
100.00
Using temporary; Using filesort
1
PRIMARY
x
null
ref
fix,fixi,market,updat
fix
4
y.fix_id
596
0.11
Using where
1
PRIMARY
x
null
ref
fix,fixi,market,updat
fix
4
y.fix_id
596
2.27
Using where
1
PRIMARY
derived5>
null
ref
auto_key0>
auto_key0>
31
y.fix_id,y.market,bobi.x.updated
10
100.00
using index
5
DERIVED
x
null
ref
boki
boki
4
const
17466
100.00
Using index condition; Using temporary; Using file...
3
DERIVED
x
null
ref
boki
boki
4
const
17466
100.00
Using index condition; Using temporary; Using file...
I have these 3 tables ( with these structure):
outreach
id url profile_id
------------------------------------------
40 www.google.com 2
41 www.yahoo.com 3
42 www.test.com 1
outreach_links
id outreach_id end_date status
-----------------------------------------------
1 41 2016-01-12 Pending
2 40 2016-03-12 Pending
3 40 2016-02-12 Approved
comments
id outreach_id name
----------------------------
1 40
2 40
3 40
and I have this Query:
select o.*,
SUM(if(ol.status = "Approved" and (ol.end_date > now() or end_date is null), 1, 0)) as cond1,
SUM(if(ol.status = "Pending" and (ol.end_date != now() or end_date is null), 1, 0)) as cond2,
SUM(if(ol.status = "Pending" and (ol.end_date < now()), 1, 0)) as cond3
from outreach o
left join outreach_links ol on ol.outreach_id = o.id
where o.profile_id=2
group by o.id
having (cond1 = 0 and cond2 = 0) or (cond1 = 0 and (cond2 = 1 and cond3 >=1)) order by ol.end_date desc
I am trying to fix this Query and make it also select the following:
1). ol.* ONLY if MAX(end_date) and
2). Count(id.comment) count all comments for that particular row
is that possible?
right now here is the output
+"id": "40"
+"profile_id": "2"
+"url": "http://www.google.com"
+"created_at": "2016-12-05 21:55:10"
+"updated_at": "2016-12-05 22:49:56"
+"cond1": "0"
+"cond2": "0"
+"cond3": "5"
I want to add
+"max_date": get me max of end_date and the whole row of the row highlighted
+"Count(comments)": get me all the comments count for this one which is 3
Thanks
Are you trying to get the latest update date? The following query should give you the latest updated date.
However, I do not understand what you are trying to get for cond1, cond2, cond3, and what should be populated as created_date, and updated_date? Can you please give definitions for these fields?
SELECT o.*, ol.*, COUNT(c.id)
FROM outreach o
LEFT JOIN outreach_links ol ON ol.outreach_id = o.id
LEFT JOIN comments c ON c.outreach_id = o.id
WHERE ol.id = (SELECT ol2.id
FROM outreach_links ol2
WHERE ol2.outreach_id = ol.outreach_id
ORDER BY ol2.end_date, ol2.id DESC
LIMIT 1)
OR ol.id IS NULL
GROUP BY o.id, ol.id
I have a table like this
PersonID Gender Age CreatedDate
================================
1 M 32 10/09/2011
2 F 33 10/09/2011
2 F 33 10/11/2011
1 M 32 10/11/2011
3 F 33 10/11/2011
I want to find Gender Count By Age with group by created date,The age range will be 30-34 and getting person will be distinctly.
Desired output should like this:
Gender AgeRange CreatedDate CountResult
================================
M 30_34 10/09/2011 1
F 30_34 10/09/2011 1
F 30_34 10/11/2011 1
So I tried this but couldtn help:
SELECT t.Gender,'30_34' AS AgeRange,t.CreatedDate,
SUM(CASE WHEN t.Age BETWEEN 30 AND 34 THEN 1 ELSE 0 END) AS CountResult,
FROM (
SELECT DISTINCT PersonID,Gender,Age,CreatedDate
FROM MyTable
GROUP PersonID,Gender,Age,CreatedDate
HAVING COUNT(PersonID)=1
) t
What can I do for solution?
Thanks
If you are want the earliest created date per personid this might do
drop table if exists mytable;
create table mytable(PersonID int, Gender varchar(1),Age int, CreatedDate date);
insert into mytable values
(1 , 'M', 32 , '2011-09-10'),
(2 , 'F', 33 , '2011-09-10'),
(2 , 'F', 33 , '2011-11-10'),
(1 , 'M', 32 , '2011-11-10'),
(3 , 'F', 33 , '2011-11-10');
select mt.gender,
mt.createddate,
sum(case when mt.age between 32 and 34 then 1 else 0 end) as Age32to34
from mytable mt
where createddate = (select min(mt1.createddate) from mytable mt1 where mt1.personid = mt.personid)
group by gender,mt.createddate
How about:
SELECT
Gender
, '30_34' AS AgeRange
, CreatedDate
, COUNT(*) AS CountResult
FROM MyTable A
JOIN (
SELECT PersonID, MIN(CreatedDate) MinCreatedDate
FROM MyTable GROUP BY PersonID
) B ON B.PersonID = A.PersonID AND B.MinCreatedDate = A.CreatedDate
WHERE Age BETWEEN 30 AND 34
GROUP BY Gender, CreatedDate
ORDER BY CreatedDate, Gender DESC
You would appear to want:
SELECT t.Gender, '30_34' AS AgeRange, t.CreatedDate,
COUNT(DISTINCT t.PersonId) AS CountResult
FROM MyTable
WHERE t.Age BETWEEN 30 AND 34
GROUP BY t.Gender, t.CreatedDate;
Why MySQL full outer join returns nulls?
Hi
I have the following data:
s_id,date,p_id,amount_sold
1, '2015-10-01', 1, 10
2, '2015-10-01', 2, 12
7, '2015-10-01', 1, 11
3, '2015-10-02', 1, 11
4, '2015-10-02', 2, 10
5, '2015-10-15', 1, 22
6, '2015-10-16', 2, 20
8, '2015-10-22', 3, 444
and i want my query to output something like this: (A = sum of amount_sold for p_id=1 for that date,B = sum of amount_sold for p_id=2 for that date)
date,A,B,Difference
'2015-10-01',21,12,9
'2015-10-02',11,10,1
'2015-10-15',22,0,22
'2015-10-01',0,20,-20
I tried with this query, but the order its returning is having NULLS and the output is wrong:
SELECT A.p_id,A.date,sum(A.amount_sold) A,B.Bs, (sum(A.amount_sold) - B.Bs) as difference FROM sales as A
LEFT JOIN (
SELECT SUM( amount_sold ) Bs,p_id,s_id, DATE
FROM sales
WHERE p_id =2
group by date
) as B ON A.s_id = B.s_id
where A.p_id=1 or B.p_id=2
group by A.date, A.p_id
UNION
SELECT A.p_id,A.date,sum(A.amount_sold) A,B.Bs, (sum(A.amount_sold) - B.Bs) as difference FROM sales as A
RIGHT JOIN (
SELECT SUM( amount_sold ) Bs,p_id,s_id, DATE
FROM sales
WHERE p_id =2
group by date
) as B ON A.s_id = B.s_id
where B.p_id=2
group by A.date, A.p_id
It returned:
p_id date A Bs difference
1 2015-10-01 21 NULL NULL
2 2015-10-01 12 12 0
1 2015-10-02 11 NULL NULL
2 2015-10-02 10 10 0
1 2015-10-15 22 NULL NULL
2 2015-10-16 20 20 0
What am i doing wrong here? and what is the correct way of doing it? any help would be appreciated.
A full join isn't needed. You can use conditional aggregation instead:
select
date,
sum(case when p_id = 1 then amount_sold else 0 end) a,
sum(case when p_id = 2 then amount_sold else 0 end) b,
sum(case when p_id = 1 then amount_sold else 0 end)
- sum(case when p_id = 2 then amount_sold else 0 end) difference
from sales
where p_id in (1,2)
group by date
I need a little help with an sql query.
I have a table with a format and data that looks like this:
id | applicant_id | application_status | status_time
1 | 1234 | received | 2013-05-06 15:00:00
1 | 1234 | pending | 2013-05-06 15:30:00
1 | 1234 | approved | 2013-05-06 16:00:00
The problem that I need to solve will have to print the following:
applicant_id | initial_status | initial_time | current_status | current_status_time
1234 | received | 2013-05-06 15:00:00 | approved | 2013-05-06 16:00:00
How could I go about accomplishing something like this, preferably only using joins and no nested selects?
The best way to approach this, in general, is to use the row_number() function. However, this requires a nested select:
select t.applicant_id,
max(case when seqnum_asc = 1 then status end) as initial_status,
max(case when seqnum_asc = 1 then status_time end) as initial_time,
max(case when seqnum_desc = 1 then status end) as current_status,
max(case when seqnum_desc = 1 then status_time end) as current_time
from (select t.*,
row_number() over (partition by applicant_id order by status_time) as seqnum_asc,
row_number() over (partition by applicant_id order by status_time desc) as seqnum_desc
from t
) t
group by t.applicant_id;
If your database did not support row_number(), I would recommend correlated subqueries, for readability. But those are also nested. Here is a solution in MySQL that meets your requirements:
select t.applicant_id,
substring_index(group_concat(status) separator ',' order by status_time), ',', 1) as initial_status,
min(status_time) as initial_time,
substring_index(group_concat(status) separator ',' order by status_time desc), ',', 1) as current_status,
max(status_time) as current_time
from t
group by t.applicant_id;
You did not state your database product, but you could use something like this on any database:
select t1.id,
t1.applicant_id,
max(case when t1.status_time = t2.mintime then t1.application_status end) initial_status,
max(case when t1.status_time = t2.mintime then t1.status_time end)initial_time,
max(case when t1.status_time = t2.maxTime then t1.application_status end) current_status,
max(case when t1.status_time = t2.maxTime then t1.status_time end) `current_time`
from yourtable t1
inner join
(
select id, applicant_id,
max(status_time) maxTime,
min(status_time) mintime
from yourtable
group by id, applicant_id
) t2
on t1.id = t2.id
and t1.applicant_id = t2.applicant_id
and
(
t1.status_time = t2.mintime
or t1.status_time = t2.maxtime
)
group by t1.id, t1.applicant_id;
See SQL Fiddle with Demo
SELECT a.application_id
, a.application_status as initial_status
, a.status_time as initial_time
, b.application_status as current_status
, b.status_time as current_status_time
FROM sample1 A
CROSS JOIN sample1 B
WHERE A.application_status = 'received'
and b. application_status = 'approved'
Assuming MS SQL (Transact-SQL), and that your source table is aptly named [SourceTable]. =)
SELECT DISTINCT
[Probe].applicant_id,
[LogMin].application_status [initial_status],
[LogMin].status_time [initial_time],
[LogMax].application_status [current_status],
[LogMax].status_time [current_status_time]
FROM (
SELECT MAX(status_time) [MaxDate],
MIN(status_time) [MinDate],
[applicant_id]
FROM [SourceTable]
GROUP BY [applicant_id]
) [Probe]
INNER JOIN [SourceTable] [LogMax]
ON [Probe].[applicant_id] = [LogMax].[applicant_id]
AND [Probe].[MaxDate] = [LogMax].[status_time]
INNER JOIN [SourceTable] [LogMin]
ON [Probe].[applicant_id] = [LogMin].[applicant_id]
AND [Probe].[MinDate] = [LogMin].[status_time]
Link to the SQLFiddle test is here.
Assuming that for one applicant_id you have one line for 'received' status and also one line for 'approved' status (as you listed in the question) you can use inline views to solve your issue:
select section1.applicant_id AS applicant_id, 'received' AS initial_status,
section1.status_time AS initial_time, 'approved' AS current_status,
section2.status_time AS current_status_time from
(select applicant_id, status_time from yourtable where application_status = 'received') section1,
(select applicant_id, status_time from yourtable where application_status = 'approved') section2
where section1.applicant_id = section2.applicant_id;
Try something like this.
select
t1.applicant_id,
t2.application_status initial_status,
t1.initial_time,
t3.application_status current_status,
t1.current_status_time
from
(select
applicant_id,
min(status_time) initial_time,
max(status_time) current_status_time
from
your_table
group by
applicant_id) t1
inner join your_table t2
on (t1.applicant_id = t2.applicant_id and t1.initial_time = t2.status_time)
inner join your_table t3
on (t1.applicant_id = t3.applicant_id and t1.current_status_time = t3.status_time)