Conditional SQL Query on Multiple Rows - mysql

I am trying to find out which customers have defaulted on their loans. I would like to query the dataset to find the User_id of customers who have not paid in the last 60 days, but and not sure how to implement this in SQL.
User_id Due_Date Loan_Amount Paid_Amount
1 2012-04-04 16:14:12 500 40
1 2012-05-04 16:14:12 500 40
1 2012-06-04 16:14:12 500 0
1 2012-07-04 16:14:12 500 0
1 2012-08-04 16:14:12 500 0
2 2012-02-15 03:30:55 2030 100
2 2012-03-15 03:30:55 2030 100
2 2012-04-15 03:30:55 2030 100
3 2012-01-03 12:24:42 777 10
3 2012-02-03 12:24:42 777 0
3 2012-03-03 12:24:42 777 0
3 2012-04-03 12:24:42 777 0
In pseudocode (shown in bold) would look something like this, but I can't seem to implement it in MySQL:
SELECT User_id from TABLE_NAME WHERE Loan_Amount > 0 AND [the value Paid_Amount has been null for over 60 days]
Desired Output:
Users 1 and 3 in the above query would be returned because they have not paid for three consecutive periods.
NOTE: Due_Date is a time stamp
Any ideas would be very much appreciated!

Looks like you can use the DATEDIFF(date1, date1) function to obtain a list of delinquent borrowers.
SELECT DISTINCT
user_id
FROM table_name n
JOIN (SELECT user_id, max(due_date) maxDate FROM table_name GROUP BY user_id) t
ON n.user_id = t.user_id
AND n.due_date = t.maxDate
WHERE
loan_amount > 0
AND paid_amount IS NULL
AMD DATEDIFF(due_date, getdate()) > 60

My previous query was wrong, try this
select distinct t1.User_id
from TABLE_NAME t1
inner join (
select ts1.User_id, sum(ts1.Paid_Amount) as Paid_Amount_Total
from TABLE_NAME ts1
group by ts1.User_id
) t2
on t1.User_id=t2.User_id and t1.Loan_Amount>t2.Paid_Amount_Total
)
where
t1.Loan_Amount > 0
and t1.User_id not in (
select ts2.User_id
from TABLE_NAME ts2
where ts2.Due_Date>=DATE_SUB(NOW(), INTERVAL 60 DAY) and ts2.Paid_Amount>0
)
t1, ts1, ts2 - are aliases for TABLE_NAME

Related

Creating an overdraft statement

I'm currently stuck on how to create a statement that shows daily overdraft statements for a particular council.
I have the following, councils, users, markets, market_transactions, user_deposits.
market_transaction run daily reducing user's account balance. When the account_balance is 0 the users go into overdraft (negative). When users make a deposit their account balance increases.
I Have put the following tables to show how transactions and deposits are stored.
if I reverse today's transactions I'm able to get what account balance a user had yesterday but to formulate a query to get the daily OD amount is where the problem is.
USERS
user_id
name
account_bal
1
Wells
-5
2
James
100
3
Joy
10
4
Mumbi
-300
DEPOSITS
id
user_id
amount
date
1
1
5
2021-04-26
2
3
10
2021-04-26
3
3
5
2021-04-25
4
4
5
2021-04-25
TRANSACTIONS
id
user_id
amount_tendered
date
1
1
5
2021-04-27
2
2
10
2021-04-26
3
3
15
2021-04-26
4
4
50
2021-04-25
The Relationships are as follows,
COUNCILS
council_id
name
1
a
2
b
3
c
MARKETS
market_id
name
council_id
1
x
3
2
y
1
3
z
2
MARTKET_USER_LINK
id
market_id
user_id
1
1
3
2
2
2
3
3
1
I'm running this SQL query to get the total amount users have spent and subtracting with the current user account balance.
Don't know If I can use this to figure out the account_balance for each day.
SELECT u.user_id, total_spent, total_deposits,m.council_id
FROM users u
JOIN market_user_link ul ON ul.user_id= u.user_id
LEFT JOIN markets m ON ul.market_id =m.market_id
LEFT JOIN councils c ON m.council_id =c.council_id
LEFT JOIN (
SELECT user_id, SUM(amount_tendered) AS total_spent
FROM transactions
WHERE DATE(date) BETWEEN DATE('2021-02-01') AND DATE(NOW())
GROUP BY user_id
) t ON t.user_id= u.user_id
ORDER BY user_id, total_spent ASC
// looks like this when run
| user_id | total_spent | council_id |
|-------------|----------------|------------|
| 1 | 50.00 | 1 |
| 2 | 2.00 | 3 |
I was hoping to reverse transactions and deposits done to get the account balance for a day then get the sum of users with an account balance < 0... But this has just failed to work.
The goal is to produce a query that shows daily overdraft (Only SUM the total account balance of users with account balance below 0 ) for a particular council.
Expected Result
date
council_id
o_d_amount
2021-04-24
1
-300.00
2021-04-24
2
-60.00
2021-04-24
3
-900.00
2021-04-25
1
-600.00
2021-04-25
2
-100.00
2021-04-25
3
-1200.00
This is actually not that hard, but the way you asked makes it hard to follow.
Also, your expected result should match the data you provided.
Edited: Previous solution was wrong - It counted withdraws and deposits more than once if you have more than one event for each user/date.
Start by having the total exchanged on each day, like
select user_id, date, sum(amount) exchanged_on_day from (
select user_id, date, amount amount from deposits
union all select user_id, date, -amount_tendered amount from transactions
) d
group by user_id, date
order by user_id, date;
What follows gets the state of the account only on days that had any deposits or withdraws.
To get the results of all days (and not just those with account movement) you just have to change the cross join part to get a table with all dates you want (like Get all dates between two dates in SQL Server) but I digress...
select dates.date, c.council_id, u.name username
, u.account_bal - sum(case when e.date >= dates.date then e.exchanged_on_day else 0 end) as amount_on_start_of_day
, u.account_bal - sum(case when e.date > dates.date then e.exchanged_on_day else 0 end) as amount_on_end_of_day
from councils c
inner join markets m on c.council_id=m.council_id
inner join market_user_link mul on m.market_id=mul.market_id
inner join users u on mul.user_id=u.user_id
left join (
select user_id, date, sum(amount) exchanged_on_day from (
select user_id, date, amount amount from deposits
union all select user_id, date, -amount_tendered amount from transactions
) d group by user_id, date
) e on u.user_id=e.user_id --exchange on each Day
cross join (select distinct date from (select date from deposits union select date from transactions) datesInternal) dates --all days that had a transaction
group by dates.date, c.council_id, u.name, u.account_bal
order by dates.date desc, c.council_id, u.name;
From there you can rearrange to get the result you want.
select date, council_id
, sum(case when amount_on_start_of_day<0 then amount_on_start_of_day else 0 end) o_d_amount_start
, sum(case when amount_on_end_of_day<0 then amount_on_end_of_day else 0 end) o_d_amount_end
from (
select dates.date, c.council_id, u.name username
, u.account_bal - sum(case when e.date >= dates.date then e.exchanged_on_day else 0 end) as amount_on_start_of_day
, u.account_bal - sum(case when e.date > dates.date then e.exchanged_on_day else 0 end) as amount_on_end_of_day
from councils c
inner join markets m on c.council_id=m.council_id
inner join market_user_link mul on m.market_id=mul.market_id
inner join users u on mul.user_id=u.user_id
left join (
select user_id, date, sum(amount) exchanged_on_day from (
select user_id, date, amount amount from deposits
union all select user_id, date, -amount_tendered amount from transactions
) d group by user_id, date
) e on u.user_id=e.user_id --exchange on each Day
cross join (select distinct date from (select date from deposits union select date from transactions) datesInternal) dates --all days that had a transaction
group by dates.date, c.council_id, u.name, u.account_bal
) result
group by date, council_id
order by date;
You can check it on https://www.db-fiddle.com/f/msScT6B5F7FjU2aQXVr2da/6
Basically the query maps users to councils, caculates periods of overdrafts for users, them aggregates over councils. I assume that starting balance is dated start of the month '2021-04-01' (it could be ending balance as well, see below), change it as needed. Also that negative starting balance counts as an overdraft. For simplicity and debugging the query is divided into a number of steps.
with uc as (
select distinct m.council_id, mul.user_id
from markets m
join market_user_link mul on m.market_id = mul.market_id
),
user_running_total as (
select user_id, date,
coalesce(lead(date) over(partition by user_id order by date) - interval 1 day, date) nxt,
sum(sum(s)) over(partition by user_id order by date) rt
from (
select user_id, date, -amount_tendered s
from transactions
union all
select user_id, date, amount
from deposits
union all
select user_id, se.d, se.s
from users
cross join lateral (
select date(NOW() + interval 1 day) d, 0 s
union all
select '2021-04-01' d, account_bal
) se
) t
group by user_id, date
),
user_overdraft as (
select user_id, date, nxt, least(rt, 0) ovd
from user_running_total
where date <= date(NOW())
),
dates as (
select date
from user_overdraft
union
select nxt
from user_overdraft
),
council__overdraft as (
select uc.council_id, d.date, sum(uo.ovd) total_overdraft, lag(sum(uo.ovd), 1, sum(uo.ovd) - 1) over(partition by uc.council_id order by d.date) prev_ovd
from uc
cross join dates d
join user_overdraft uo on uc.user_id = uo.user_id and d.date between uo.date and uo.nxt
group by uc.council_id, d.date
)
select council_id, date, total_overdraft
from council__overdraft
where total_overdraft <> prev_ovd
order by date, council_id
Really council__overdraft is quite usable, the last step just compacts output excluding intermidiate dates when overdraft is not changed.
With following sample data:
users
user_id name account_bal
1 Wells -5
2 James 100
3 Joy 10
4 Mumbi -300
deposits, odered by date, extra row added for the last date
id user_id amount date
3 3 5 2021-04-25
4 4 5 2021-04-25
1 1 5 2021-04-26
2 3 10 2021-04-26
5 3 73 2021-05-06
transactions, odered by date (note the added row, to illustrate running total in action)
id user_id amount_tendered date
5 4 50 2021-04-25
2 2 10 2021-04-26
3 3 15 2021-04-26
1 1 5 2021-04-27
4 3 17 2021-04-27
councils
council_id name
1 a
2 b
3 c
markets
market_id name council_id
1 x 3
2 y 1
3 z 2
market_user_link
id market_id user_id
1 1 3
2 2 2
3 3 1
4 3 4
the query ouput is
council_id
date
overdraft
1
2021-04-01
0
2
2021-04-01
-305
3
2021-04-01
0
2
2021-04-25
-350
2
2021-04-26
-345
2
2021-04-27
-350
3
2021-04-27
-7
3
2021-05-06
0
Alternatively, provided the users table is holding a closing (NOW()) balance, replace user_running_total CTE with the following code
user_running_total as (
select user_id, date,
coalesce(lead(date) over(partition by user_id order by date) - interval 1 day, date) nxt,
coalesce(sum(sum(s)) over(partition by user_id order by date desc
rows between unbounded preceding and 1 preceding), sum(s)) rt
from (
select user_id, date, amount_tendered s
from transactions
union all
select user_id, date, -amount
from deposits
union all
select user_id, se.d, se.s
from users
cross join lateral (
select date(NOW() + interval 1 day) d, account_bal s
union all
select '2021-04-01' d, 0
) se
) t
where DATE(date) between date '2021-04-01' and date(NOW() + interval 1 day)
group by user_id, date
),
This way the query starts with closing balance dated next date after now and rollouts a running total in the reverse order till '2021-04-01' as a starting date.
Output
council_id
date
overdraft
1
2021-04-01
0
2
2021-04-01
-260
3
2021-04-01
-46
2
2021-04-25
-305
3
2021-04-25
-41
2
2021-04-26
-300
3
2021-04-26
-46
2
2021-04-27
-305
3
2021-04-27
-63
3
2021-05-06
0
db-fiddle both versions

Write Query to display look like in image

The table provided shows all new users signing up on a specific date in the format YYYY-MM-DD.
Your query should output the change from one month to the next. Because the first month has no preceding month, your output should skip that row. Your output should look like the following table.
My table data
Table data:
ID DateJoined
1 2017-01-06
2 2017-01-12
3 2017-01-16
4 2017-01-25
5 2017-02-05
6 2017-02-07
7 2017-02-21
8 2017-03-05
9 2017-03-07
10 2017-03-14
11 2017-03-16
12 2017-03-25
13 2017-03-25
14 2017-03-25
15 2017-03-25
16 2017-03-26
17 2017-04-05
18 2017-04-14
19 2017-04-21
20 2017-05-07
23 2017-05-14
24 2017-05-16
25 2017-05-25
26 2017-05-25
27 2017-05-25
28 2017-05-25
Enter image description here
I want this output:
count all records from every month and subtract it from the next month record.
This is my query:
SELECT
MONTH(L.joindate),
COUNT(L.joindate) - COUNT(R.joindate),
MONTH(R.joindate),
COUNT(R.joindate)
FROM
userlog AS L
LEFT JOIN
userlog AS R
ON MONTH(R.joindate)= (SELECT MIN(MONTH(joindate)) FROM userlog WHERE MONTH(joindate) < MONTH(L.joindate))
GROUP BY (MONTH(L.joindate)),(MONTH(R.joindate));
Use lag(), available in MySQL 8.0:
select date_format(joindate, '%Y-%m-01') joinmonth,
count(*) - lag(count(*), 1, 0) over(order by date_format(joindate, '%Y-%m-01')) m2m
from userlog
group by joinmonth
Note that I changed the logic to truncate dates to the first of month to use date_format().
In earlier versions, you can use a correlated subquery:
select date_format(joindate, '%Y-%m-01') joinmonth,
count(*) - (
select count(*)
from userlog l1
where l1.joindate >= date_format(l.joindate, '%Y-%m-01') - interval 1 month
and l1.joindate < date_format(l.joindate, '%Y-%m-01')
) m2m
from userlog l
group by joinmonth
LIMIT 12 OFFSET 1
You need to use Lag. Also, since it says you need to skip the first row so I have used the not null condition. I believe this query should work.
select
Month,
MonthToMonthChange
from
(
select
m_name as Month,
(total_id - diff) as MonthToMonthChange
from
(
select
total_id,
m_name,
Lag(total_id, 1) OVER(
ORDER BY
m_num ASC
) AS diff
from
(
select
MonthNAME(DateJoined) m_name,
Month(DateJoined) m_num,
count(*) total_id
from
maintable
Group by
m_name,
m_num
) as first_subquery
) as second_subquery
) as final_query
where
MonthToMonthChange IS NOT NULL;
select
MONTHNAME(UL1.DateJoined) as MONTH,
count(UL1.DateJoined) -
(
select count(UL2.DateJoined)
from tablename UL2
where MONTH(UL2.DateJoined )=MONTH(UL1.DateJoined) -1
) as MonthToMonthChange
from tablename UL1
where Month(UL1.DateJoined)!=1
Group by MONTHNAME(UL1.DateJoined)
order by UL1.DateJoined ASC;
https://i.stack.imgur.com/BXXDb.png
I tried this and it worked
select date_format(DateJoined, CONCAT('%M')) as Month,
count(*) - lag(count(*), 1, 0) over(order by date_format(DateJoined, CONCAT('%m'))) MonthToMonthChange
from maintable_OKLOT
group by Month
limit 12 offset 1

Max() is taking quite long is there any alternate way to write this query?

I have written a MySQL query, which is working fine as per needs. What I'm trying to do is searching latest records by hours and mins.
For example:
id, date, value, ip
1 2020-04-22 21:10:14 10 123
2 2020-04-22 21:20:14 20 123
3 2020-04-23 15:26:14 30 123
4 2020-04-23 15:50:14 40 123
5 2020-04-23 18:30:14 50 123
6 2020-04-24 11:05:14 60 123
7 2020-04-24 11:15:14 70 123
So my query will return:
id, date, value
2 2020-04-22 21:20:14 20 123
4 2020-04-23 15:50:14 40 123
5 2020-04-23 18:30:14 50 123
7 2020-04-24 11:15:14 70 123
Here is my query:
FROM table_name
WHERE id IN (
SELECT MAX(id)
FROM table_name
WHERE ip = '12345'
GROUP BY HOUR(`date`), DATE(`date`)
)
ORDER BY id DESC;
My table has millions of records, I'm trying to figuring out a way through a query. Otherwise, I have another way to do it by Cron Jobs.
You could try a correlated subquery for filtering:
select t.*
from table_name t
where t.id = (
select max(t1.id)
from mytable t1
where
t1.ip = 12345
and t1.date >= date_format(t.date, '%Y-%m-%d %h:00:00')
and t1.date < date_format(t.date, '%Y-%m-%d %h:00:00') + interval 1 hour
)
For performance with this query, you need an index on (ip, date, id).

Select difference based on record having minimum and maximum date in MySql

Below is my table let's call account
**ID accountID score tracking_date
1 1 3 2014-09-25 00:01:05
2 2 4 2014-09-26 01:05:18
3 1 6 2014-09-27 09:23:05
4 2 9 2014-09-28 20:01:05
5 1 1 2014-09-28 23:21:34
6 3 7 2014-09-21 00:01:00
7 2 1 2014-09-22 01:45:24
8 2 9 2014-09-27 14:01:43
9 3 1 2014-09-24 22:01:27
I want to select record with max date and also the difference of score with the records having tracking_date as minimum for that accountId. So I want output like below
ID accountID score_with_maxdate diff_score_with_mindate max_tracking_date
1 1 1 -2 2014-09-28 23:21:34
2 2 9 8 2014-09-28 20:01:05
3 3 1 -6 2014-09-24 22:01:27
Any help?
Here is one option. We can self-join a subquery which finds both the min and max tracking dates, for each account, twice to your original table. This will bring in all metadata for those max tracking date records, including the scores.
SELECT
t1.accountID,
t2.score AS score_with_maxdate,
t2.score - t3.score AS diff_score_with_mindate,
t1.max_tracking_date
FROM
(
SELECT
accountID,
MAX(tracking_date) AS max_tracking_date,
MIN(tracking_date) AS min_tracking_date
FROM yourTable
GROUP BY accountID
) t1
INNER JOIN yourTable t2
ON t1.accountId = t2.accountID AND t2.tracking_date = t1.max_tracking_date
INNER JOIN yourTable t3
ON t1.accountId = t3.accountID AND t3.tracking_date = t1.min_tracking_date
ORDER BY
t1.accountID;
Demo
This is a somewhat tricky question. I think conditional aggregation is a convenient way to solve the problem:
select min(t.id) as id, t.accountId,
max(case when t.tracking_date = t2.max_td then t.score end) as score_with_maxdate,
max(case when t.tracking_date = t2.max_td then t.score
when t.tracking_date = t2.min_td then - t.score
end) as diff_score_with_mindate,
max(t.tracking_date) as max_tracking_date
from t join
(select t2.accountId, min(t2.tracking_date) as min_td, max(t2.tracking_date) as max_td
from t t2
group by t2.accountId
) t2
on t.accountId = t2.accountId
group by t.accountId;
Another hackish way of getting same results by using aggregate and string fucntion
select t.accountID,
t.score_with_maxdate,
t.score_with_maxdate - t.score_with_mindate score_with_maxdate,
t.max_tracking_date
from(
select accountID,
substring_index(group_concat(score order by tracking_date desc),',', 1) + 0 score_with_maxdate,
substring_index(group_concat(score order by tracking_date asc),',', 1) + 0 score_with_mindate,
max(tracking_date) max_tracking_date
from demo
group by accountID
) t
Demo
But i would suggest you to go with other solutions mentioned by Tim & Gordon

Mysql sum column according to another column

This is my table data from my Mysql Table
t_Id t_Type t_Date t_acd_Id t_acc_Id t_Amount t_Desc t_u_Id c_Id
------ ------ ---------- -------- -------- -------- ------ ------ --------
1 0 2016-01-26 266 29 400.00 1 1
2 0 2016-01-27 266 29 160.00 1 1
3 1 2016-01-28 29 266 83.30 1 1
4 2 2016-01-27 29 272 400.00 1 1
5 0 2016-01-27 266 272 300.00 1 1
6 1 2016-01-28 272 22 20.00 1 1
I Want my result like
accout_Id rec_Amount pay_Amount
------ ---------- ----------
29 483.30 560.00
where rec_Amount is sum of t_acd_Id and pay_Amount is sum of t_acc_Id
How to get this result?
My current query
SELECT
(SELECT SUM(t_Amount) FROM tbl_transactions WHEREt_acd_Id= 29) AS rec_Amount,
(SELECT SUM(t_Amount) FROM tbl_transactions WHEREt_acc_Id= 29) AS pay_Amount
FROM tbl_transactions
which gives multiple rows
This query only serves the above requirement (for single account). If you want to get result for all the accounts then you need to group the records by account.
Try this(It's based on your requirement):
SELECT CASE
WHEN t_acc_id = 29 THEN t_acc_id
WHEN t_acd_id = 29 THEN t_acd_id
END account_id,
Sum(CASE
WHEN t_acd_id = 29 THEN t_amount
ELSE 0
END) rec_Amount,
Sum(CASE
WHEN t_acc_id = 29 THEN t_amount
ELSE 0
END) pay_Amount
FROM tbl_transactions
WHERE t_acc_id = 29
OR t_acd_id = 29
can you try with this query? as i have checked it manually.
SELECT t4.t_acd_Id as accout_Id ,sum(t4.t_Amount) as rec_Amount, (SELECT SUM(t_Amount) from table4 WHERE t_acc_Id =t4.t_acd_Id) as pay_Amount FROM `table4` as t4 WHERE t4.t_acd_Id IN (29,266) GROUP BY t4.t_acd_Id
Thanks
The following query takes into account the possibility that a given idea might appear only in t_acd_Id or t_acc_Id, but not both. In this case, we would like to do a full outer join, but MySQL does not directly support this. Instead, the first subquery in my answer obtains all unique ID values. This is then LEFT JOINed to two other subqueries for each of the totals you want.
SELECT t1.accout_Id, t2.rec_Amount, t3.pay_Amount
FROM
(
SELECT DISTINCT t_acd_Id AS accout_Id FROM tbl_transactions
UNION
SELECT DISTINCT t_acc_Id AS accout_Id FROM tbl_transactions
) t1
LEFT JOIN
(
SELECT t_acd_Id AS accout_Id, SUM(t_acd_Id) AS rec_Amount
FROM tbl_transactions
GROUP BY t_acd_Id
) t2
ON t1.accout_Id = t2.accout_Id
LEFT JOIN
(
SELECT t_acc_Id AS accout_Id, SUM(t_acc_Id) AS pay_Amount
FROM tbl_transactions
GROUP BY t_acc_Id
) t3
ON t1.accout_Id = t3.accout_Id
Click the link below for a running demo:
SQLFiddle