i am currently making a monthly report using MySQL. I have a table named "monthly" that looks something like this:
id | date | amount
10 | 2009-12-01 22:10:08 | 7
9 | 2009-11-01 22:10:08 | 78
8 | 2009-10-01 23:10:08 | 5
7 | 2009-07-01 21:10:08 | 54
6 | 2009-03-01 04:10:08 | 3
5 | 2009-02-01 09:10:08 | 456
4 | 2009-02-01 14:10:08 | 4
3 | 2009-01-01 20:10:08 | 20
2 | 2009-01-01 13:10:15 | 10
1 | 2008-12-01 10:10:10 | 5
Then, when i make a monthly report (which is based by per month of per year), i get something like this.
yearmonth | total
2008-12 | 5
2009-01 | 30
2009-02 | 460
2009-03 | 3
2009-07 | 54
2009-10 | 5
2009-11 | 78
2009-12 | 7
I used this query to achieved the result:
SELECT substring( date, 1, 7 ) AS yearmonth, sum( amount ) AS total
FROM monthly
GROUP BY substring( date, 1, 7 )
But I need something like this:
yearmonth | total
2008-01 | 0
2008-02 | 0
2008-03 | 0
2008-04 | 0
2008-05 | 0
2008-06 | 0
2008-07 | 0
2008-08 | 0
2008-09 | 0
2008-10 | 0
2008-11 | 0
2008-12 | 5
2009-01 | 30
2009-02 | 460
2009-03 | 3
2009-05 | 0
2009-06 | 0
2009-07 | 54
2009-08 | 0
2009-09 | 0
2009-10 | 5
2009-11 | 78
2009-12 | 7
Something that would display the zeroes for the month that doesnt have any value. Is it even possible to do that in a MySQL query?
You should generate a dummy rowsource and LEFT JOIN with it:
SELECT *
FROM (
SELECT 1 AS month
UNION ALL
SELECT 2
…
UNION ALL
SELECT 12
) months
CROSS JOIN
(
SELECT 2008 AS year
UNION ALL
SELECT 2009 AS year
) years
LEFT JOIN
mydata m
ON m.date >= CONCAT_WS('.', year, month, 1)
AND m.date < CONCAT_WS('.', year, month, 1) + INTERVAL 1 MONTH
GROUP BY
year, month
You can create these as tables on disk rather than generate them each time.
MySQL is the only system of the major four that does have allow an easy way to generate arbitrary resultsets.
Oracle, SQL Server and PostgreSQL do have those (CONNECT BY, recursive CTE's and generate_series, respectively)
Quassnoi is right, and I'll add a comment about how to recognize when you need something like this:
You want '2008-01' in your result, yet nothing in the source table has a date in January, 2008. Result sets have to come from the tables you query, so the obvious conclusion is that you need an additional table - one that contains each month you want as part of your result.
Related
I am trying to create a view in postgreSQL with the requirements as below:
The table needs to show the same period last year data for every records.
Sample data:
date_sk | location_sk | division_sk | employee_type_sk | value
20180202 | 6 | 8 | 4 | 1
20180202 | 7 | 2 | 4 | 2
20190202 | 6 | 8 | 4 | 1
20190202 | 7 | 2 | 4 | 1
20200202 | 6 | 8 | 4 | 1
20200202 | 7 | 2 | 4 | 3
In the table, date_sk, location_sk, division_sk and employee_type_sk are super keys which form an unique record in the table.
You can check the required output as below:
date_sk | location_sk | division_sk | employee_type_sk | value | value_last_year
20180202 | 6 | 8 | 4 | 1 | NULL
20180203 | 7 | 2 | 4 | 2 | NULL
20190202 | 6 | 8 | 4 | 1 | 1
20190203 | 7 | 3 | 4 | 1 | NULL
20200202 | 6 | 8 | 4 | 1 | 1
20200203 | 7 | 3 | 4 | 3 | 1
The records start on 20180202, therefore, the data for the same period last year is unavailable. At the 4th record, there is a difference in division_sk comparing with the same period last year - hence, the head_count_last_year is NULL.
My current solution is to create a view from the sample data with an addition column as same_date_last_year then LEFT JOIN the same table. The SQL queries are below:
CREATE VIEW test_view AS
SELECT *,
CONCAT(LEFT(date_sk, 4) - 1, RIGHT(date_sk, 4)) AS same_date_last_year
FROM test_table
SELECT
test_view.date_sk,
test_view.location_sk,
test_view.division_sk,
test_view.employee_type_sk,
test_view.value,
test_table.value AS value_last_year
FROM test_view
LEFT JOIN test_table ON (test_view.same_date_last_year = test_table.date_sk)
We have a lot of data in the table. My solution above is unacceptable in terms of performance.
Is there a different query which yields the same result and might improve the performance ?
You could simply use a correlated subquery here which is likely best for performance:
select *,
(
select value from t t2
where t2.date_sk=t.date_sk - interval '1' year and
t2.location_sk=t.location_sk and
t2.division_sk=t.division_sk and
t2.employee_type_sk=t.employee_type_sk
) as value_last_year
from t
WITH CTE(DATE_SK,LOCATION_SK,DIVISION_SK,EMPLOYEE_TYPE_SK,VALUE)AS
(
SELECT CAST('20180202' AS DATE),6,8,4,1 UNION ALL
SELECT CAST('20180203'AS DATE),7,2,4,2 UNION ALL
SELECT CAST('20190202'AS DATE),6,8,4,1 UNION ALL
SELECT CAST('20190203'AS DATE),7,2,4,1 UNION ALL
SELECT CAST('20200202'AS DATE),6,8,4,1 UNION ALL
SELECT CAST('20200203'AS DATE),7,2,4,3
)
SELECT C.DATE_SK,C.LOCATION_SK,C.DIVISION_SK,C.EMPLOYEE_TYPE_SK,C.VALUE,
LAG(C.VALUE)OVER(PARTITION BY C.LOCATION_SK,C.DIVISION_SK,C.EMPLOYEE_TYPE_SK ORDER BY C.DATE_SK ASC)LAGG
FROM CTE AS C
ORDER BY C.DATE_SK ASC;
Could you please try if the above is suitable for you. I assume,DATE_SK is a date column or can be CAST to a date
I have a Teradata query that generates:
customer | order | amount | days_ago
123 | 1 | 50 | 2
123 | 1 | 50 | 7
123 | 2 | 10 | 19
123 | 3 | 100 | 35
234 | 4 | 20 | 20
234 | 5 | 10 | 10
With performance in mind, what’s the most efficient way to produce an output per customer where orders is the number of distinct orders a customer had within the last 30 days and total is the sum of the amount of the distinct orders regardless of how many days ago the order was placed?
Desired output:
customer | orders | total
123 | 2 | 160
234 | 2 | 30
Given your rules, maybe it takes two steps - de-duplicate first then aggregate:
SELECT customer,
SUM(CASE WHEN days_ago <=30 THEN 1 ELSE 0 END) AS orders,
SUM(amount) AS total
FROM
(SELECT customer, order, MAX-or-MIN(amount) AS amount, MIN-or-MAX(days_ago) AS days_ago
FROM your_relation
GROUP BY 1, 2) AS DistinctCustOrder
GROUP BY 1;
Current ratio of user is his last inserted ratio in table "Ratio History"
user_id | year | month | ratio
For example if user with ID 1 has two rows
1 | 2019 | 2 | 10
1 | 2019 | 3 | 15
his ratio is 15.
there is some slice from develop table
user_id | year | month | ratio
1 | 2018 | 7 | 10
2 | 2018 | 8 | 20
3 | 2018 | 8 | 30
1 | 2019 | 1 | 40
2 | 2019 | 2 | 50
3 | 2018 | 10 | 60
2 | 2019 | 3 | 70
I need a query which will select grouped rows by user_id and their last ratio.
As a result of the request, the following entries should be selected
user_id | year | month | ratio
1 | 2019 | 1 | 40
2 | 2019 | 3 | 70
3 | 2018 | 10 | 60
I tried use this query
select rh1.user_id, ratio, rh1.year, rh1.month from ratio_history rh1
join (
select user_id, max(year) as maxYear, max(month) as maxMonth
from ratio_history group by user_id
) rh2 on rh1.user_id = rh2.user_id and rh1.year = rh2.maxYear and rh1.month = rh2.maxMonth
but i got only one row
Use distinct on:
select distinct on (user_id) rh.*
from ratio_history rh
order by user_id, year desc, month desc;
distinct on is a very convenient Postgres extension. It returns one row for the key values in parentheses? Which row, it is the first row based on the sort criteria. Note that the sort criteria need to start with the expressions in parentheses.
I have SQL Query:
SELECT Date, Hours, Counts FROM TRANSACTION_DATE
Example Output:
Date | Hours | Counts
----------------------------------
01-Feb-2018 | 20 | 5
03-Feb-2018 | 25 | 3
04-Feb-2018 | 22 | 3
05-Feb-2018 | 21 | 2
07-Feb-2018 | 28 | 1
10-Feb-2018 | 23 | 1
If you can see, there are days that missing because no data/empty, but I want the missing days to be shown and have a value of zero:
Date | Hours | Counts
----------------------------------
01-Feb-2018 | 20 | 5
02-Feb-2018 | 0 | 0
03-Feb-2018 | 25 | 3
04-Feb-2018 | 22 | 3
05-Feb-2018 | 21 | 2
06-Feb-2018 | 0 | 0
07-Feb-2018 | 28 | 1
08-Feb-2018 | 0 | 0
09-Feb-2018 | 0 | 0
10-Feb-2018 | 23 | 1
Thank you in advanced.
You need to generate a sequence of dates. If there are not too many, a recursive CTE is an easy method:
with dates as (
select min(date) as dte, max(date) as last_date
from transaction_date td
union all
select dateadd(day, 1, dte), last_date
from dates
where dte < last_date
)
select d.date, coalesce(td.hours, 0) as hours, coalesce(td.count, 0) as count
from dates d left join
transaction_date td
on d.dte = td.date;
I need to create a form to summarize wage of each employees according to Date_start and Date_end that I selected.
I have 3 related tables.
tbl_labor
lb_id | lb_name | lb_OT ($/day) | If_social_sec
1 | John | 10 | yes
2 | Mary | 10 | no
tbl_production
pdtn_date | lb_id | pdtn_qty(pcs) | pd_making_id
5/9/12 | 1 | 200 | 12
5/9/12 | 1 | 40 | 13
5/9/12 | 2 | 300 | 12
7/9/12 | 1 | 48 | 13
13/9/12 | 2 | 220 | 14
15/9/12 | 1 | 20 | 12
20/9/12 | 1 | 33 | 14
21/9/12 | 2 | 55 | 14
21/9/12 | 1 | 20 | 12
tbl_pdWk_process
pd_making_id | pd_cost($/dozen) | pd_id
12 | 2 | 001
13 | 5 | 001
14 | 6 | 002
The outcome will look like this:
lb_name | no.working days | Total($)| OT payment | Social_sec($)| Net Wage |
John | 4 | 98.83 | 20 (2x10) | 15 | 103.83 (98.83+20-15)|
Mary | 2 | 160 | 10 (1x10) | 0 | 170 (160+10-0) |
My conditions are:
Wage are calculate between 2 dates that i specify eg. 5/9/12 - 20/9/12
Wage must be calculated from (pd_cost * pdtn_qty). However, pdtn_qty was kept in 'pieces' whereas pd_cost was kept in 'dozen'. Therefore the formula should be (pdtn_qty * pd_cost)/12
Add OT * no. of OT days that each worker did (eg. John had 2 OT days, Mary 1 OT day)
Total wages must be deducted eg. 15$ if If_social_sec are "TRUE"
Count no. of working days that each employees had worked.
I've tried but i couldn't merge all this condition together in one SQL statement, so could you please help me. Thank you.
OK this is really messy. Mainly because Access has no COUNT(DISTINCT ) option. So counting the working days is a mess. If you can skip that, then you can drop all the pdn1,pdn2,pdn3 stuff. But id does work. Couple of notes
1. I think your maths is not quite right in the example given, I make it like this:
2 I've used the IIF clause to simulate 2 OT for john, 1 for mary. You'll need to change that. Good luck.
select
lab.lb_name,
max(days),
sum(prod.pdtn_qty * pdWk.pd_cost / 12) as Total ,
max(lab.lb_OT * iif(lab.lb_id=1,2,1)) as OTPayment,
max(iif(lab.if_social_sec='yes' , 15,0 ) ) as Social_Sec,
sum(prod.pdtn_qty * pdWk.pd_cost / 12.00) +
max(lab.lb_OT * iif(lab.lb_id=1,2,1)) -
max(iif(lab.if_social_sec='yes' , 15,0 ) ) as NetWage
from
tbl_labor as lab,
tbl_production as prod,
tbl_pdWk_process as pdwk,
(select pdn2.lb_id, count(pdn2.lb_id) as days from
(select lb_id
from tbl_production pdn1
where pdn1.pdtn_date >= #9/5/2012#
and pdn1.pdtn_date <= #2012-09-20#
group by lb_id, pdtn_date ) as pdn2
group by pdn2.lb_id) as pdn3
where prod.pdtn_date >= #9/5/2012#
and prod.pdtn_date <= #2012-09-20#
and prod.lb_id = lab.lb_id
and prod.pd_making_id = pdwk.pd_making_id
and lab.lb_id = pdn3.lb_id
group by lab.lb_name
OK to add the items not in production table, you'll need to append something like this:
Union
select lab.lb_name,
0,
0,
max(lab.lb_OT * iif(lab.lb_id=1,2,1)) ,
max(iif(lab.if_social_sec='yes' , 15,0 ) ),0
from tbl_labor lab
where lb_id not in ( select lb_id from tbl_production where pdtn_date >= #2012-09-05# and pdtn_date <= #2012-09-20# )
group by lab.lb_name
Hope this helps.