I have the following table called vacations, where the employee number is displayed along with the start and end date of their vacations:
id_employe
start
end
1001
2020-12-24
2021-01-04
What I am looking for is to visualize the amount of vacation days that each employee had, but separating them by employee number, month, year and number of days; without taking into account non-business days (Saturdays, Sundays and holidays).
I have the following query, which manages to omit Saturday and Sunday from the posting:
SELECT id_employee,
EXTRACT(YEAR FROM t.Date) AS year,
EXTRACT(MONTH FROM t.Date) AS month,
SUM(WEEKDAY(`Date`) < 5) AS days
FROM (SELECT v.id_employee,
DATE_ADD(v.start, interval s.seq - 1 DAY) AS Date
FROM vacations v CROSS JOIN seq_1_to_100 s
WHERE DATE_ADD(v.start, interval s.seq - 1 DAY) <= v.end
ORDER BY v.id_employee, v.start, s.seq ) t
GROUP BY id_employee, EXTRACT(YEAR_MONTH FROM t.Date);
My question is, how could I in addition to skipping the weekends, also skip the holidays? I suppose that I should establish another table where the dates of those holidays are stored, but how could my * query * be adapted to perform the comparison?
If we consider that the employee 1001 took his vacations from 2020-12-24 to 2021-01-04 and we take Christmas and New Years as holidays, we should get the following result:
id_employee
month
year
days
1001
12
2020
5
1001
1
2021
1
After you have created a table that stores the holiday dates, then you probably can do something like this:
SELECT id_employee,
EXTRACT(YEAR FROM t.Date) AS year,
EXTRACT(MONTH FROM t.Date) AS month,
SUM(CASE WHEN h.holiday_date IS NULL THEN WEEKDAY(`Date`) < 5 END) AS days
FROM (SELECT v.id_employee,
DATE_ADD(v.start, interval s.seq - 1 DAY) AS Date
FROM vacations v CROSS JOIN seq_1_to_100 s
WHERE DATE_ADD(v.start, interval s.seq - 1 DAY) <= v.end
ORDER BY v.id_employee, v.start, s.seq ) t
LEFT JOIN holidays h ON t.date=h.holiday_date
GROUP BY id_employee, EXTRACT(YEAR_MONTH FROM t.Date);
Assuming that the holidays table structure would be something like this:
CREATE TABLE holidays (
id INT NOT NULL AUTO_INCREMENT PRIMARY KEY,
holiday_date DATE,
holiday_description VARCHAR(255));
Then LEFT JOIN it to your current query and change the SUM() slightly by adding CASE expression to check. If the ON t.date=h.holiday_date in the left join matches, there will be result of field h.holiday_date, otherwise it will be NULL, hence only the CASE h.holiday_date WHEN IS NULL .. will be considered.
Demo fiddle
Adding this solution compatible with both MariaDB and MySQL version that supports common table expression:
WITH RECURSIVE cte AS
(SELECT id_employee, start, start lvdt, end FROM vacations
UNION ALL
SELECT id_employee, start, lvdt+INTERVAL 1 DAY, end FROM cte
WHERE lvdt+INTERVAL 1 DAY <=end)
SELECT id_employee,
YEAR(v.lvdt) AS year,
MONTH(v.lvdt) AS month,
SUM(CASE WHEN h.holiday_date IS NULL THEN WEEKDAY(v.lvdt) < 5 END) AS days
FROM cte v
LEFT JOIN holidays h
ON v.lvdt=h.holiday_date
GROUP BY id_employee,
YEAR(v.lvdt),
MONTH(v.lvdt);
Related
I am trying to optimize the below query to help fetch all customers in the last three months who have a monthly order frequency +4 for the past three months.
Customer ID
Feb
Mar
Apr
0001
4
5
6
0002
3
2
4
0003
4
2
3
In the above table, the customer with Customer ID 0001 should only be picked, as he consistently has 4 or more orders in a month.
Below is a query I have written, which pulls all customers with an average purchase frequency of 4 in the last 90 days, but not considering there is a consistent purchase of 4 or more last three months.
Query:
SELECT distinct lines.customer_id Customer_ID, (COUNT(lines.order_id)/90) PurchaseFrequency
from fct_customer_order_lines lines
LEFT JOIN product_table product
ON lines.entity_id= product.entity_id
AND lines.vendor_id= product.vendor_id
WHERE LOWER(product.country_code)= "IN"
AND lines.date >= DATE_SUB(CURRENT_DATE() , INTERVAL 90 DAY )
AND lines.date < CURRENT_DATE()
GROUP BY Customer_ID
HAVING PurchaseFrequency >=4;
I tried to use window functions, however not sure if it needs to be used in this case.
I would sum the orders per month instead of computing the avg and then retrieve those who have that sum greater than 4 in the last three months.
Also I think you should select your interval using "month(CURRENT_DATE()) - 3" instead of using a window of 90 days. Of course if needed you should handle the case of when current_date is jan-feb-mar and in that case go back to oct-nov-dec of the previous year.
I'm not familiar with Google BigQuery so I can't write your query but I hope this helps.
So I've found the solution to this using WITH operator as below:
WITH filtered_orders AS (
select
distinct customer_id ID,
extract(MONTH from date) Order_Month,
count(order_id) CountofOrders
from customer_order_lines` lines
where EXTRACT(YEAR FROM date) = 2022 AND EXTRACT(MONTH FROM date) IN (2,3,4)
group by ID, Order_Month
having CountofOrders>=4)
select distinct ID
from filtered_orders
group by ID
having count(Order_Month) =3;
Hope this helps!
An option could be first count the orders by month and then filter users which have purchases on all months above your threshold:
WITH ORDERS_BY_MONTH AS (
SELECT
DATE_TRUNC(lines.date, MONTH) PurchaseMonth,
lines.customer_id Customer_ID,
COUNT(lines.order_id) PurchaseFrequency
FROM fct_customer_order_lines lines
LEFT JOIN product_table product
ON lines.entity_id= product.entity_id
AND lines.vendor_id= product.vendor_id
WHERE LOWER(product.country_code)= "IN"
AND lines.date >= DATE_SUB(CURRENT_DATE() , INTERVAL 90 DAY )
AND lines.date < CURRENT_DATE()
GROUP BY PurchaseMonth, Customer_ID
)
SELECT
Customer_ID,
AVG(PurchaseFrequency) AvgPurchaseFrequency
FROM ORDERS_BY_MONTH
GROUP BY Customer_ID
HAVING COUNT(1) = COUNTIF(PurchaseFrequency >= 4)
I have a table records like this in Athena, one user one row in a month:
month, id
2020-05 1
2020-05 2
2020-05 5
2020-06 1
2020-06 5
2020-06 6
Need to calculate the percentage=( users come both prior month and current month )/(prior month total users).
Like in the above example, users come both in May and June 1,5 , May total user 3, this should calculate a percentage of 2/3*100
with monthly_mau AS
(SELECT month as mauMonth,
date_format(date_add('month',1,cast(concat(month,'-01') AS date)), '%Y-%m') AS nextMonth,
count(distinct userid) AS monthly_mau
FROM records
GROUP BY month
ORDER BY month),
retention_mau AS
(SELECT
month,
count(distinct useridLeft) AS retention_mau
FROM (
(SELECT
userid as useridLeft,month as monthLeft,
date_format(date_add('month',1,cast(concat(month,'-01') AS date)), '%Y-%m') AS nextMonth
FROM records ) AS prior
INNER JOIN
(SELECT
month ,
userid
FROM records ) AS current
ON
prior.useridLeft = current.userid
AND prior.nextMonth = current.month )
WHERE userid is not null
GROUP BY month
ORDER BY month )
SELECT *, cast(retention_mau AS double)/cast(monthly_mau AS double)*100 AS retention_mau_percentage
FROM monthly_mau as m
INNER JOIN monthly_retention_mau AS r
ON m.nextMonth = r.month
order by r.month
This gives me percentage as 100 which is not right. Any idea?
Hmmm . . . assuming you have one row per user per month, you can use window functions and conditional aggregation:
select month, count(*) as num_users,
sum(case when prev_month = dateadd('month', -1, month) then 1 else 0 end) as both_months
from (select r.*,
cast(concat(month, '-01') AS date) as month_date,
lag(cast(concat(month, '-01') AS date)) over (partition by id order by month) as prev_month_date
from records r
) r
group by month;
I'm trying to pull this through in Postgres 11.8:
SELECT count(distinct e.id) counter_employees,
(SELECT count(distinct id) FROM employees
WHERE date_trunc('month',date_hired) = period AND company = 11
) hires,
FROM employees e
WHERE period IN (SELECT DISTINCT make_date(...) FROM amounts)
I cant figure out how to declare that the period the subquery should check is outside the subquery. Also, the period is not from a table but generated, so there is not a column in amounts to relate to the employees inside the subquery.
employee table:
id date_hired company
431 2020-01-03 11
422 2020-01-02 11
323 2020-02-03 11
amounts table:
payment_period amount company
202001 999 11
202002 999 11
For every payment period in amounts I want to get some data such as employee count and hires of that period:
period count hires
202001 5 1
202002 6 ...
One option uses aggregation and window functions. If you have hires for each month, then you can get the information directly from employees, like so:
select
date_trunc('month', date_hired) month_hired,
sum(count(*)) over(order by date_trunc('month', date_hired)) no_employees,
count(*) hires
from employees
group by date_trunc('month', date_hired)
On the other hand, if there are months without hires, then you could use generate_series() to create the list of months, then bring the employees with a left join, and aggregate:
select
d.month_hired,
sum(count(e.id)) over(order by d.month_hired) no_employees,
count(e.id) hires
from (
select generate_series(
date_trunc('month', min(date_hired)),
date_trunc('month', max(date_hired)),
interval '1' month
) month_hired
from employees
) d
left join employees e
on e.date_hired >= d.month_hired
and e.date_hired < d.month_hired + interval '1' month
group by d.month_hired
We could run another count for every period distilled from amounts, but that's expensive - unless there are only very few?
For more than a few, compute counts per period for the whole employees table, plus a running total. Then LEFT JOIN to it, should be pretty efficient:
SELECT mon AS period, e.mon_hired AS count, e.all_hired AS hires
FROM (
SELECT to_date(payment_period, 'YYYYMM') AS mon
FROM (SELECT DISTINCT payment_period FROM amounts) a0
) a
LEFT JOIN (
SELECT date_trunc('month', date_hired) AS mon
, count(*) AS mon_hired
, sum(count(*)) OVER (ORDER BY date_trunc('month', date_hired)) AS all_hired
FROM employees e
GROUP BY 1
) e USING (mon)
ORDER BY 1;
This assumes we can just count all employees hired so far to get the total number of hires. (Nobody ever gets fired.)
Works just fine as long as there are rows for every period. Else we need to fill in for the gaps. We can compute a complete grid, or default to the latest row in case of a missing month like this:
WITH e AS (
SELECT date_trunc('month', date_hired) AS mon
, count(*) AS mon_hired
, sum(count(*)) OVER (ORDER BY date_trunc('month', date_hired)) AS all_hired
FROM employees e
GROUP BY 1
)
SELECT mon AS period, ae.*
FROM (
SELECT to_date(payment_period, 'YYYYMM') AS mon
FROM (SELECT DISTINCT payment_period FROM amounts) a0
) a
LEFT JOIN LATERAL (
SELECT CASE WHEN e.mon = a.mon THEN e.mon_hired ELSE 0 END AS count -- ①
, e.all_hired AS hires
FROM e
WHERE e.mon <= a.mon
ORDER BY e.mon DESC
LIMIT 1
) ae USING (mon)
ORDER BY 1;
① If nothing changed for the month, we need to fall back to the last month with data. Take the total count from there, but the monthly count is 0.
We can run a window function over an aggregate on the same query level. See:
Group and count events per time intervals, plus running total
Related:
PostgreSQL: running count of rows for a query 'by minute'
Aside: don't omit the AS keyword for a column alias. See:
Date column arithmetic in PostgreSQL query
I have a schedule table for each month schedule. And this table also has days off within that month. I need a result set that will tell working days and off days for that month.
Eg.
CREATE TABLE SCHEDULE(sch_yyyymm varchar2(6), sch varchar2(20), sch_start_date date, sch_end_date date);
INSERT INTO SCHEDULE VALUES('201703','Working Days', to_date('03/01/2017','mm/dd/yyyy'), to_date('03/31/2017','mm/dd/yyyy'));
INSERT INTO SCHEDULE VALUES('201703','Off Day', to_date('03/05/2017','mm/dd/yyyy'), to_date('03/07/2017','mm/dd/yyyy'));
INSERT INTO SCHEDULE VALUES('201703','off Days', to_date('03/08/2017','mm/dd/yyyy'), to_date('03/10/2017','mm/dd/yyyy'));
INSERT INTO SCHEDULE VALUES('201703','off Days', to_date('03/15/2017','mm/dd/yyyy'), to_date('03/15/2017','mm/dd/yyyy'));
Using SQL or PL/SQL I need to split the record with Working Days and Off Days.
From above records I need result set as:
201703 Working Days 03/01/2017 - 03/04/2017
201703 Off Days 03/05/2017 - 03/10/2017
201703 Working Days 03/11/2017 - 03/14/2017
201703 Off Days 03/15/2017 - 03/15/2017
201703 Working Days 03/16/2017 - 03/31/2017
Thank You for your help.
Edit: I've had a bit more of a think, and this approach works fine for your insert records above - however, it misses records where there are not continuous "off day" periods. I need to have a bit more of a think and will then make some changes
I've put together a test using the lead and lag functions and a self join.
The upshot is you self-join the "Off Days" onto the existing tables to find the overlaps. Then calculate the start/end dates on either side of each record. A bit of logic then lets us work out which date to use as the final start/end dates.
SQL fiddle here - I used Postgres as the Oracle function wasn't working but it should translate ok.
select sch,
/* Work out which date to use as this record's Start date */
case when prev_end_date is null then sch_start_date
else off_end_date + 1
end as final_start_date,
/* Work out which date to use as this record's end date */
case when next_start_date is null then sch_end_date
when next_start_date is not null and prev_end_date is not null then next_start_date - 1
else off_start_date - 1
end as final_end_date
from (
select a.*,
b.*,
/* Get the start/end dates for the records on either side of each working day record */
lead( b.off_start_date ) over( partition by a.sch_start_date order by b.off_start_date ) as next_start_date,
lag( b.off_end_date ) over( partition by a.sch_start_date order by b.off_start_date ) as prev_end_date
from (
/* Get all schedule records */
select sch,
sch_start_date,
sch_end_date
from schedule
) as a
left join
(
/* Get all non-working day schedule records */
select sch as off_sch,
sch_start_date as off_start_date,
sch_end_date as off_end_date
from schedule
where sch <> 'Working Days'
) as b
/* Join on "Off Days" that overlap "Working Days" */
on a.sch_start_date <= b.off_end_date
and a.sch_end_date >= b.off_start_date
and a.sch <> b.off_sch
) as c
order by final_start_date
If you had a dates table this would have been easier.
You can construct a dates table using a recursive cte and join on to it. Then use the difference of row number approach to classify rows with same schedules on consecutive dates into one group and then get the min and max of each group which would be the start and end dates for a given sch. I assume there are only 2 sch values Working Days and Off Day.
with dates(dt) as (select date '2017-03-01' from dual
union all
select dt+1 from dates where dt < date '2017-03-31')
,groups as (select sch_yyyymm,dt,sch,
row_number() over(partition by sch_yyyymm order by dt)
- row_number() over(partition by sch_yyyymm,sch order by dt) as grp
from (select s.sch_yyyymm,d.dt,
/*This condition is to avoid a given date with 2 sch values, as 03-01-2017 - 03-31-2017 are working days
on one row and there is an Off Day status for some of these days.
In such cases Off Day would be picked up as sch*/
case when count(*) over(partition by d.dt) > 1 then min(s.sch) over(partition by d.dt) else s.sch end as sch
from dates d
join schedule s on d.dt >= s.sch_start_date and d.dt <= s.sch_end_date
) t
)
select sch_yyyymm,sch,min(dt) as start_date,max(dt) as end_date
from groups
group by sch_yyyymm,sch,grp
I couldn't get the recursive cte running in Oracle. Here is a demo using SQL Server.
Sample Demo in SQL Server
I am trying to get daily sum of sales from a google big-query table. I used following code for that.
select Day(InvoiceDate) date, Sum(InvoiceAmount) sales from test_gmail_com.sales
where year(InvoiceDate) = Year(current_date()) and
Month(InvoiceDate) = Month(current_date())
group by date order by date
From the above query it gives only the sum of sales daily which were in the table. There is a chance that some days do not have any sales. For those kind of situations, I need to get the date and sum should be 0. As an example, in every month should 30 0r 31 rows with sum of sales. Examples show below. 4th day of the month does not have a sales. So its sum should be 0.
date | sales
-----+------
1 | 259
-----+------
2 | 359
-----+------
3 | 45
-----+------
4 | 0
-----+------
5 | 156
Is it possible to do in Big-query? Basically date column should be a series from 1 - 28/29/30 or 31st depending on the month of the year
Generting a list of dates and then joining whatever table you need on top seems the easiest. I used the generate_date_array + unnest and it looks quite clean.
To generate a list of days (one day per row):
SELECT
*
FROM
UNNEST(GENERATE_DATE_ARRAY('2018-10-01', '2020-09-30', INTERVAL 1 DAY)) AS example
You can use below to generate on fly all dates in given range (in below example it is all dates from 2015-06-01 till CURRENT_DATE() - by changing those you can control which dates range to generate)
SELECT DATE(DATE_ADD(TIMESTAMP("2015-06-01"), pos - 1, "DAY")) AS calendar_day
FROM (
SELECT ROW_NUMBER() OVER() AS pos, *
FROM (FLATTEN((
SELECT SPLIT(RPAD('', 1 + DATEDIFF(TIMESTAMP(CURRENT_DATE()), TIMESTAMP("2015-06-01")), '.'),'') AS h
FROM (SELECT NULL)),h
)))
so, now - you can use it with LEFT JOIN with your table to have all dates accounted. See potential example below
SELECT
calendar_day,
IFNULL(sales, 0) AS sales
FROM (
SELECT DATE(DATE_ADD(TIMESTAMP("2015-06-01"), pos - 1, "DAY")) AS calendar_day
FROM (
SELECT ROW_NUMBER() OVER() AS pos, *
FROM (FLATTEN((
SELECT SPLIT(RPAD('', 1 + DATEDIFF(TIMESTAMP(CURRENT_DATE()), TIMESTAMP("2015-06-01")), '.'),'') AS h
FROM (SELECT NULL)),h
)))
) AS all_dates
LEFT JOIN (
SELECT DAY(InvoiceDate) DATE, SUM(InvoiceAmount) sales
FROM test_gmail_com.sales
WHERE YEAR(InvoiceDate) = YEAR(CURRENT_DATE()) AND
MONTH(InvoiceDate) = MONTH(CURRENT_DATE())
GROUP BY DATE
)
ON DATE = calendar_day
I wanna need to get previous months sales
Below gives all days of previous month
SELECT DATE(DATE_ADD(DATE_ADD(DATE_ADD(CURRENT_DATE(), -1, "MONTH"), 1 - DAY(CURRENT_DATE()), "DAY"), pos - 1, "DAY")) AS calendar_day
FROM (
SELECT ROW_NUMBER() OVER() AS pos, *
FROM (FLATTEN((
SELECT SPLIT(RPAD('', 1 + DATEDIFF(DATE_ADD(CURRENT_DATE(), - DAY(CURRENT_DATE()), "DAY"), DATE_ADD(DATE_ADD(CURRENT_DATE(), -1, "MONTH"), 1 - DAY(CURRENT_DATE()), "DAY")), '.'),'') AS h
FROM (SELECT NULL)),h
)))
Using the Standard SQL dialect and the generate_array function to simplify the code:
WITH serialnum AS (
SELECT
sn
FROM
UNNEST(GENERATE_ARRAY(0,
DATE_DIFF(DATE_ADD(DATE_TRUNC(CURRENT_DATE()
, MONTH)
, INTERVAL 1 MONTH)
, DATE_TRUNC(CURRENT_DATE(), MONTH)
, DAY) - 1)
) AS sn
), date_seq AS (
SELECT
DATE_ADD(DATE_TRUNC(CURRENT_DATE(), MONTH),
INTERVAL(sn) DAY) AS this_day
FROM
serialnum
)
SELECT
Day(InvoiceDate) date
, Sum(IFNULL(InvoiceAmount, 0)) sales
FROM
date_seq
LEFT JOIN
test_gmail_com.sales
ON
date_seq.this_day = DAY(test_gmail_com.sales.InvoiceDate)
WHERE
year(InvoiceDate) = Year(current_date())
and
Month(InvoiceDate) = Month(current_date())
GROUP BY
date
ORDER BY
date
;
UPDATE
Or, simpler still using the generate_date_array function:
WITH date_seq AS (
SELECT
GENERATE_DATE_ARRAY(DATE_TRUNC(CURRENT_DATE(), MONTH),
DATE_ADD(DATE_ADD(DATE_TRUNC(CURRENT_DATE(), MONTH)
, INTERVAL 1 MONTH)
, INTERVAL -1 DAY)
, INTERVAL 1 DAY)
AS this_day
)
SELECT
Day(InvoiceDate) date
, Sum(IFNULL(InvoiceAmount, 0)) sales
FROM
date_seq
LEFT JOIN
test_gmail_com.sales
ON
date_seq.this_day = DAY(test_gmail_com.sales.InvoiceDate)
WHERE
year(InvoiceDate) = Year(current_date())
and
Month(InvoiceDate) = Month(current_date())
GROUP BY
date
ORDER BY
date
;
For these purposes it is practical to have a 'calendar' table, a table that just lists all the days within a certain range. For your specific question, it would suffice to have a table with the numbers 1 to 31. A quick way to get this table is to make a spreadsheet with these numbers, save it as a csv file and import this file into BigQuery as a table.
You then left outer join your result set onto this table, with ifnull(sales,0) as sales.
If you want the number of days per month (28--31) to be right, you basically have two options. Either you create a proper calendar table that covers several years and that you join on using year, month and day. Or you use the simple table with numbers 1--31 and remove numbers based on the month and the year.
For Standard SQL
WITH
splitted AS (
SELECT
*
FROM
UNNEST( SPLIT(RPAD('',
1 + DATE_DIFF(CURRENT_DATE(), DATE("2015-06-01"), DAY),
'.'),''))),
with_row_numbers AS (
SELECT
ROW_NUMBER() OVER() AS pos,
*
FROM
splitted),
calendar_day AS (
SELECT
DATE_ADD(DATE("2015-06-01"), INTERVAL (pos - 1) DAY) AS day
FROM
with_row_numbers)
SELECT
*
FROM
calendar_day
ORDER BY
day DESC