I have 2 tables; employee and time. For time table, I want to take id information automatically from employee table and subtracting every employees' start date of work from employee table from system date. If result = 1 year plus, result will be automatically added to the time table.
employee.hire_date date /
time.year number
I want it to do this (time.year = sysdate - employee.hire_date) process automatically.
For example, the employee started on 21.01.2019. Today(21.01.2020) write '1' on time table year column automatically.
Thanks.
Create times as a view on the employees table.
Oracle Setup:
CREATE TABLE employees ( id, start_date ) AS
SELECT 1, DATE '2019-01-21' FROM DUAL UNION ALL
SELECT 2, DATE '2019-06-21' FROM DUAL UNION ALL
SELECT 3, DATE '2015-01-01' FROM DUAL;
Create View:
CREATE VIEW times ( id, years ) AS
SELECT id,
FLOOR( MONTHS_BETWEEN( SYSDATE, start_date ) / 12 )
FROM employees;
Output:
SELECT *
FROM times;
gives:
ID | YEARS
-: | ----:
1 | 1
2 | 0
3 | 5
db<>fiddle here
Related
I am working to get cumulative distinct count of uids on daily basis. My dataset consists dates and UserIDs active on that date. Example : Say there are 2 uids (235,2354) appeared on date 2022-01-01 and they also appeared on next day with new uid 125 (235,2354,125) on 2022-01-02 At this point i want store cumulative count to be 3 not 5 as (user id 235 and 2354 already appeared on past day ).
My Sample Data looks like as follows:
https://github.com/manish-tripathi/Datasets/blob/main/Sample%20Data.xlsx
enter image description here
and my output should look as follows:
enter image description here
Here's one way that seems to work, using your linked Excel sheet as the data source.
Create a new table:
Table 2 = DISTINCT('Table'[Date])
Add the columns:
MAU = CALCULATE(
DISTINCTCOUNT('Table'[User ID]),
'Table'[Date] <= EARLIER('Table 2'[Date]))
DAU = CALCULATE(DISTINCTCOUNT('Table'[User ID]),
'Table'[Date] = EARLIER('Table 2'[Date]))
Result from your Excel data
How to get a list of missing dates from a BigQuery table. For e.g. a table(test_table) is populated everyday by some job but on few days the jobs fails and data isn't written into the table.
Use Case:
We have a table(test_table) which is populated everyday by some job( a scheduled query or cloud function).Sometimes those job fail and data isn't available for those particular dates in my table.
How to find those dates rather than scrolling through thousands of rows.
The below query will return me a list of dates and ad_ids where data wasn't uploaded (null).
note: I have used MAX(Date) as I knew dates was missing in between my boundary dates. For safe side you can also specify the starting_date and ending_date incase data hasn't been populated in the last few days at all.
WITH Date_Range AS
-- anchor for date range
(
SELECT MIN(DATE) as starting_date,
MAX(DATE) AS ending_date
FROM `project_name.dataset_name.test_table`
),
day_series AS
-- anchor to get all the dates within the range
(
SELECT *
FROM Date_Range
,UNNEST(GENERATE_TIMESTAMP_ARRAY(starting_date, ending_date, INTERVAL 1 DAY)) AS days
-- other options depending on your date type ( mine was timestamp)
-- GENERATE_DATETIME_ARRAY or GENERATE_DATE_ARRAY
)
SELECT
day_series.days,
original_table.ad_id
FROM day_series
-- do a left join on the source table
LEFT JOIN `project_name.dataset_name.test_table` AS original_table ON (original_table.date)= day_series.days
-- I only want the records where data is not available or in other words empty/missing
WHERE original_table.ad_id IS NULL
GROUP BY 1,2
ORDER BY 1
Final output will look like below:
An Alternate solution you can try following query to get desired output:-
with t as (select 1 as id, cast ('2020-12-25' as timestamp) Days union all
select 1 as id, cast ('2020-12-26' as timestamp) Days union all
select 1 as id, cast ('2020-12-27' as timestamp) Days union all
select 1 as id, cast ('2020-12-31' as timestamp) Days union all
select 1 as id, cast ('2021-01-01' as timestamp) Days union all
select 1 as id, cast ('2021-01-04' as timestamp) Days)
SELECT *
FROM (
select TIMESTAMP_ADD(Days, INTERVAL 1 DAY) AS Days, TIMESTAMP_SUB(next_days, INTERVAL 1 DAY) AS next_days from (
select t.Days,
(case when lag(Days) over (partition by id order by Days) = Days
then NULL
when lag(Days) over (partition by id order by Days) is null
then Null
else Lead(Days) over (partition by id order by Days)
end) as next_days
from t) where next_days is not null
and Days <> TIMESTAMP_SUB(next_days, INTERVAL 1 DAY)),
UNNEST(GENERATE_TIMESTAMP_ARRAY(Days, next_days, INTERVAL 1 DAY)) AS days
Output will be as :-
I used the code above but had to restructure it for BigQuery:
-- anchor for date range - this will select dates from the source table (i.e. the table your query runs off of)
WITH day_series AS(
SELECT *
FROM (
SELECT MIN(DATE) as starting_date,
MAX(DATE) AS ending_date
FROM --enter source table here--
---OPTIONAL: filter for a specific date range
WHERE DATE BETWEEN 'YYYY-MM-DD' AND YYYY-MM-DD'
),UNNEST(GENERATE_DATE_ARRAY(starting_date, ending_date, INTERVAL 1 DAY)) as days
-- other options depending on your date type ( mine was timestamp)
-- GENERATE_DATETIME_ARRAY or GENERATE_DATE_ARRAY
)
SELECT
day_series.days,
output_table.date
FROM day_series
-- do a left join on the output table (i.e. the table you are searching the missing dates for)
LEFT JOIN `project_name.dataset_name.test_table` AS output_table
ON (output_table.date)= day_series.days
-- I only want the records where data is not available or in other words empty/missing
WHERE output_table.date IS NULL
GROUP BY 1,2
ORDER BY 1
I am trying to create a measure that calculates (a/qty)*100 for each month,
where qty commes from Delivery table (generated with an R script)
month qty
<date> <dbl>
1 2019-02-01 1
2 2019-03-01 162
3 2019-04-01 2142
4 2019-05-01 719
And a comes from a table TABLE_A that has been created within Power BI that looks like this :
Client Date a
x 2019-03-07 3
x 2019-04-14 7
y 2019-03-12 2
So far, I managed to calculate that value overall with the following measure formula :
MEASURE = CALCULATE( (Sum(TABLE_A[a])/sum(Delivery[qty]))*100)
The issue I have is that I would need this measure monthly (i.e. join the tables on month) without explicitly defining a link between the tables in the PowerBI model.
For each row in TABLE_A you need to look up the corresponding qty in Delivery, so try something along these lines:
MEASURE =
DIVIDE(
SUM( TABLE_A[a] ),
SUMX(
TABLE_A,
LOOKUPVALUE(
Delivery[qty],
Delivery[month], EOMONTH( TABLE_A[Date], -1 ) + 1
)
)
) * 100
The formula EOMONTH( TABLE_A[Date], -1 ) returns the end of the previous month relative to that date and adding 1 day to that to get the start of the current month for that date.
I have a report page which contains tables about cars and bikes. Each of them is a separate table like:
Cars
Id | CarName | Time1
Bikes
Id | BikeName | Time2
There are no relationships between these tables however they must be displayed in same page. How can i use a Slicer or a Timeline 2.0.1 to manipulate all dashboards simultaneously by just filtering once the date?
I.e. If i select interval between 01/01/19-02/02/19 it will filter the Cars by field Time1 and the Bikes by Time2 and display the dashboards accordingly?
Thanks so much!
Build a CalendarTable and link both tables bikes and cars to it. You may find lots of propositions of CalendarTables. Then make slicer on CalendarTable. Beware not to make slicer on your fact tables bikes or cars.
There are more advantages to using CalendarTable then just the possibility of filtering multiple tables. I would use CalendarTable even with a single table because it contains complete list of days - your bike table may not - and that is why time intelligence functions work properly. And mind the performance - slicing small and unique CalendarTable is faster then big fact tables.
Here is an example of simple CalendarTable. Choose in menu Modeling / New Table:
Calendar =
GENERATE (
CALENDAR (
DATE ( 2016, 1, 1 ),
DATE ( 2020, 12, 31 )
),
VAR CurrentDay = [Date]
VAR day = DAY ( CurrentDay )
VAR month = MONTH ( CurrentDay )
VAR year = YEAR ( CurrentDay )
VAR YM_text = FORMAT ( [Date], "yyyy-MM" )
RETURN
ROW (
"day" , day,
"month" , month,
"year" , year,
"YM_text" , YM_text
)
)
Set up min and max date. Here from 2016-01-01 to 2020-12-31.
I have a requirement where I have a data like this,
Date Name Age
1-1-2018 A 1
2-2-2018 B 1
3-3-2018 B 1
6-6-2018 C 2
7-7-2018 B 6
I am trying to give a slicer to the user to select the required number of months from the last month.
So to do that, I am using a calculated column like this:
Month Year = DATEDIFF((Table1[Date]), TODAY(), MONTH) + 1
So that changes the data to something like this:
Date Name Age MonthYear
1-1-2018 A 1 7
2-2-2018 B 1 6
3-3-2018 B 1 5
6-6-2018 C 2 2
7-7-2018 B 6 1
The user selects the Month Year from the Slicer.
For example, when he selects 2, I want to display the last 2 months records in the table.
Expected Output:
Date Name Age
6-6-2018 C 2
7-7-2018 B 6
This works for me if I hardcode it like this:
Calculated Table = CALCULATETABLE(Table1,
FILTER(Table1, OR(Table1[MonthYear] > 2, Table1[MonthYear] = 2)))
But it fails when I try to pass the value in the place of 2 dynamically through a measure using SelectedValue function.
Calculated columns and calculated tables cannot reference a slicer value since they are only computed when you load your data.
If you want to apply this filtering to a visual, I'd suggest creating a separate table for your slicer. For example, you could use Months = GENERATESERIES(1,12) and then rename the column Months as well.
Use the Months[Months] column for your slicer and then create a measure which references it to filter your table/matrix visual.
Filter = IF(SELECTEDVALUE(Months[Months]) >= MAX(Table1[Month Year]), 1, 0)
Then use that measure in your Visual level filters box: