Average of difference between 2 datetime fields then cast to time - google-bigquery

I am working in Google BigQuery.
I have a DeliveryDate and ShipDate field (both datetime). I am calculating the difference then averaging. My problem is that my data visualization software is having trouble picking up the date time format of, for example, '0-0-0 25:0:0'. I want to CAST or really any function to get just the time portion.
SELECT
CarrierName,
AVG((DeliveryDate - ShipDate)) AS AverageShipToDeliver
FROM
`jan2022floyd.floyd_jan22.leaf_Q4_Jan22`
GROUP BY
CarrierName
Unfortunately I cannot add a CAST function into the above because 'AverageShipToDeliver' is not recognized and I can't do calculations inside of it.

Try to use the date_diff function instead, it will return an integer that you should be able to work with more effectively. You'll likely need to calculate at the delivery label though then average up.
select CarrierName
, AVG(date_diff(DeliveryDate, ShipDate, DAY))
FROM `jan2022floyd.floyd_jan22.leaf_Q4_Jan22`
GROUP BY CarrierName
https://cloud.google.com/bigquery/docs/reference/standard-sql/date_functions#date_diff

Related

MS Access - Problems using variables in WHERE clause

I have a working query which takes too long to run. It is being used to populate an Access form field with a list of distinct contracts ordered by their start date.
The following query returns a list of distinct contract start dates for multiple commodities (which share contract start dates) where the contract start date (DELSTART) is greater or equal to the current date (PRICEDATE).
The function returndelivery returns a date attribute of the contract converted to a double, the function returnnumericdate just returns a double from a date (yyyymmdd).
SELECT DISTINCT (tblFuturesPrices.Period),
returnnumericdate(returndelivery([PERIOD],"S")) AS DELSTART,
ReturnNumericDate(Date()) AS PRICEDATE
FROM tblFuturesPrices
WHERE returnnumericdate(returndelivery([PERIOD],"S")) >= ReturnNumericDate(Date())
GROUP BY PERIOD
ORDER BY returnnumericdate(returndelivery([PERIOD],"S"));
Ideally I would like to refer to the variables DELSTART and PRICEDATE in the where clause but Access prompts for a variable value when I do so. I think the query takes longer than it should because I'm having to use my user defined functions numerous times.
The source table (tblFutures) contains prices for each commodity / contract for working days going back 6 months.
Thanks in advance.
I think the query takes longer than it should because I'm having to
use my user defined functions numerous times.
That's it. But you can reduce those functions:
returnnumericdate(returndelivery([PERIOD],"S")) >= ReturnNumericDate(Date())
will be no different from
returndelivery([PERIOD],"S") >= Date()
Don't know what returndelivery does.
Addendum:
Filter on the raw data and create a new function returndeliverydate that does the same as returndelivery except returns a Date value:
SELECT
tblFuturesPrices.Period,
returndeliverydate([PERIOD],"S") AS DELSTART,
Date() AS PRICEDATE
FROM
tblFuturesPrices
WHERE
returndeliverydate([PERIOD],"S") >= Date()
Save this query and use it as source in a new query:
Select Distinct
DELSTART,
PRICEDATE
FROM
YourQuery

Select and manipulate SQL data, DISTINCT and SUM?

Im trying to make a small report for myself to see how my much time I get inputed in my system every day.
The goal is to have my SQL to sum up the name, Total time worked and Total NG product found for one specific day.
In this order:
1.) Sort out my data for a specific 'date'. I.E 2016-06-03
2.) Present a DISTINCT value for 'operators'
3.) SUM() all time registered at this 'date' and by this 'operator' under 'total_working_time_h'
4.) SUM() all no_of_defects registered at this 'date' and by this 'operator' under 'no_of_defects'
date, operator, total_working_time_h, no_of_defects
Currently I get the data I want by using the Query below. But now I need both the DISTINCT value of the operator and the SUM of the information. Can I use sub-queries for this or should it be done by a loop? Any other hints where I can learn more about how to solve this?
If i run the DISTINCT function I don't get the opportunity to sum my data the way I try.
SELECT date, operator, total_working_time_h, no_of_defects FROM {$table_work_hours} WHERE date = '2016-06-03' "
Without knowing the table structure or contents, the following query is only a good guess. The bits to notice and work with are sum() and GROUP BY. Actually syntax will vary a bit depending on what RDBMS you are using.
SELECT
date
,operator
,SUM(total_working_time_h) AS total_working_time_h
,SUM(no_of_defects) AS no_of_defects
FROM {$table_work_hours}
WHERE date = '2016-06-03'
GROUP BY
date
,operator
(Take out the WHERE clause or replace it with a range of dates to get results per operator per date.)
I'm not sure why you are trying to do DISTINCT. You want to know the data, no of hours, etc for a specific date.
do this....
Select Date, Operator, 'SumWorkHrs'=sum(total_working_time_h),
'SumDefects'=sum(no_ofDefects) from {$table_work_hours}
Where date='2016-06-03'
Try this:
SELECT SUM(total_working_time) as total_working_time,
SUM(no_of_defects) as no_of_defects ,
DISTINCT(operator) AS operator FROM {$table_work_hours} WHERE
date = '2016-06-03'

How to Calculate Sum untill start of month of a given date in DAX

I would like to calculate Sum(QTY) until the start date of the month for a given date.
Basically I can calculate Sum(QTY) until given date in my measure like:
SumQTYTillDate:=CALCULATE(SUM([QTY]);FILTER(ALL(DimDateView[Date]);DimDateView[Date]<=MIN(DimDateView[Date])))
But I also would like to calculate Sum(QTY) for dates before 10/1/2015 - which is the first date of selected Date's month. I have changed above measure and used STARTOFMONTH function to find first day of the month for a given date like;
.......DimDateView[Date]<=STARTOFMONTH(MIN(DimDateView[Date]))))
but not avail, it gives me
"A function ‘MIN’ has been used in a True/False expression that is
used as a table filter expression. This is not allowed."
What am I missing? How can I use STARTOFMONTH function in my measure?
Thanks.
STARTOFMONTH() must take a reference to a column of type Date/Time. MIN() is a scalar value, not a column reference. Additionally, your measure wouldn't work, because STARTOFMONTH() is evaluated in the row context of your FILTER(). The upshot of all this is that you would get a measure which just sums [QTY] across the first of every month in your data.
The built in time intelligence functions tend to be unintuitive at best. I always suggest using your model and an appropriate FILTER() to get to what you want.
In your case, I'm not entirely sure what you're looking for, but I think you want the sum of [QTY] for all time before the start of the month that the date you've selected falls in. In this case it's really easy to do. Add a field to your date dimension, [MonthStartDate], which holds, for every date in the table, the date of the start of the month it falls in. Now you can write a measure as follows:
SumQTY=SUM(FactQTY[QTY])
SumQTYTilStartOfMonth:=
CALCULATE(
[SumQTY]
;FILTER(
ALL(DimDateView)
;DimDateView[Date] < MIN(DimDateView[MonthStartDate])
)
)

SQL Like function Broken? or Limited?

I am trying to use the LIKE function to get data with similar names. Everything looks fine but the data I get in return is missing some values when I get back more than ~20 rows of data.
I have a very basic query. I just want data that starts with Lab, ideally for the whole day, or at least 12 hours. The code below misses some data and I cannot discern a pattern for what it picks to skip.
SELECT History.TagName, DateTime, Value FROM History
WHERE History.TagName like ('Lab%')
AND Quality = 0
AND wwRetrievalMode = 'Full'
AND DateTime >= '20150811 6:00'
AND DateTime <= '20150811 18:00'
To give you an idea of the data I am pulling, I have Lab.Raw.NTU, Lab.Raw.Alk, Lab.Sett.NTU, etc. Most of the data should have values at 6am/pm, 10am/pm, and 2am/pm. Some have more, few have less, not important. When I change the query to be more specific (i.e. only 1 hour window or LIKE "Lab.Raw.NTU") I get all of my data. Currently, this will spit out data for all tags and I get both 6am data and 6pm data, but certain values will be missing such as Lab.Raw.NTU at 6pm. There seem to be other data that is missing if I change the window for the previous day or the night shift, so I don't think it has to be with the data itself. Something weird is going on with the LIKE function but I have no idea what.
Is there another way to get the tagnames that I want besides like? Such as Tagname > Lab and Tagname <= Labz? (that gives me an error, so I am thinking not)
Please help.
It appears that you are using the Like operator correctly; that could be a red herring. Check the data type of the DateTime field. If it is character based such as varchar you are doing string comparisons instead of date comparisons, which could cause unexpected results. Try doing an explicit cast to ensure they are compared as dates:
DateTime >= convert(datetime, '20150811 6:00')

PostgreSQL - GROUP BY timestamp values?

I've got a table with purchase orders stored in it. Each row has a timestamp indicating when the order was placed. I'd like to be able to create a report indicating the number of purchases each day, month, or year. I figured I would do a simple SELECT COUNT(xxx) FROM tbl_orders GROUP BY tbl_orders.purchase_time and get the value, but it turns out I can't GROUP BY a timestamp column.
Is there another way to accomplish this? I'd ideally like a flexible solution so I could use whatever timeframe I needed (hourly, monthly, weekly, etc.) Thanks for any suggestions you can give!
This does the trick without the date_trunc function (easier to read).
// 2014
select created_on::DATE from users group by created_on::DATE
// updated September 2018 (thanks to #wegry)
select created_on::DATE as co from users group by co
What we're doing here is casting the original value into a DATE rendering the time data in this value inconsequential.
Grouping by a timestamp column works fine for me here, keeping in mind that even a 1-microsecond difference will prevent two rows from being grouped together.
To group by larger time periods, group by an expression on the timestamp column that returns an appropriately truncated value. date_trunc can be useful here, as can to_char.