I'm trying to go back and retrieve counts for the last 4 full months. This is an example of what I have so far:
SELECT datecolumn, Count(datacolumnA) AS CountOfdatacolumnA, datacolumnB
FROM tableA
WHERE datacolumnB='AA' AND datecolumn >= ADD_MONTHS(CURRENT_DATE, -4)
My results show the last four months plus the current month, October in this case. The problem is that June isn't showing the correct count for the entire month. I'm only getting a partial count for the month.
You need to adjust to the start of the month. You can do this by subtracting the day of the month to get the '0th' of the month and then adding 1 to get the first. (I think dates in teradata are decimals with the int part being number of days since an epoch)
Select
datecolumn,
Count(datacolumnA) As CountOfdatacolumnA,
datacolumnB
From
tableA
Where
datacolumnB='AA' And
datecolumn >=
add_months(current_date, -4)
- extract(day from add_months(current_date, -4)) + 1
Related
I'm trying to query a table comparing order numbers from last week (Sunday to Saturday) vs 2 weeks ago, and calculate percent change between the two. My thought process so far has been to group my date column by week, then use a lag function to pull last week and the previous week in to the same row. From there use basic arithmetic functions to calculate percent change. In practice, I haven't been able to get a working query, but I picture the table to look as follows:
Week
Orders
Orders - Previous Week
% Change
2023-02-05
5
10
-0.5
2023-01-29
10
2
+5.0
2023-01-29
2
Important to note that the days in last week should not change regardless of what day it is today (i.e not use today -7 days to calculate last week, and -14 days to calculate 2 weeks ago)
My query so far:
SELECT
min(date) as date,
orders,
coalesce(lag(order) over (order by (date), 0)) as Orders - Previous Week
FROM `table`
WHERE date BETWEEN '2023-01-01' AND current_date()
group by date_trunc(date, WEEK)
ORDER BY date desc
I realize I'm not using coalesce and my lag function correctly, but a bit lost on how to correct it
To calculate the percent change, you can use the following query:
sql
Copy code
SELECT
min(date) as Week,
sum(orders) as Orders,
coalesce(sum(lag(orders) over (order by date_trunc(date, WEEK))), 0) as "Orders - Previous Week",
(sum(orders) - coalesce(sum(lag(orders) over (order by date_trunc(date, WEEK))), 0)) / coalesce(sum(lag(orders) over (order by date_trunc(date, WEEK))), 0) as "% Change"
FROM `table`
WHERE date BETWEEN '2023-01-01' AND current_date()
group by date_trunc(date, WEEK)
ORDER BY Week desc
In this query, the sum function is used to aggregate the orders by week. The coalesce function is used to handle the case where there is no previous week data, and default to 0. The percent change calculation uses the same formula you described.
I have inherited a query from an old MS Access DB and cannot for the life of me figure out what was trying to be done in this date parameter function. I normally only use SQL and this seems a bit different. Can any one assist in describing what this logic is doing?
use pdx_sap_user
go
select po_number,
po_issue_date
from vw_po_header
where po_issue_date > getDate() And PO_issue_date < DateAdd("d",-1,DateAdd("m",8,DateAdd("d",-(Day(getDate())-1),getDate())))
You can de-obfuscate it a lot by using DateSerial:
where
po_issue_date > getDate() And
po_issue_date < DateSerial(Year(getDate()), Month(getDate()) + 8, 0)
First: there is no getDate() function in Access. Probably it should be Date() which returns the current date.
Now starting from the inner expression:
Day(Date()) returns the current day as an integer 1-31.
So in DateAdd("d", -(Day(Date())-1), Date()) from the current date are subtracted as many days as needed to return the 1st of the current month.
Then:
DateAdd("m", 8, DateAdd("d", -(Day(Date())-1), Date()))
adds 8 months to the the 1st of the current month returning the 1st of the month of the date after 8 months.
Finally:
DateAdd("d", -1,...)
subtracts 1 day from the date returned by the previous expression, returning the last day of the previous month of that date.
So if you run today 13-Sep-2019 this code, the result will be:
30-Apr-2020
because this is the last day of the previous month after 8 months.
I think the following:
Take the current date
Substract the current day of month -1 to get the first day of current month
Add 8 month to this
Substract 1 day to get the last day of the previous month
So it calculates some deadline in approx 8 months.
But I wonder how a PO issue date can be in the future...
I am trying to write an efficient query to get the sum of the previous 7 days worth of values from a relational DB table, and record each total against the final date in the 7 day period (e.g. the 'WeeklyTotals Table' in the example below). For example, in my WeeklyTotals query, I would like the value for February 15th to be 333, since that is the total sum of users from Feb 9th - Feb 15th, and so on:
I have a base query which gets me my previous weeks users for today's date (simplified for the sake of the example):
SELECT Date, Sum("Total Users")
FROM "UserRecords"
WHERE (dateadd(hour, -8, "UserRecords"."Date") BETWEEN
dateadd(hour, -8, sysdate) - INTERVAL '7 DAY' AND dateadd(hour, -8, sysdate);
The problem is, this only get's me the total for today's date. I need a query which will get me this information for the previous seven days.
I know I can make a view for each date (since I only need the previous seven entries) and join them all together, but that seems really inefficient (I'll have to create/update 7 views, and then do all the inner join operations). I am wondering if there's a more efficient way to achieve this.
Provided there are no gaps, you can use a running total with SUM OVER including the six previous rows. Use ROW_NUMBER to exclude the first six records, as their totals don't represent complete weeks.
select log_date, week_total
from
(
select
log_date,
sum(total_users) over (order by log_date rows 6 preceding) as week_total,
row_number() over (order by log_date) as rn
from mytable
where log_date > 0
)
where rn >= 7
order by log_date;
UPDATE: In case there are gaps, it should be
sum(total_users) over (order by log_date range interval '6' day preceding)
but I don't know whether PostgreSQL supports this already. (Moreover the ROW_NUMBER exclusion wouldn't work then and would have to be replaced by something else.)
Here's a a query that self joins to the previous 6 days and sums the value to get the weekly totals:
select u1.date, sum(u2.total_users) as weekly_users
from UserRecords u1
join UserRecords u2
on u1.date - u2.date < 7
and u1.date >= u2.date
group by u1.date
order by u1.date
You can use the SUM over Window function, with the expression using Date Part, of week.
Self joins are much slower than Window functions.
Alright so I am trying to retrieve data a field we will call DATE_OF_ENTRY and the field is like this.
Example DATE_OF_ENTRY Data
28-NOV-15
So I need to use this field in a script that will be running twice a month to pull certain records. Basically when it's the 16th day of the current month I want all the records from the 1st-15th to be pulled up. When I run this script on the 1st of the next month I want all the records from the 16th-End of last month.
What I am using now
WHERE ROUND(DATE_OF_ENTRY,'MM') = ROUND(sysdate-1,'MM') AND DATE_OF_ENTRY < trunc(sysdate)
The problem with this statement is that it works on the 1st for the 16th to End of the last month, but on the 16th it gets data from the prior month still.
Any help is appreciated!
Using TRUNC() function with MONTH parameter will get the first day of the month.
Using TRUNC() function with DATE_OF_ENTRY will remove the TIME part.
Use + operator to add days to a DATE
SELECT TRUNC(sysdate, 'MONTH') firstDay,
TRUNC(sysdate, 'MONTH') + 15 Day15,
*
FROM yourTable
WHERE TRUNC(DATE_OF_ENTRY) >= TRUNC(sysdate, 'MONTH')
AND TRUNC(DATE_OF_ENTRY) <= TRUNC(sysdate, 'MONTH') + 15
I currently have a simple sql script (in Oracle) that updates based a date range >='01JUN13'. I'm trying to modify this script to automatically update based on the last two years based on today's date. So the next month, I need the last two years of data greater than or equal to July 2013. Thanks.
It's not entirely clear from your question whether you want the date range to start from exactly two years ago, to the day , or from the start of the month.
Matching to the day:
select * from your_table
where date_col >= add_months(trunc(sysdate), -24)
/
Matching to the first day of the month:
select * from your_table
where date_col >= add_months(trunc(sysdate, 'MON'), -24)
/