Hello I'm stuck trying to calculate the difference in time between each transaction for each ID.
The data looks like
Customer_ID | Transaction_Time
1 00:30
1 00:35
1 00:37
1 00:38
2 00:20
2 00:21
2 00:23
I'm trying to get the result to look something like
Customer_ID | Time_diff
1 5
1 2
1 1
2 1
2 2
I would really appreciate any help.
Thanks
Most databases support the LAG() function. However, the date/time functions can depend on the database. Here is an example for SQL Server:
select t.*
from (select t.*,
datediff(second,
lag(transaction_time) over (partition by customer_id order by transaction_time),
transaction_time
) as diff
from t
) t
where diff is not null;
The logic would be similar in most databases, although the function for calculating the time difference varies.
Related
I'm attempting to calculate average number of days between a customer's 1st and 3rd purchase, but struggling to get the data ordered in a way that will allow me to calculate.
I currently have the below data table. (Note: Order sequence number refers to the number order for that customer.)
Order Date
Customer Number
Order Sequence Number
2020-09-20
1
1
2021-01-20
1
2
2021-01-21
1
3
2020-10-01
2
1
2020-08-06
3
1
2020-09-06
3
2
2020-09-09
3
3
I've been trying to get the data to look like the following table. [To then be able to calculate datediff on the last two columns.]
Customer Number
Order Count
First Order Date
Third Order Date
1
3
2020-09-20
2021-01-21
2
1
2020-10-01
Null
3
3
2020-08-06
2020-09-09
I've completely messed up the code, but here's what I've been trying.
CREATE TABLE X2 as
SELECT
customer_number,
max(order_sequence_number) as order_count,
CASE
WHEN order_sequence_number = 1 then order_date
ELSE null
END as first_order_date,
CASE
WHEN order_sequence_number = 3 then order_date
ELSE null
END as third_order_date
FROM X1
GROUP BY customer_number;
Can someone please tell me what I'm missing? Thanks in advance!
You are on the right track but you need aggregation functions:
SELECT customer_number,
max(order_sequence_number) as order_count,
MAX(CASE WHEN order_sequence_number = 1 THEN order_date END) as first_order_date,
MAX(CASE WHEN order_sequence_number = 3 THEN order_date END) as third_order_date
FROM X1
GROUP BY customer_number;
To get the difference in days, you would just subtract the two expressions using whatever date arithmetic is supported in your database.
I am working on an accounting system in which there is a way to revert transactions which are made by mistake.
There are processes which run on invoices which generate transactions.
One process can generate multiple transactions for an invoice. There can be multiple processes which can be run on an invoice.
The schema looks as under:
Transactions
========================================================
Id | InvoiceId | InvoiceProcessType | Amount | CreatedOn
1 1 23 10.00 Today
2 1 23 13.00 Today
3 1 23 17.00 Yesterday
4 1 23 32.00 Yesterday
Now 1 and 2 happened together and 3 and 4 happened together and I want to revert the latter (3,4), what would be a possible solution to group them.
One possible solution is to add a column ProcessCount which is incremented on every process.
The new schema would look as under.
Transactions
==============================================================================
Id | InvoiceId | InvoiceProcessType | Amount | CreatedOn | ProcessCount
1 1 23 10.00 Today 1
2 1 23 13.00 Today 1
3 1 23 17.00 Yesterday 2
4 1 23 32.00 Yesterday 2
Is there any other way I can implement this ?
TIA
If you are basing the batching on an arbitrary time frame between the createdon date/time values, then you can use lag() and a cumulative sum. For instance, if two rows are in the same batch if they are within an hour, then:
select t.*,
sum(case when prev_createdon > dateadd(hour, -1, createdon) then 0 else 1 end) over
(partition by invoiceid order by createdon, id) as processcount
from (select t.*,
lag(createdon) over (partition by invoiceid order by createdon, id) as prev_createdon
from transactions t
) t;
That said, it would seem that your processing needs to be enhanced. Each time the code runs, a row should be inserted into some table (say processes). The id generated from that insertion should be used to insert into transactions. That way, you can keep the information about when -- and who and what and so on -- inserted particular transactions.
You can use the dense_rank to identify it as follows:
select t.*,
dense_rank() over (partition by InvoiceId
order by CreatedOn desc) as ProcessCount
from your_table t
You can then revert (/delete) as per your requirement, There is no need to explicitly maintain the ProcessCount column. It can be derived as per the above query.
I've got a table which contains event status data, similar to this:
ID Time Status
------ -------------------------- ------
357920 2019-12-25 09:31:38.854764 1
362247 2020-01-02 09:31:42.498483 1
362248 2020-01-02 09:31:46.166916 1
362249 2020-01-02 09:31:47.430933 1
362300 2020-01-03 09:31:46.932333 1
362301 2020-01-03 09:31:47.231288 1
I'd like to construct a query which returns the number of successful events each day, so:
Time Count
-------------------------- -----
2019-12-25 00:00:00.000000 1
2020-01-02 00:00:00.000000 3
2020-01-03 00:00:00.000000 2
I've stumbled across this SO answer to a similar question, but the answer there is for all the data returned by the query, whereas I need the sum grouped by date range.
Also, I cannot use BETWEEN to select a specific date range, since this query is for a Grafana dashboard, and the date range is determined by the dashboard's UI. I'm using Postgres for the SQL dialect, in case that matters.
You need to remove the time from time component. In most databases, you can do this by converting to a date:
select cast(time as date) as dte,
sum(case when status = 1 then 1 else 0 end) as num_successful
from t
group by cast(time as date)
order by dte;
This assumes that 1 means "successful".
The cast() does not work in all databases. Other alternatives are things like trunc(time), date_trunc('day', time), date_trunc(time, day) -- and no doubt many others.
In Postgres, I would phrase this as:
select date_trunc('day', time) as dte,
count(*) filter (where status = 1) as num_successful
from t
group by dte
order by dte;
How about like this:
SELECT date(Time), sum(status)
FROM table
GROUP BY date(Time)
ORDER BY min(Time)
I am trying to assign a Trip # to records for Customers with sequential days, and increment the Trip ID if they have a break in sequential days, and come later in the month for example. The data structure looks like this:
CustomerID Date
1 2014-01-01
1 2014-01-02
1 2014-01-04
2 2014-01-01
2 2014-01-05
2 2014-01-06
2 2014-01-08
The desired output based upon the above example dataset would be:
CustomerID Date Trip
1 2014-01-01 1
1 2014-01-02 1
1 2014-01-04 2
2 2014-01-01 1
2 2014-01-05 2
2 2014-01-06 2
2 2014-01-08 3
So if the Dates for that Customer are back-to-back, it is considered the same Trip, and has the same Trip #. Is there a way to do this in SQL Server? I am using MSSQL 2012.
My initial thoughts are to use the LAG, ROW_NUMBER, or OVER/PARTITION BY function, or even a Recursive Table Variable Function. I can paste some code, but in all honesty, my code isn't working so far. If this is a simple query, but I am just not thinking about it correctly, that would be great.
Thank you in advance.
Since Date is a DATE (ie has no hours), you could for example use DENSE_RANK() by Date - ROW_NUMBER() days which will give a constant value for continuous days, something like;
WITH cte AS (
SELECT CustomerID, Date,
DATEADD(DAY,
-ROW_NUMBER() OVER (PARTITION BY CustomerID ORDER BY Date),
Date) dt
FROM trips
)
SELECT CustomerID, Date,
DENSE_RANK() OVER (PARTITION BY CustomerID ORDER BY dt)
FROM cte;
An SQLfiddle to test with.
SQL command: get min date and hour from table
TblAzmon:
Acode(pk) | Aname | Adate | Ahour | ADcode_fk
----------------------------------------------------------------------------
1 system 1358/05/05 08:00 2
2 graphic 1389/05/05 08:00 1
3 simulation 1392/05/06 07:30 1
4 math 1389/05/05 09:00 1
I want the output date and time for the manager (ADcode) to get the smallest.
Desired output: [Where ADcode_fk='1']
Acode | Adate | Ahour
----------------------------------
2 1389/05/05 08:00
SQL command:
select Acode,Adate,Ahour from TblAzmon<br>
where Adate in (select min(Adate) from TblAzmon where ADcode_fk='1')
And Ahour in (select min(Ahour) from TblAzmon where ADcode_fk='1')
Output:---------->0 rows - NULL
Tip: All columns are of type text. Apart from the column Acode.
Please write the SQL code.
You could made it like that, using order by and top:
select top 1 *
from tblAzmon a
order by Adate, Ahour
Assuming you mean the earliest combination of date and hour, You can do this with order by and top:
select top 1 *
from tblAzmon a
order by Adate, Ahour
Your SQL doesnt work, because u select the minHour and minDate at once, and since the min(Date) doesnt have the min(Hour) you get 0 rows back.
U need to brake them apart and select them one by one like this. With that u should be able to do it on your own =)
SELECT Acode,Adate,min(Ahour)
FROM (Select Acode,min(Adate),Ahour FROM TblAzmon WHERE ADcode_fk='1') t
WHERE ADcode_fk='1'