I want to do a select that gives me the time of an employee resolving a ticket.
The problem is that the ticket is divided in actions, so its not only getting the time of a row, it can be from n rows.
This is an abbreviation of what I have:
Tickets
TicketID | Days | Hours | Minutes
------------------------------------------------
12 | 0 | 2 | 32
12 | 1 | 0 | 12
12 | 4 | 6 | 0
13 | 2 | 5 | 12
13 | 0 | 2 | 33
And this is what I want to get:
TicketID | Time (in minutes)
------------------------------------------------
12 | 2994
13 | 1425
(Or just one row with the condition where specifying TicketID)
This is the select that im doing right now:
select distinct ((Days*8)*60) + (Hours*60) + Minutes from Tickets where ticketid = 12
But is not working as I want.
select ticketid, sum((Days*8)*60), sum((Hours*60)), sum (Minutes)
from tickets
group by ticketid
select TicketID, sum((Days*8)*60) + sum(Hours*60) + sum(Minutes) as Time_in_minutes
from Tickets
group by TicketID
Distinct, as you were trying before, takes each row in the source table (Tickets) and filters out all of the duplicate rows. Instead, you are trying to sum up the days, minutes, and hours for each ticket. So sum them up, and group by the ticket number.
Try this:
SELECT TicketID, (Sum(Minutes)+(Sum(Hours)*60)+(sum(Days)*24*60) ) time
FROM Tickets Group by TicketID
Related
I have a table with multiple equal date entries and a value. I need a table that calculates the historical value and the count of entries per date. I want to use the data to create some charts in gnuplot/etc later.
Raw data:
date | value
------------+------
2017-11-26 | 5
2017-11-26 | 5
2017-11-26 | 5
2017-11-28 | 20
2017-11-28 | 5
2018-01-07 | 200
2018-01-07 | 5
2018-01-07 | 20
2018-01-15 | 5
2018-01-16 | 50
Output should be:
date | avg | count manual calc explanation
------------+--------+------- ---------------------------------------
2017-11-26 | 5 | 3 (5+5+5) / 3 = 5
2017-11-28 | 8 | 2 (5+5+5+20+5) / 5 = 8
2018-01-07 | 33.125 | 3 (5+5+5+20+5+200+5+20) / 8 = 33.125
2018-01-15 | 30 | 1 (5+5+5+20+5+200+5+20+5) / 9 = 30
2018-01-16 | 32 | 1 (5+5+5+20+5+200+5+20+5+50) / 10 = 32
If it is not possible to calculate two different columns, I would be fine for the avg column. For counting only the dates I have the solution "SELECT DISTINCT date, COUNT(date) FROM table_name GROUP BY date ORDER BY date"
I played around with DISTINCTs, GROUP BYs, JOINs, etc, but I did not find any solution. I found some other articles on the web, but no one covers a case where a date is more than once listed in the table.
You want a running average (total value divided by total count up to the row). This is done with window functions.
select
date,
sum(sum_value) over (order by date) as running_sum,
sum(cnt) over (order by date) as running_count,
sum(sum_value) over (order by date) /
sum(cnt) over (order by date) as running_average
from
(
select date, sum(value) as sum_value, count(*) as cnt
from mytable
group by date
) aggregated
order by date;
Demo: https://dbfiddle.uk/?rdbms=postgres_13&fiddle=fb13b63970cb096913a53075b8b5c8d7
I have a table that has the following schema:
ID | FirstName | Surname | TransmissionID | CaptureDateTime
1 | Billy | Goat | ABCDEF | 2018-09-20 13:45:01.098
2 | Jonny | Cash | ABCDEF | 2018-09-20 13:45.01.108
3 | Sally | Sue | ABCDEF | 2018-09-20 13:45:01.298
4 | Jermaine | Cole | PQRSTU | 2018-09-20 13:45:01.398
5 | Mike | Smith | PQRSTU | 2018-09-20 13:45:01.498
There are well over 70,000 records and they store logs of transmissions to a web-service. What I'd like to know is how would I go about writing a script that would select the distinct TransmissionID values and also show the timespan between the earliest CaptureDateTime record and the latest record? Essentially I'd like to see what the rate of records the web-service is reading & writing.
Is it even possible to do so in a single SELECT statement or should I just create a stored procedure or report in code? I don't know where to start aside from SELECT DISTINCT TransmissionID for this sort of query.
Here's what I have so far (I'm stuck on the time calculation)
SELECT DISTINCT [TransmissionID],
COUNT(*) as 'Number of records'
FROM [log_table]
GROUP BY [TransmissionID]
HAVING COUNT(*) > 1
Not sure how to get the difference between the first and last record with the same TransmissionID I would like to get a result set like:
TransmissionID | TimeToCompletion | Number of records |
ABCDEF | 2.001 | 5000 |
Simply GROUP BY and use MIN / MAX function to find min/max date in each group and subtract them:
SELECT
TransmissionID,
COUNT(*),
DATEDIFF(second, MIN(CaptureDateTime), MAX(CaptureDateTime))
FROM yourdata
GROUP BY TransmissionID
HAVING COUNT(*) > 1
Use min and max to calculate timespan
SELECT [TransmissionID],
COUNT(*) as 'Number of records',datediff(s,min(CaptureDateTime),max(CaptureDateTime)) as timespan
FROM [log_table]
GROUP BY [TransmissionID]
HAVING COUNT(*) > 1
A method that returns the average time for all transmissionids, even those with only 1 record:
SELECT TransmissionID,
COUNT(*),
DATEDIFF(second, MIN(CaptureDateTime), MAX(CaptureDateTime)) * 1.0 / NULLIF(COUNT(*) - 1, 0)
FROM yourdata
GROUP BY TransmissionID;
Note that you may not actually want the maximum of the capture date for a given transmissionId. You might want the overall maximum in the table -- so you can consider the final period after the most recent record.
If so, this looks like:
SELECT TransmissionID,
COUNT(*),
DATEDIFF(second,
MIN(CaptureDateTime),
MAX(MAX(CaptureDateTime)) OVER ()
) * 1.0 / COUNT(*)
FROM yourdata
GROUP BY TransmissionID;
I have two tables.
**tblMonthlyData**
ReportMonth | TotalItems | TotalVariances
Jan | 5 | 0
Feb | 1 | 1
Mar | 2 | 0
Apr | 8 | 4
May | 4 | 0
Jun | 5 | 0
Jul | 3 | 0
Aug | 5 | 0
Sep | 9 | 3
Oct | 1 | 0
Nov | 7 | 0
Dec | 6 | 0
and
**tblDailyData**
ID | ItemNum | CountedQty | SystemQty | Variance
1 | Item1 | 4 | 4 | 0
2 | Item2 | 8 | 5 | -3
3 | Item3 | 1 | 2 | 1
4 | Item4 | 6 | 4 | -2
For the sake of clarity, we'll say the above tblDailyData is from a count done today, 01/27/2017. Variance is a calculated field based on the data in both quantity fields.
I'm trying to add the count of records in tblDailyData to TotalItems in tblMonthlyData based on the date of the count (i.e. counts are done daily and each counts data needs to be added to the appropriate month in tblMonthlyData). So for the above example I'd need to add 4 (number of records) to TotalItems in tblMonthlyData for the Jan record, resulting in the updated record being 9, and add 3 (number of variances) to TotalVariances, resulting in the updated record being 3.
So far, I've tried using a Make Table Query for both total items counted and total number of variances, then using an Update Query that looks like this:
UPDATE tblMonthlyData
SET TotalItems = TotalItems + tblTempTotalItems.CountOfItems,
TotalVariances = TotalVariances + tblTempTotalVariances.CountOfVariances
WHERE Format$([ReportMonth],"mmm")=Format$(Now(),"mmm");
I've also tried a similar method using select queries to count records and variances (without creating the temporary tables) and running the update query based on those. Both methods result in Access prompting for the CountOfItems and CountOfVariances parameters when the update query is ran instead of just taking the values from the specified temporary table or select query.
This seemed like it'd be such a simple operation (query the count of records and variances, add them to the appropriate monthly record in separate table), but it turns out I can't figure out how to make it work. Thanks for any help!
This does not seem to be a situation for a table, but rather for some views/queries, which will always be up to date.
Use a GROUP BY FORMAT([date_field],"mm/dd/yyyy") clause in your query for daily item count (if you want to add that to a montlhy count, we will do that in ANOTHER query.
SELECT FORMAT([date_field],"mm/dd/yyyy") AS Date, COUNT(ID) AS TotalItems
FROM tblDailyData
GROUP BY Date
Call this query dailyTotalItems.
SELECT FORMAT([date_field],"mm/dd/yyyy") AS Date, COUNT(ID) AS TotalItemsWithVariance, SUM(
FROM tblDailyData
WHERE NOT (Variance = 0)
GROUP BY Date
Call this query dailyTotalItemsWithVariance.
SELECT MONTH([date_field]) As MonthDate, SUM(TotalItems) As TotalMonthlyItems
FROM dailyTotalItems
GROUP BY MonthDate
Call this query monthlyTotalItems.
SELECT MONTH([date_field]) As MonthDate, SUM(TotalItemsWithVariance) As TotalMonthlyItemsWithVariance
FROM dailyTotalItemsWithVariance
GROUP BY MonthDate
Call this query monthlyTotalItemsWithVariance.
Then LEFT JOIN both on MonthDate.
SELECT * FROM monthlyTotalItems
LEFT JOIN monthlyTotalItemsWithVariance ON monthlyTotalItems.MonthDate = monthlyTotalItemsWithVariance.MonthDate
NOTE: TotalItems will always be >= TotalItemsWithVariance AND every date with a variance must have had a count. So get ALL dates in monthlyTotalItems and left join to match the monthlyTotalItemsWithVariance items (which must be included, as shown above)
I have a table of hourly product usage (how many times the product is used) data –
ID (bigint)| ProductId (tinyint)| Date (int - YYYYMMDD) | Hour (tinyint)| UsageCount (int)
#|1 | 20140901 | 0 | 10
#|1 | 20140901 | 1 | 15
#|1 | 20140902 | 5 | 25
#|1 | 20140903 | 5 | 25
#|1 | 20140904 | 3 | 25
#|1 | 20140905 | 7 | 25
#|1 | 20140906 | 10 | 25
#|1 | 20140907 | 9 | 25
#|1 | 20140908 | 5 | 25
#|2 | 20140903 | 16 | 10
#|2 | 20140903 | 13 | 115
Likewise, I have the usage data for 4 different products (ProductId from 1 through 4) stored for every hour in the product_usage table. As you can imagine, it is constantly growing as the nightly ETL process dumps the data for the entire previous day. If a product is not used on any hour of a day, the record for that hour won’t appear in this table. Similarly, if a product is not used for the entire day, there won’t be any record for that day in the table. I need to generate a report that gives daily usage and last 7 days’ rolling average –
For example:
ProductId | Date | DailyUsage | RollingAverage
1 | 20140901 | sum of usages of that day | (Sum of usages from 20140901 through 20140826) / 7
1 | 20140901 | sum of usages of that day | (Sum of usages from 20140901 through 20140826) / 7
1 | 20140902 | sum of usages of that day | (Sum of usages from 20140902 through 20140827) / 7
2 | 20140902 | sum of usages of that day | (Sum of usages from 20140902 through 20140827) / 7
And so on..
I am planning to create an Indexed View in SQL server 2014. Can you think of an efficient SQL query to do this?
Try:
select x.*,
avg(dailyusage) over(partition by productid order by productid, date rows between 6 preceding and current row) as rolling_avg
from (select productid, date, sum(usagecount) as dailyusage
from tbl
group by productid, date) x
Fiddle:
http://sqlfiddle.com/#!6/f674a7/4/0
Replace "avg(dailusage) over...." with sum (rather than avg) if what you really want is the sum for the past week. In your title you say you want the average but later you say you want the sum. The query should be the same other than that, so use whichever you actually want.
As was pointed out by Gordon this is basically the average of the past 6 dates in which the product was used, which might be more than just the past 6 days if there are days without any rows for that product on the table because it wasn't used at all. To get around that you could use a date table and your products table.
You have to be careful if you can be missing data on some days. If I assume that there is data for some product on each day, then this approach will work:
select p.productid, d.date, sum(usagecount),
sum(sum(usagecount)) over (partition by p.productid order by d.date
rows between 6 preceding and current row) as Sum7day
from (select distinct productid from hourly) p cross join
(select distinct date from hourly) d left join
hourly h
on h.productid = p.productid and h.date = p.date
group by p.productid, d.date;
I've set up a SQL Fiddle to illustrate the question...
I have a database of pupils (referenced by PupilId) who have assessments (AssessmentLevelId) recorded in various subjects (NCSubjectId) at various period (PeriodId).
Not every possible period may have an assessment in it.
PupilId | PeriodId | NCSubjectId | AssessmentLevelId
-----------------------------------------------------
100 | 1 | 10 | 1
100 | 3 | 10 | 2
200 | 1 | 10 | 1
300 | 1 | 10 | 1
400 | 1 | 10 | 1
100 | 5 | 10 | 2
300 | 7 | 10 | 2
100 | 15 | 10 | 2
I want to find the number of pupils who have a particular assessment level by a particular PeriodId.
So far I have this:
SELECT PupilId, COUNT(1) FROM NCAssessment
WHERE AssessmentLevelId = 2
AND NCSubjectId=10
AND PeriodId <= 10
GROUP BY PupilId
Which finds the pupil ids, but pupil 100 has a count of 2. I guess I need to wrap this in another query but am stumped. Any suggestions?
This is using Azure SQL.
Thanks.
If I understand your question correctly, I think this might be what you are looking for:
AssessmentLevelId = 2 has been removed from the query, because some Periods may not have an assessment.
SELECT AssessmentLevelID, PeriodID, COUNT(DISTINCT PupilID)
FROM NCAssessment
WHERE NCSubjectId=10 AND
PeriodId <= 10
GROUP BY AssessmentLevelID, PeriodID
If this isn't correct, could you please post a sample result you are expecting. Thanks!
If you want the number of distinct pupils that match, then use count(distinct):
SELECT COUNT(DISTINCT PupilId) as NumMatchingPupils, COUNT(*) as NumMatchingAssessments
FROM NCAssessment
WHERE AssessmentLevelId = 2 AND NCSubjectId = 10 AND PeriodId <= 10;
COUNT(DISTINCT) will count each pupil once, regardless of the number of maps. COUNT(*) or COUNT(1) will count the number of assessments that match.