I am looking for a query which gives me the daily playing time. The start (first_date) and end date(last_update) are given as shown in the Table. The following query gives me the sum of playing time on given date. How can I extend it to get a table from first day to last day and plot the query data in it and show 0 on dates when no game is played.
SELECT startTime, SUM(duration) as sum
FROM myTable
WHERE startTime = endTime
GROUP BY startTime
To show date when no one play you will need create a table days with a date field day so you could do a left join. (100 years is only 36500 rows).
Using select Generate days from date range
This use store procedure in MSQL
I will assume if a play pass the midnight a new record begin. So I could simplify my code and remove the time from datetime field
SELECT d.day, SUM(duration) as sum
FROM
days d
left join myTable m
on CONVERT(date, m.starttime) = d.day
GROUP BY d.day
If I understand correctly, you could try:
SELECT SUM(duration) AS duration, date
FROM myTable
WHERE date <= 20140430
AND date => 20140401
GROUP BY date
This would get the total time played for each date between april 1 and april 30
As far as showing 0 for dates not in the table, I don't know.
Also, the table you posted doesn't show a duration column, but the query you posted does, so I went ahead and used it.
Related
Why am I getting different results when I compare weekly results into using a code individually per week. Does it have something to do with the timestamp?
This is the code for all the weeks:
select date_trunc('week',date_joined) as week, COUNT(*) as count from auth_user
where date_joined>='01-01-2019' and date_joined<='31-03-2019'
group by week
order by week
This is the resulting table:
first result
This is the code for getting an individual week:
select COUNT(*) from auth_user where date_joined>='31-12-2018' and date_joined<='06-01-2019'
This is the result for the first week: second result
I'd say that date_joined is a timestamp, and your second query misses the entries from January 6th.
Try with
AND date_joined < '2019-01-07'
Also, you should use ISO notation: YYYY-MM-DD
I have a table with 17,000 records that is ordered by time spaced in 15 minute intervals. The time values loop back onto themselves every 24 hours, so for example, I could have 100 records that are all at 1 AM, just on different days. I want to create a 'average day' by taking those 100 records at 1 am and finding the average of them for the averaged 1 am.
I don't know how to format the table to make it show up nicely here.
I'm assuming you want to calculate the average value per time interval regardless of the day in a query. You could use this SQL to group your table by Time interval only (assuming that it's separate from the date field), and average whichever fields you want to average. Do not select or group by the date field, just select and group by the time field.
SELECT TimeField
, AVG([Field1ToAverage])
, AVG([Field2ToAverage])
FROM MyTable
GROUP BY TimeField;
If the date and time fields are stored together in the same column, you will have to extract the time only:
SELECT TimeValue([DateTimeField])
, AVG([Field1ToAverage])
, AVG([Field2ToAverage])
FROM MyTable
GROUP BY TimeValue([DateTimeField]);
please help me with this. using SQL server 2008
I need to find the number of sales done on the current day.
then find the weekday from current date and based on that find the average of the sales on all those particular weekdays in the last month
ex:
select count(sales) from salestable where orderdate= getdate()
where it gives the count of the sales done on the current date
then I need to find out the average of the sales done on the same weekday for ex if today is Sunday find the average of the sales done in the last month on all Sundays in that month.
I recommend that you borrow the data warehousing technique of creating a Calendar table that you pre-populate with 1 row for every date within the range you might need. You can add to it basically any column that is useful - in this case DayOfWeek and MonthID. Then you can eliminate date math entirely and use joins - sort of like this (not complete but points you in the right direction):
select count(salestable.sales) as salescount, a.salesavg
from salestable
join calendar on salestable.orderdate = calendar.calendardate
join (
select monthid, dayofweek, avg(salestable.sales) as salesavg
from salestable
join calendar on salestable.orderdate = calendar.calendardate
group by monthid, dayofweek) as a
on calendar.monthid = a.monthid and calendar.dayofweek = a.dayofweek
where calendar.calendardate = getdate()
You create and populate the calendar table once and reuse it every time you need to do date operations. Once you get used to this technique, you will NEVER go back to date math.
For this kind of queries are Common Table Expressions very usefull. Then you can use DATEPART function to get day of week.
This solution is also untested and intended to just point you in the right direction.
This solution uses a co-related sub-query to get the average sales.
select
order_date,
count(sales) total_sales,
(select avg(sales)
from sales_table
where order_date between dateadd(day,-30,#your_date) and #your_date
and datepart(WEEKDAY,order_date) = datepart(WEEKDAY,#your_date)
) avg_sales_mth
from sales_table
where order_date = #your_date
I need to show distinct users per week. I have a date-visit column, and a user id, it is a big table with 1 billion rows.
I can change the date column from the CSVs to year,month, day columns. but how do I deduce the week from that in the query.
I can calculate the week from the CSV, but this is a big process step.
I also need to show how many distinct users visit day after day, looking for workaround as there is no date type.
any ideas?
To get the week of year number:
SELECT STRFTIME_UTC_USEC(TIMESTAMP('2015-5-19'), '%W')
20
If you have your date as a timestamp (i.e microseconds since the epoch) you can use the UTC_USEC_TO_DAY/UTC_USEC_TO_WEEK functions. Alternately, if you have an iso-formatted date string (e.g. "2012/03/13 19:00:06 -0700") you can call PARSE_UTC_USEC to turn the string into a timestamp and then use that to get the week or day.
To see an example, try:
SELECT LEFT((format_utc_usec(day)),10) as day, cnt
FROM (
SELECT day, count(*) as cnt
FROM (
SELECT UTC_USEC_TO_DAY(PARSE_UTC_USEC(created_at)) as day
FROM [publicdata:samples.github_timeline])
GROUP BY day
ORDER BY cnt DESC)
To show week, just change UTC_USEC_TO_DAY(...) to UTC_USEC_TO_WEEK(..., 0) (the 0 at the end is to indicate the week starts on Sunday). See the documentation for the above functions at https://developers.google.com/bigquery/docs/query-reference for more information.
please help me with my problem. So, I have a table named 'RATES' which contains these columns:
id (int)
rate (money)
start_time (datetime)
end_time(datetime)
example data:
1 150 8:00am 6:00pm
2 200 6:00pm 4:00am
3 250 8:00am 4:00am (the next day)
What I have to do is to select all the id(s) to where a given time would fall.
e.g given time: 9:00 pm, the output should be 2,3
The problem is I got this time range between 8am to 4am the next day and I don't know what to do. Help, please! thanks in advance :D
Assuming that #Andriy M is correct:
Data never spans more than 24 hours
if end_time<=start_time then end_time belongs to the next day
then what you're looking for is this:
Declare #GivenTime DateTime
Set #GivenTime = '9:00 PM'
Select ID
From Rates
Where (Start_Time<End_Time And Start_Time<=#GivenTime And End_Time>=#GivenTime)
Or (Start_Time=End_Time And Start_Time=#GivenTime)
Or (Start_Time>End_Time And (Start_Time>=#GivenTime Or End_Time<=#GivenTime))
I don't really ever use MS SQL, but maybe this will help.
I was going to suggest something like this, but by the way you have your data set up, this would fail.
SELECT id FROM RATES
WHERE datepart(hh, start_time) <= 9 AND datepart(hh, end_time) >= 9;
You'll have you search using the actual date if you expect to get the correct data back.
SELECT id FROM RATES
WHERE start_time <= '2011-1-1 9:00' AND end_time >= '2011-1-1 9:00';
This may not be exactly correct, but it may help you look in the right direction.
I guess #gbn is not going to help you. I will try and fill in.
Given -- a table called timedata that has ranges only going over at most one day
WITH normalized AS
(
SELECT *
FROM timedata
WHERE datepart(day,start_time) = datepart(day,endtime)
UNION ALL
SELECT id, rate, start_time, dateadd(second,dateadd(day,datediff(day,0,end_time),0),-1) as end_time
FROM timedata
WHERE not (datepart(day,start_time) = datepart(day,endtime))
UNION ALL
SELECT id, rate,dateadd(day,datediff(day,0,end_time),0) as start_time, end_time
FROM timedata
WHERE not (datepart(day,start_time) = datepart(day,endtime))
)
SELECT *
FROM normalized
WHERE datepart(hour,start_time) < #inhour
AND datepart(hour,end_time) > #inhour
This makes use of a CTE and a trick to truncate datetime values. To understand this trick read this question and answer: Floor a date in SQL server
Here is an outline of what this query does:
Create a normalized table with each time span only going over one day by
Selecting all rows that occur on the same day.
Then for each entry that spans two days joining in
Selecting the starttime and one second before the next day as the end time for all that span.
and
Selecting 12am of the end_time date as the starttime and the end_time.
Finally you perform the select using the hour indicator on this normalized table.
If your ranges go over more than one day you would need to use a recursive CTE to get the same normalized table.