I am trying to find the total time taken per person and provide the answer in total minutes spent using SQL. The page_start_time is time data type.The data is shown below:
This is the visitors table. I need to find the total time taken using the page_start_time field per USER_ID.
I tried the following code:
select sum(datediff(minute, 0, page_start_time)) as Totalnumberofminutesspent, User_id
from visitors
GROUP BY user_id
ORDER BY Totalnumberofminutesspent DESC;
I got the following answer:
When I checked manually, the answer is incorrect.
I am guessing you want the difference between the minimum and maximum times for each user:
select user_id,
datediff(minute, min(page_start_time), max(page_start_time) as Totalnumberofminutesspent
from visitors
group by user_id
order by Totalnumberofminutesspent desc;
Related
I can't seem to find a perhaps easy solution to what I'm trying to accomplish here, using SQL and, more importantly, QuestDB. I also find it hard to put my exact question into words so bear with me.
Input
My real input is different of course but a similar dataset or case is the gas_prices table on the demo page of QuestDB. On https://demo.questdb.io, you can directly write and run queries against some sample database, so it should be easy enough to follow.
The main task I want to accomplish is to find out which month was responsible for the year's highest galon price.
Output
Using the following query, I can get the average galon price per month just fine.
SELECT timestamp, avg(galon_price) as avg_per_month FROM 'gas_prices' SAMPLE BY 1M
timestamp
avg_per_month
2000-06-05T00:00:00.000000Z
1.6724
2000-07-05T00:00:00.000000Z
1.69275
2000-08-05T00:00:00.000000Z
1.635
...
...
Then, I get all these monthly averages, group them by year and return the maximum galon price per year by wrapping the above query in a subquery, like so:
SELECT timestamp, max(avg_per_month) as max_per_year FROM (
SELECT timestamp, avg(galon_price) as avg_per_month FROM 'gas_prices' SAMPLE BY 1M
) SAMPLE BY 12M
timestamp
max_per_year
2000-01-05T00:00:00.000000Z
1.69275
2001-01-05T00:00:00.000000Z
1.767399999999
2002-01-05T00:00:00.000000Z
1.52075
...
...
Wanted output
I want to know which month was responsible for the maximum price of a year.
Looking at the output of the above query, we see that the maximum galon price for the year 2000 was 1.69275. Which month of the year 2000 had this amount as average price? I'd like to display this month in an additional column.
For the first row, July 2000 is shown in the additional column for year 2000 because it is responsible for the highest average price in 2000. For the second row, it was May 2001 as that month had the highest average price of 2001.
timestamp
max_per_year
which_month_is_responsible
2000-01-05T00:00:00.000000Z
1.69275
2000-07-05T00:00:00.000000Z
2001-01-05T00:00:00.000000Z
1.767399999999
2001-05-05T00:00:00.000000Z
...
...
What did I try?
I tried by adding a subquery to the SELECT to have a "duplicate" of some sort for the timestamp column but that's apparently never valid in QuestDB (?), so probably the solution is by adding even more subqueries in the FROM? Or a UNION?
Who can help me out with this? The data is there in the database and it can be calculated. It's just a matter of getting it out.
I think 'wanted output' can be achieved with window functions.
Please have a look at:
CREATE TABLE electricity (ts TIMESTAMP, consumption DOUBLE) TIMESTAMP(ts);
INSERT INTO electricity
SELECT (x*1000000)::timestamp, rnd_double()
FROM long_sequence(10000000);
SELECT day, ts, max_per_day
FROM
(
SELECT timestamp_floor('d', ts) as day,
ts,
avg_in_15_min as max_per_day,
row_number() OVER (PARTITION BY timestamp_floor('d', ts) ORDER BY avg_in_15_min desc) as rn_per_day
FROM
(
SELECT ts, avg(consumption) as avg_in_15_min
FROM electricity
SAMPLE BY 15m
)
) WHERE rn_per_day = 1
I'm trying display the user growth per day using Grafana Time Series with SQL Server. However I found the documentation to be unhelpful and my queries are incorrect.
The following returns a constant value of 1 for every day. What do I need to change to display the number of new users created per day?
Thank you very much in advance.
SELECT
$__timeGroup([created_at],'1d') as time,
COUNT(id) as value,
'users' as metric
FROM [db].[user]
WHERE $__timeFilter([created_at])
GROUP BY [created_at]
ORDER BY 1
This works for me:
SELECT
$__timeGroup(created_at, '1d') AS time,
COUNT(id) as 'New Users'
FROM [db].[user]
GROUP BY $__timeGroup(created_at, '1d')
ORDER BY 1
I have a sample table that looks like this
I need to to a SQL script to get the Average Handling Time of a Case, I researched for suggestions but never worked with timestamps and I'm really lost on how to do it.
If you subtract one timestamp from another, you get an interval. And you can calculate the average over intervals.
select avg(close_timestamp - create_timestamp)
from the_table;
You can calculate the AVG of the difference of the timestamp.
SELECT agent, avg(close_timestamp - create_timestamp) average_timestamp
FROM your_table
GROUP BY agent
ORDER BY agent
You can format the solution for obtain it in days/hours/minutes/seconds.
I have an int field in my product table called product_stat which is incremented everytime a product is looked at. I also have a date field called product_date_added.
In order to figure out the average visits per day a product gets, you need to calculate how many days the product has existed by using the current date and the date the product was added. Then divide the product stat by the amount of days it has existed to get the average visits per day.
OK but what I want to do is select a number of products and order them by visits per day DESC
How can I do that?
Thanks!!!
Something like this should do the trick, using DATEDIFF to get the difference between two dates, and then dividing the product_stat column by that difference.
SELECT
p.*,
p.product_stat/DATEDIFF(CURDATE(),p.product_date_added) as visits_per_day
FROM products p
ORDER BY visits_per_day DESC
Although note that DATEDIFF only came around as of MySQL 4.1.1. If you're using an earlier version you should do "TO_DAYS(CURDATE()) - TO_DAYS(p.product_date_added)" instead.
You will want something like this:
SELECT product_name,
product_stat / datediff(now(), product_date_added) as 'VisitPerDay'
FROM product
ORDER by VisitPerDay DESC
I have a table like this that stores messages coming through a system:
Message
-------
ID (bigint)
CreateDate (datetime)
Data (varchar(255))
I've been asked to calculate the messages saved per second at peak load. The only data I really have to work with is the CreateDate. The load on the system is not constant, there are times when we get a ton of traffic, and times when we get little traffic. I'm thinking there are two parts to this problem: 1. Determine ranges of time that are considered peak load, 2. Calculate the average messages per second during these times.
Is this the right approach? Are there things in SQL that can help with this? Any tips would be greatly appreciated.
I agree, you have to figure out what Peak Load is first before you can start to create reports on it.
The first thing I would do is figure out how I am going to define peak load. Ex. Am I going to look at an hour by hour breakdown.
Next I would do a group by on the CreateDate formated in seconds (no milleseconds). As part of the group by I would do an avg based on number of records.
I don't think you'd need to know the peak hours; you can generate them with SQL, wrapping a the full query and selecting the top 20 entries, for example:
select top 20 *
from (
[...load query here...]
) qry
order by LoadPerSecond desc
This answer had a good lesson about averages. You can calculate the load per second by looking at the load per hour, and dividing by 3600.
To get a first glimpse of the load for the last week, you could try (Sql Server syntax):
select datepart(dy,createdate) as DayOfYear,
hour(createdate) as Hour,
count(*)/3600.0 as LoadPerSecond
from message
where CreateDate > dateadd(week,-7,getdate())
group by datepart(dy,createdate), hour(createdate)
To find the peak load per minute:
select max(MessagesPerMinute)
from (
select count(*) as MessagesPerMinute
from message
where CreateDate > dateadd(days,-7,getdate())
group by datepart(dy,createdate),hour(createdate),minute(createdate)
)
Grouping by datepart(dy,...) is an easy way to distinguish between days without worrying about month borders. It works until you select more that a year back, but that would be unusual for performance queries.
warning, these will run slow!
this will group your data into "second" buckets and list them from the most activity to least:
SELECT
CONVERT(char(19),CreateDate,120) AS CreateDateBucket,COUNT(*) AS CountOf
FROM Message
GROUP BY CONVERT(Char(19),CreateDate,120)
ORDER BY 2 Desc
this will group your data into "minute" buckets and list them from the most activity to least:
SELECT
LEFT(CONVERT(char(19),CreateDate,120),16) AS CreateDateBucket,COUNT(*) AS CountOf
FROM Message
GROUP BY LEFT(CONVERT(char(19),CreateDate,120),16)
ORDER BY 2 Desc
I'd take those values and calculate what they want