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
Related
I am asking for help with this item. I am a novice to SQL and not very sure how to handle this problem I appreciate any help from the forum.
I have a table that is updated multiple times a day. I would like to create a view that only displays the last update that was made for a given day.
Here is a sample of the data
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This is the desired result of the SQL Query when the data set provided has been queries
enter image description here
As I understood you want to get the last record of every day.
Just group it by day
You will have to use EXTRACT to do it
Example: EXTRACT(DAY FROM DATE)
Then select the max time from the column where you have the time of the day. If you dont have the time in a different column you will also need to extract it.
SELECT MAX(TIME_COLUMN) FROM `TABLE_NAME`
GROUP BY EXTRACT(DAY FROM DATE)
SELECT MAX (your_date) AS "Max Date"
FROM your_table
I'm looking to only select one data point from each date in my report. I want to ensure each day is accounted for and has at least one row of information, as we had to do a few different things to move a large data file into our data warehouse (import one large Google Sheet for some data, use Python for daily pulls of some of the other data - want to make sure no date was left out), and this data goes from now through last summer. I could do a COUNT DISTINCT clause to just make sure the number of days between the first data point and yesterday (the latest data point), but I want to verify each day is accounted for. Should mention I am in BigQuery. Also, an example of the created_at style is: 2021-02-09 17:05:44.583 UTC
This is what I have so far:
SELECT FIRST(created_at)
FROM 'large_table'
ORDER BY created_at
**I know FIRST is probably not the best clause for this case, and it's currently acting to grab the very first data point in created_at, but just as a jumping-off point.
You can use aggregation:
select any_value(lt).*
from large_table lt
group by created_at
order by min(created_at);
Note: This assumes that created_at is a date -- or at least only has one value per date. You might need to convert it to a date:
select any_value(lt).*
from large_table lt
group by date(created_at)
order by min(created_at);
BigQuery equivalent of the query in your question
SELECT created_at
FROM 'large_table'
ORDER BY created_at
LIMIT 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 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;
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