I have written the sql query:
SELECT id
date_diff("day", create_date, date) as day
action_type
FROM "my_database"
It brings this:
id day action_type
1 0 upload
1 0 upload
1 0 upload
1 1 upload
1 1 upload
2 0 upload
2 0 upload
2 1 upload
How to change my query to get table with unique days in column day and average number "upload" action_type among all id's. So desired result must look like this:
day avg_num_action
0 2.5
1 1.5
It is 2.5, because (3+2)/2 (3 uploads of id:1 and 2 uploads for id:2). same for 1.5
Please try this. Consider your given query as a table. If any WHERE condition needed then please enable this other wise disable where clause.
SELECT t.day
, COUNT(*) / COUNT(DISTINCT t.id) avg_num_action
FROM (SELECT id,
date_diff("day", create_date, date) as day,
action_type
FROM "my_database") t
WHERE t.action_type = 'upload'
GROUP BY t.day
Create a table from your given result set and write query based on that.
SELECT t.tday
, COUNT(*) / COUNT(DISTINCT t.id) avg_num_action
FROM my_database t
GROUP BY t.tday
Please check from url https://dbfiddle.uk/?rdbms=mysql_8.0&fiddle=871935ea2b919c4e24eb83fcbce78973
Update: I think my two-steps approach is more complicated than needed. Rahul Biswas shows how this can be done in one step. I suggest you use and accept his answer.
Original answer:
Two steps:
Count entries per ID and day
Take the average count per day
The query:
with rows as (select id, date_diff('day', create_date, date) as day from mytable)
, per_id_and_day as (select id, day, count(*) as cnt from rows group by id, day)
select day, avg(cnt)
from per_id_and_day
group by day
order by day;
You don't need a subquery for this logic:
SELECT date_diff("day", create_date, date) as day,
COUNT(*) * 1.0 / COUNT(DISTINCT id)
FROM "my_database"
GROUP BY date_diff("day", create_date, date)
Related
I have a table that has 3 columns: user_id, date, amount. I need to find out on which date the amount reached 1 Million for the first time. The amount can go up or down on any given day.
I tried using partition by user_id order by date desc but I can't figure out how to find the exact date on which it reached 1 Million for the first time. I am exploring lead, lag functions. Any pointers would be appreciated.
You may use conditional aggregation as the following:
select user_id,
min(case when amount >= 1000000 then date end) as expected_date
from table_name
group by user_id
And if you want to check where the amount reaches exactly 1M, use case when amount = 1000000 ...
If you meant that the amount is a cumulative amount over the increasing of date, then query will be:
select user_id,
min(case when cumulative_amount >= 1000000 then date end) as expected_date
from
(
select *,
sum(amount) over (partition by user_id order by date) cumulative_amount
from table_name
) T
group by user_id;
Try this:
select date,
sum(amount) as totalamount
from tablename
group by date
having totalamount>=1000000
order by date asc
limit 1
This would summarize the amount for each day and return 1 record where it reached 1M for the first time.
Sample result on SQL Fiddle.
And if you want it to be grouped for both date and user_id, add user_id in select and group by clauses.
select user_id, date,
sum(amount) as totalamount
from tablename
group by user_id,date
having totalamount>=1000000
order by date asc
limit 1
Example here.
I have a table of user_id who have visited my platform. I want to get count of only those user IDs who have visited my store 4 or more times for each user and for every day for a duration of 10 days.
To achieve this I am using this query:
select date(arrival_timestamp), count(user_id)
from mytable
where date(arrival_timestamp) >= current_date-10
and date(arrival_timestamp) < current_date
group by 1
having count(user_id)>=4
order by 2 desc
limit 10;
But this query is virtually taking all the users having count value greater than 4 and not on a daily basis which covers almost every user and hence I am not able to segregate only those users who vist my store more than once on a particular day. Any help in this regard is appreciated.
Thanks
you can try this
with list as (
select user_id, count(*) as user_count, array_agg(arrival_timestamp) as arrival_timestamp
from mytable
where date(arrival_timestamp) >= current_date-10
and date(arrival_timestamp) < current_date
group by user_id)
select user_id, unnest(arrival_timestamp)
from list
where user_count >= 4
From a list of daily users that have visited your store 4 or more times a day over the last 10 days (the internal query) select these who have 10 occurencies, i.e. every day.
select user_id
from
(
select user_id
from the_table
where arrival_timestamp::date between current_date - 10 and current_date - 1
group by user_id, arrival_timestamp::date
having count(*) >= 4
) t
group by user_id
having count(*) = 10;
Based on table below in Presto I need a column for all new 'rid'. What I managed to do is the same what I can achieve with partition by but it's not exactly what I'm looking for (db<>fiddle demo).
Goal is to have many groupings counts but I think this should describe problem sufficiently.
I need data truncated by days and column for new users every day as shown at example below. In simple words - if value repeats don't count it. I've tried to find correlation between this and relational division problem but I just stuck.
You could use row_number() to rank the records of each rid by time; then you can aggregate and count in only the top record per group.
select
date_trunc(day, t.time) dy,
count(*) rid_count,
sum(case when t.rn = 1 then 1 else 0 end) new_rid_count
from (
select
t.*
row_number() over(partition by t.rid order by t.time) rn
from mytable t
) t
group by date_trunc(day, t.time)
I think of this as two levels of aggregation. The inner one to get the earliest date. The outer to aggregate:
select first_day, count(*)
from (select rid, date_trunc('day', min(time))::date as first_day
from orders o
group by rid
) r
group by 1
I have a table with just two columns: User_ID and fail_date. Each time somebody's card is rejected they are logged in the table, their card is automatically tried again 3 days later, and if they fail again, another entry is added to the table. I am trying to write a query that counts unique failures by month so I only want to count the first entry, not the 3 day retries, if they exist. My data set looks like this
user_id fail_date
222 01/01
222 01/04
555 02/15
777 03/31
777 04/02
222 10/11
so my desired output would be something like this:
month unique_fails
jan 1
feb 1
march 1
april 0
oct 1
I'll be running this in Vertica, but I'm not so much looking for perfect syntax in replies. Just help around how to approach this problem as I can't really think of a way to make it work. Thanks!
You could use lag() to get the previous timestamp per user. If the current and the previous timestamp are less than or exactly three days apart, it's a follow up. Mark the row as such. Then you can filter to exclude the follow ups.
It might look something like:
SELECT month,
count(*) unique_fails
FROM (SELECT month(fail_date) month,
CASE
WHEN datediff(day,
lag(fail_date) OVER (PARTITION BY user_id,
ORDER BY fail_date),
fail_date) <= 3 THEN
1
ELSE
0
END follow_up
FROM elbat) x
WHERE follow_up = 0
GROUP BY month;
I'm not so sure about the exact syntax in Vertica, so it might need some adaptions. I also don't know, if fail_date actually is some date/time type variant or just a string. If it's just a string the date/time specific functions may not work on it and have to be replaced or the string has to be converted prior passing it to the functions.
If the data spans several years you might also want to include the year additionally to the month to keep months from different years apart. In the inner SELECT add a column year(fail_date) year and add year to the list of columns and the GROUP BY of the outer SELECT.
You can add a flag about whether this is a "unique_fail" by doing:
select t.*,
(case when lag(fail_date) over (partition by user_id order by fail_date) > fail_date - 3
then 0 else 1
end) as first_failure_flag
from t;
Then, you want to count this flag by month:
select to_char(fail_date, 'Mon'), -- should aways include the year
sum(first_failure_flag)
from (select t.*,
(case when lag(fail_date) over (partition by user_id order by fail_date) > fail_date - 3
then 0 else 1
end) as first_failure_flag
from t
) t
group by to_char(fail_date, 'Mon')
order by min(fail_date)
In a Derived Table, determine the previous fail_date (prev_fail_date), for a specific user_id and fail_date, using a Correlated subquery.
Using the derived table dt, Count the failure, if the difference of number of days between current fail_date and prev_fail_date is greater than 3.
DateDiff() function alongside with If() function is used to determine the cases, which are not repeated tries.
To Group By this result on Month, you can use MONTH function.
But then, the data can be from multiple years, so you need to separate them out yearwise as well, so you can do a multi-level group by, using YEAR function as well.
Try the following (in MySQL) - you can get idea for other RDBMS as well:
SELECT YEAR(dt.fail_date) AS year_fail_date,
MONTH(dt.fail_date) AS month_fail_date,
COUNT( IF(DATEDIFF(dt.fail_date, dt.prev_fail_date) > 3, user_id, NULL) ) AS unique_fails
FROM (
SELECT
t1.user_id,
t1.fail_date,
(
SELECT t2.fail_date
FROM your_table AS t2
WHERE t2.user_id = t1.user_id
AND t2.fail_date < t1.fail_date
ORDER BY t2.fail_date DESC
LIMIT 1
) AS prev_fail_date
FROM your_table AS t1
) AS dt
GROUP BY
year_fail_date,
month_fail_date
ORDER BY
year_fail_date ASC,
month_fail_date ASC
I like to write a sql query that counts the number of days each user used the application and how many concurrent days. A user can enter the app several times a day but that should count as 1.
My table looks like this:
id | bigint
user_id | bigint
action_date | timestamp without time zone
To count the number of days per user:
SELECT user_id, count(DISTINCT action_date::date) AS days
FROM user_action_tbl
GROUP BY user_id;
One way to do it
SELECT user_id, COUNT(*) days_total, SUM(conseq) days_consecutive
FROM
(
SELECT user_id,
CASE WHEN LEAD(date, 1) OVER (PARTITION BY user_id ORDER BY date) - date = 1 THEN 1 ELSE 0 END consecutive
FROM
(
SELECT user_id, action_date::date date
FROM table1
GROUP BY user_id, action_date::date
) q
) p
GROUP BY user_id
Here is a SQLFiddle demo