Group by for each row in bigquery - sql

I have a table that stores user comments for each month. Comments are stored using UTC timestamps, I want to get the users that posts more than 20 comments per day. I am able to get the timestamp start and end for each day, but I can't group the comments table by number of comments.
This is the script that I have for getting dates, timestamps and distinct users.
SELECT
DATE(TIMESTAMP_SECONDS(r.ts_start)) AS date,
r.ts_start AS timestamp_start,
r.ts_start+86400 AS timestamp_end,
COUNT(*) AS number_of_comments,
COUNT(DISTINCT s.author) AS dictinct_authors
FROM ((
WITH
shifts AS (
SELECT
[STRUCT(" 00:00:00 UTC" AS hrs,
GENERATE_DATE_ARRAY('2018-07-01','2018-07-31', INTERVAL 1 DAY) AS dt_range) ] AS full_timestamps )
SELECT
UNIX_SECONDS(CAST(CONCAT( CAST(dt AS STRING), CAST(hrs AS STRING)) AS TIMESTAMP)) AS ts_start,
UNIX_SECONDS(CAST(CONCAT( CAST(dt AS STRING), CAST(hrs AS STRING)) AS TIMESTAMP)) + 86400 AS ts_end
FROM
shifts,
shifts.full_timestamps
LEFT JOIN
full_timestamps.dt_range AS dt)) r
INNER JOIN
`user_comments.2018_07` s
ON
(s.created_utc BETWEEN r.ts_start
AND r.ts_end)
GROUP BY
r.ts_start
ORDER BY
number_of_comments DESC
And this is the sample output 1:
The user_comments.2018_07 table is as the following:
More concretely I want the first output 1, has one more column showing the number of authors that have more than 20 comments for the date. How can I do that?

If the goal is only to get the number of users with more than twenty comments for each day from table user_comments.2018_07, and add it to the output you have so far, this should simplify the query you first used. So long as you're not attached to keeping the min/max timestamps for each day.
with nb_comms_per_day_per_user as (
SELECT
day,
author,
COUNT(*) as nb_comments
FROM
# unnest as we don't really want an array
unnest(GENERATE_DATE_ARRAY('2018-07-01','2018-07-31', INTERVAL 1 DAY)) AS day
INNER JOIN `user_comments.2018_07` c
on
# directly convert timestamp to a date, without using min/max timestamp
date(timestamp_seconds(created_utc))
=
day
GROUP BY day, c.author
)
SELECT
day,
sum(nb_comments) as total_comments,
count(*) as distinct_authors, # we have already grouped by author
# sum + if enables to count "very active" users
sum(if(nb_comments > 20, 1, 0)) as very_active_users
FROM nb_comms_per_day_per_user
GROUP BY day
ORDER BY total_comments desc
Also I supposed the column comment containing booleans is not used, as you do not use it in your initial query?

Related

Month over Month percent change in user registrations

I am trying to write a query to find month over month percent change in user registration. \
Users table has the logs for user registrations
user_id - pk, integer
created_at - account created date, varchar
activated_at - account activated date, varchar
state - active or pending, varchar
I found the number of users for each year and month. How do I find month over month percent change in user registration? I think I need a window function?
SELECT
EXTRACT(month from created_at::timestamp) as created_month
,EXTRACT(year from created_at::timestamp) as created_year
,count(distinct user_id) as number_of_registration
FROM users
GROUP BY 1,2
ORDER BY 1,2
This is the output of above query:
Then I wrote this to find the difference in user registration in the previous year.
SELECT
*
,number_of_registration - lag(number_of_registration) over (partition by created_month) as difference_in_previous_year
FROM (
SELECT
EXTRACT(month from created_at::timestamp) as created_month
,EXTRACT(year from created_at::timestamp) as created_year
,count( user_id) as number_of_registration
FROM users as u
GROUP BY 1,2
ORDER BY 1,2) as temp
The output is this:
You want an order by clause that contains created_year.
number_of_registration
- lag(number_of_registration) over (partition by created_month order by created_year) as difference_in_previous_year
Note that you don't actually need a subquery for this. You can do:
select
extract(year from created_at) as created_year,
extract(month from created_at) as created_year
count(*) as number_of_registration,
count(*) - lag(count(*)) over(partition by extract(month from created_at) order by extract(year from created_at))
from users as u
group by created_year, created_month
order by created_year, created_month
I used count(*) instead of count(user_id), because I assume that user_id is not nullable (in which case count(*) is equivalent, and more efficient). Casting to a timestamp is also probably superfluous.
These queries work as long as you have data for every month. If you have gaps, then the problem should be addressed differently - but this is not the question you asked here.
I can get the registrations from each year as two tables and join them. But it is not that effective
SELECT
t1.created_year as year_2013
,t2.created_year as year_2014
,t1.created_month as month_of_year
,t1.number_of_registration_2013
,t2.number_of_registration_2014
,(t2.number_of_registration_2014 - t1.number_of_registration_2013) / t1.number_of_registration_2013 * 100 as percent_change_in_previous_year_month
FROM
(select
extract(year from created_at) as created_year
,extract(month from created_at) as created_month
,count(*) as number_of_registration_2013
from users
where extract(year from created_at) = '2013'
group by 1,2) t1
inner join
(select
extract(year from created_at) as created_year
,extract(month from created_at) as created_month
,count(*) as number_of_registration_2014
from users
where extract(year from created_at) = '2014'
group by 1,2) t2
on t1.created_month = t2.created_month
First off, Why are you using strings to hold date/time values? Your 1st step should to define created_at, activated_at as a proper timestamps. In the resulting query I assume this correction. If this is faulty (you do not correct it) then cast the string to timestamp in the CTE generating the date range. But keep in mind that if you leave it as text you will at some point get a conversion exception.
To calculate month-over-month use the formula "100*(Nt - Nl)/Nl" where Nt is the number of users this month and Nl is the number of users last month. There are 2 potential issues:
There are gaps in the data.
Nl is 0 (would incur divide by 0 exception)
The following handles this by first generating the months between the earliest date to the latest date then outer joining monthly counts to the generated dates. When Nl = 0 the query returns NULL indication the percent change could not be calculated.
with full_range(the_month) as
(select generate_series(low_month, high_month, interval '1 month')
from (select min(date_trunc('month',created_at)) low_month
, max(date_trunc('month',created_at)) high_month
from users
) m
)
select to_char(the_month,'yyyy-mm')
, users_this_month
, case when users_last_month = 0
then null::float
else round((100.00*(users_this_month-users_last_month)/users_last_month),2)
end percent_change
from (
select the_month, users_this_month , lag(users_this_month) over(order by the_month) users_last_month
from ( select f.the_month, count(u.created_at) users_this_month
from full_range f
left join users u on date_trunc('month',u.created_at) = f.the_month
group by f.the_month
) mc
) pc
order by the_month;
NOTE: There are several places there the above can be shortened. But the longer form is intentional to show how the final vales are derived.

SQL In Oracle - How to search through occurrences in an interval?

I've gotten myself stuck working in Oracle with SQL for the first time. In my library example, I need to make a query on my tables for a library member who has borrowed more than 5 books in some week during the past year. Here's my attempt:
SELECT
PN.F_NAME,
PN.L_NAME,
M.ENROLL_DATE,
COUNT(*) AS BORROWED_COUNT,
(SELECT
(BD.DATE_BORROWED + INTERVAL '7' DAY)
FROM DUAL, BORROW_DETAILS BD
GROUP BY BD.DATE_BORROWED + INTERVAL '7' DAY
HAVING COUNT(*) > 5
) AS VALID_INTERVALS
FROM PERSON_NAME PN, BORROW_DETAILS BD, HAS H, MEMBER M
WHERE
PN.PID = M.PID AND
M.PID = BD.PID AND
BD.BORROWID = H.BORROWID
GROUP BY PN.F_NAME, PN.L_NAME, M.ENROLL_DATE, DATEDIFF(DAY, BD.DATE_RETURNED, VALID_INTERVALS)
ORDER BY BORROWED_COUNT DESC;
As I'm sure you can tell, Im really struggling with the Dates in oracle. For some reason DATEDIFF wont work at all for me, and I cant find any way to evaluate the VALID_INTERVAL which should be another date...
Also apologies for the all caps.
DATEDIFF is not a valid function in Oracle; if you want the difference then subtract one date from another and you'll get a number representing the number of days (or fraction thereof) between the values.
If you want to count it for a week starting from Midnight Monday then you can TRUNCate the date to the start of the ISO week (which will be Midnight of the Monday of that week) and then group and count:
SELECT MAX( PN.F_NAME ) AS F_NAME,
MAX( PN.L_NAME ) AS L_NAME,
MAX( M.ENROLL_DATE ) AS ENROLL_DATE,
TRUNC( BD.DATE_BORROWED, 'IW' ) AS monday_of_iso_week,
COUNT(*) AS BORROWED_COUNT
FROM PERSON_NAME PN
INNER JOIN MEMBER M
ON ( PN.PID = M.PID )
INNER JOIN BORROW_DETAILS BD
ON ( M.PID = BD.PID )
GROUP BY
PN.PID,
TRUNC( BD.DATE_BORROWED, 'IW' )
HAVING COUNT(*) > 5
ORDER BY BORROWED_COUNT DESC;
db<>fiddle
You haven't given your table structures or any sample data so its difficult to test; but you don't appear to need to include the HAS table and I'm assuming there is a 1:1 relationship between person and member.
You also don't want to GROUP BY names as there could be two people with the same first and last name (who happened to enrol on the same date) and should use something that uniquely identifies the person (which I assume is PID).

How to Average Number of Chats per Day on LEFT JOIN table in Snowflake SQL?

In Snowflake SQL dictation, how do I average the number of video chats per day using a field from a table I left joined to the entire query?
I'm thinking I have to do a SUM function to total the number of video chats and then aggregate by # of video chats for each date and then divide by 30 days (the rolling date range I specified throughout my entire query).
Any help would be appreciated as deadlines are approaching. Thank you.
SELECT DISTINCT
t1."pid",
IFNULL(t2."VideoChats",0),
t3."SFUser",
t3."TotalProviders",
t4."dimaccount.practice_specialty",
t5."Account: CMRR",
t6."CreatedDate",
t7."stg_sf_case.Date_Time_Resolved__c",
t8."stg_sf_case.Closed_Date",
t9."pid"
FROM (SELECT "pid"
FROM "EDW_PROD"."PUBLIC"."STG_MYSQL_PROVIDERMODULES" AS a
WHERE a."active"
AND a."status" = 'PURCHASED'
AND a."module_id" = '14'
GROUP BY a."pid"
) t1
LEFT JOIN (SELECT "started_at",
"pid",
COUNT(*) AS "VideoChats"
FROM "EDW_PROD"."PUBLIC"."STG_MYSQL_VIDEOCHATROOM" AS b
LEFT JOIN "EDW_PROD"."PUBLIC"."DIMACCOUNT" AS dimaccount
ON b."pid" = dimaccount."PID"
WHERE b."started_at" >= DATE_TRUNC('month', CURRENT_DATE())
AND b."started_at" < DATEADD('month', 1, DATE_TRUNC('month', CURRENT_DATE()))
AND dimaccount."CurrentRow" = 'Y'
GROUP BY b."pid", b."started_at"
) t2 ON t1."pid" = t2."pid"
For a rolling average you probably want to use a window function. Something along these lines.
SELECT AVG(VideoChats) over (partition by pid order by started_at rows between 30 preceding and current row) as AvgVideoChats
--I saw a post about AVG not allowing a sliding window, so you may have to do this instead
SELECT SUM(VideoChats) over (partition by pid order by started_at rows between 30 preceding and current row) / 30. as AvgVideoChats
You may need to do this in a wrapper around your t2 query and adjust your date filters so that there are values available for averaging, but I'm not quite clear enough on what your query is doing with dates, or what results you are looking for, to be sure.

SQL Statement Only latest entry of the day

seems it is too long ago that I needed create own SQL Statements. I have a table (GAS_COUNTER) with timestamps (TS) and values (VALUE).
There are hundreds of entries per day, but I only need the latest of the day. I tried different ways but never get what I need.
Edit
Thanks for the fast replies, but some do not meet my needs (I need the latest value of each day in the table) and some don't work. My best own statement was:
select distinct (COUNT),
from
(select
extract (DAY_OF_YEAR from TS) as COUNT,
extract (YEAR from TS) as YEAR,
extract (MONTH from TS) as MONTH,
extract (DAY from TS) as DAY,
VALUE as VALUE
from GAS_COUNTER
order by COUNT)
but the value is missing. If I put it in the first select all rows return. (logical correct as every line is distinct)
Here an example of the Table content:
TS VALUE
2015-07-25 08:47:12.663 0.0
2015-07-25 22:50:52.155 2.269999999552965
2015-08-10 11:18:07.667 52.81999999284744
2015-08-10 20:29:20.875 53.27999997138977
2015-08-11 10:27:21.49 54.439999997615814
2nd Edit and solution
select TS, VALUE from GAS_COUNTER
where TS in (
select max(TS) from GAS_COUNTER group by extract(DAY_OF_YEAR from TS)
)
This one would give you the very last record:
select top 1 * from GAS_COUNTER order by TS desc
Here is one that would give you last records for every day:
select VALUE from GAS_COUNTER
where TS in (
select max(TS) from GAS_COUNTER group by to_date(TS,'yyyy-mm-dd')
)
Depending on the database you are using you might need to replace/adjust to_date(TS,'yyyy-mm-dd') function. Basically it should extract date-only part from the timestamp.
Select the max value for the timestamp.
select MAX(TS), value -- or whatever other columns you want from the record
from GAS_COUNTER
group by value
Something like this would window the data and give you the last value on the day - but what happens if you get two TS the same? Which one do you want?
select *
from ( select distinct cast( TS as date ) as dt
from GAS_COUNTER ) as gc1 -- distinct days
cross apply (
select top 1 VALUE -- last value on the date.
from GAS_COUNTER as gc2
where gc2.TS < dateadd( day, 1, gc1.dt )
and gc2.TS >= gc1.dt
order by gc2.TS desc
) as x

Select one row per day for each value

I have a SQL query in PostgreSQL 9.4 that, while more complex due to the tables I am pulling data from, boils down to the following:
SELECT entry_date, user_id, <other_stuff>
FROM <tables, joins, etc>
GROUP BY entry_date, user_id
WHERE <whatever limits I want, such as limiting the date range or users>
With the result that I have one row per user, per day for which I have data. In general, this query would be run for an entry_date period of one month, with the desired result of having one row per day of the month for each user.
The problem is that there may not be data for every user every day of the month, and this query only returns rows for days that have data.
Is there some way to modify this query so it returns one row per day for each user, even if there is no data (other than the date and the user) in some of the rows?
I tried doing a join with a generate_series(), but that didn't work - it can make there be no missing days, but not per user. What I really need would be something like "for each user in list, generate series of (user,date) records"
EDIT: To clarify, the final result that I am looking for would be that for each user in the database - defined as a record in a user table - I want one row per date. So if I specify a date range of 5/1/15-5/31/15 in my where clause, I want 31 rows per user, even if that user had no data in that range, or only had data for a couple of days.
generate_series() was the right idea. You probably did not get the details right. Could work like this:
WITH cte AS (
SELECT entry_date, user_id, <other_stuff>
FROM <tables, joins, etc>
GROUP BY entry_date, user_id
WHERE <whatever limits I want>
)
SELECT *
FROM (SELECT DISTINCT user_id FROM cte) u
CROSS JOIN (
SELECT entry_date::date
FROM generate_series(current_date - interval '1 month'
, current_date - interval '1 day'
, interval '1 day') entry_date
) d
LEFT JOIN cte USING (user_id, entry_date);
I picked a running time window of one month ending "yesterday". You did not define your "month" exactly.
Assuming entry_date to be data type date.
Simpler for your updated requirements
To get results for every user in a users table (and not for a current selection) and for your given time range, it gets simpler. You don't need the CTE:
SELECT *
FROM (SELECT user_id FROM users) u
CROSS JOIN (
SELECT entry_date::date
FROM generate_series(timestamp '2015-05-01'
, timestamp '2015-05-31'
, interval '1 day') entry_date
) d
LEFT JOIN (
SELECT entry_date, user_id, <other_stuff>
FROM <tables, joins, etc>
GROUP BY entry_date, user_id
WHERE <whatever>
) t USING (user_id, entry_date);
Why this particular way to call generate_series()?
Generating time series between two dates in PostgreSQL
And best use ISO 8601 date format (YYYY-MM-DD) which works regardless of locale settings.