Hive aggregate columns based on different conditions - select

Assume my table looks like this:
cust_id, domain, year, mon, day
1, google.au, 2018, 10, 1
2, virgin.com.au, 2018, 10, 1
3, hotmail.au, 2018, 10, 1
4, yahoo.au, 2018, 10, 1
1, foobar.au, 2018, 10, 1
3, foobar.com.au, 2018, 10, 1
15, haha.com, 2018, 10, 1
11, hehe.net, 2018, 10, 1
I need to group by year/mon/day and aggregate columns based on different conditions:
1) count of distinct domains ending with .au but not .com.au
2) count of distinct domains ending with .com.au
3) count of distinct hostnames where cust_id in a specific list, let's assume (1, 2, 3, 4)
4) count of all distinct hostnames
So my output would look like:
2018, 10, 1, 4, 2, 6, 8
I'm leaning towards using subqueries for each condition and then joining them:
select condition_1.year, condition_1.mon, condition_1.day, condition_1.c1, condition_3.c3, condition_4.c4
from
(select year, mon, day, count(distinct domain) c1 from mytable where year = 2018 and mon = 10 and day = 1
and domain rlike '[.]au' and domain not rlike '[.]com[.]au'
group by year, mon, day) condition_1
full outer join
(select count(distinct domain) c2 from mytable where year = 2018 and mon = 10 and day = 1
and domain rlike '[.]com[.]au') condition_2
full outer join
(select count(distinct domain) c3 from mytable where year = 2018 and mon = 10 and day = 1
and cust_id in (1, 2, 3, 4)) condition_3
full outer join
(select count(distinct hostname) c4 from mytable where year = 2018 and mon = 10 and day = 1) condition_4
This seems horribly inefficient, though I can't think of a better way.
The CASE statement would not work here as I need distinct counts.
How could I achieve this more efficiently?

This can be accomplished with regular expressions and with conditional aggregation.
select year,mon,day
,count(distinct case when domain regexp '(?<!\.com)\.au$' then domain end) as ends_with_au
,count(distinct case when domain regexp '\.com\.au$' then domain end) as ends_with_com_au
,count(distinct case when cust_id in (1,2,3,4) then domain end) as specific_cust
,count(distinct domain) as all_domains
from mytable
group by year,mon,day
The regexp (?<!\.com)\.au$ uses a negative lookbehind assertion to check for the preceding characters to .au are not .com. $ metacharacter means match .au as the last 3 characters in the string. . has to be escaped with \.

Use collect_set() - it collects distinct set, ignoring NULLs, use size function to get the number of elements (already distinct):
select
year, mon, day,
size(condition_1) as condition_1_cnt,
size(condition_2) as condition_2_cnt,
size(condition_3) as condition_3_cnt,
size(condition_4) as condition_4_cnt
from
(
select year, mon, day,
collect_set(case when domain rlike '(?<![.]com)[.]au' then domain end) condition_1,
collect_set(case when domain rlike '[.]com[.]au' then domain end) condition_2,
collect_set(case when cust_id in (1, 2, 3, 4) then domain end) condition_3,
collect_set(hostname) condition_4
from mytable
where year = 2018 and mon = 10 and day = 1
group by year, mon, day
)s;

Related

Cohort Analysis with RedShift by Month

I am trying to build a cohort analysis for monthly retention but experiencing challenge getting the Month Number column right. The month number is supposed to return month(s) user transacted i.e 0 for registration month, 1 for the first month after registration month, 2 for the second month until the last month but currently, it returns negative month numbers in some cells.
It should be like this table:
cohort_month total_users month_number percentage
---------- ----------- -- ------------ ---------
January 100 0 40
January 341 1 90
January 115 2 90
February 103 0 73
February 100 1 40
March 90 0 90
Here is the SQL:
with cohort_items as (
select
extract(month from insert_date) as cohort_month,
msisdn as user_id
from mfscore.t_um_user_detail where extract(year from insert_date)=2020
order by 1, 2
),
user_activities as (
select
A.sender_msisdn,
extract(month from A.insert_date)-C.cohort_month as month_number
from mfscore.t_wm_transaction_logs A
left join cohort_items C ON A.sender_msisdn = C.user_id
where extract(year from A.insert_date)=2020
group by 1, 2
),
cohort_size as (
select cohort_month, count(1) as num_users
from cohort_items
group by 1
order by 1
),
B as (
select
C.cohort_month,
A.month_number,
count(1) as num_users
from user_activities A
left join cohort_items C ON A.sender_msisdn = C.user_id
group by 1, 2
)
select
B.cohort_month,
S.num_users as total_users,
B.month_number,
B.num_users * 100 / S.num_users as percentage
from B
left join cohort_size S ON B.cohort_month = S.cohort_month
where B.cohort_month IS NOT NULL
order by 1, 3
I think the RANK window function is the right solution. So the idea is to assigne a rank to months of user activities for each user, order by year and month.
Something like:
WITH activity_per_user AS (
SELECT
user_id,
event_date,
RANK() OVER (PARTITION BY user_id ORDER BY DATE_PART('year', event_date) , DATE_PART('month', event_date) ASC) AS month_number
FROM user_activities_table
)
RANK number starts from 1, so you may want to substract 1.
Then, you can group by user_id and month_number to get the number of interactions for each user per month from the subscription (adapt to your use case accordingly).
SELECT
user_id,
month_number,
COUNT(1) AS n_interactions
FROM activity_per_user
GROUP BY 1, 2
Here is the documentation:
https://docs.aws.amazon.com/redshift/latest/dg/r_WF_RANK.html

7 Day Return/Retention Rate

I've been trying to calculate 7 Day Return Rate (also known as Classic Retention Rate, as described here: https://www.braze.com/blog/calculate-retention-rate/) and then taking a 30 day average to reduce noise in Postgresql.
However, I'm sure I'm doing something wrong. First of all, the numbers look waaay higher than intuitively I feel they should be (generally around 5% for the rest of the sector). Also, I believe the first 7 days should show 0, as theoretically users should take at least 7 days to count as a "return". However, I get around 40-70%, as shown below.
Would someone mind taking a look at the code below and seeing if there are any errors? 7 Day Return Rate is a really common metric for apps, and I haven't found any questions using postgresql that calculate it to this level of sophistication on Stack Exchange (or even the rest of the web), so I feel like a solid response could be very useful to a lot of people.
Sample data
Wednesday, August 1, 2018 12:00 AM 71.14
Thursday, August 2, 2018 12:00 AM 55.44
Friday, August 3, 2018 12:00 AM 50.09
Saturday, August 4, 2018 12:00 AM 45.81
Sunday, August 5, 2018 12:00 AM 43.27
Monday, August 6, 2018 12:00 AM 40.61
Tuesday, August 7, 2018 12:00 AM 39.38
Wednesday, August 8, 2018 12:00 AM 38.46
Thursday, August 9, 2018 12:00 AM 36.81
Friday, August 10, 2018 12:00 AM 35.94
with
user_first_event as (
select distinct id, min(timestamp)::date as first_event_date
from log
where
timestamp <= current_date
and timestamp >= {{start_date}} and timestamp <= {{end_date}}
group by id),
event as (
select distinct id, timestamp::date as user_event_date
from log
where timestamp <= current_date and timestamp >= {{start_date}}),
gap as (
select
user_first_event.id,
user_first_event.first_event_date,
event.user_event_date,
event.user_event_date - user_first_event.first_event_date as days_since_signup
from user_first_event
join event on user_first_event.id = event.id
where user_first_event.first_event_date <= event.user_event_date),
conversion_rate as (
select
first_event_date,
(sum(case when days_since_signup = 7 then 1 else 0 end) * 100.0 /
count(distinct id)
) as seven_day_retention_rate
from gap
group by first_event_date
)
SELECT first_event_date,
AVG(seven_day_retention_rate)
OVER(ORDER BY first_event_date ROWS BETWEEN 29 PRECEDING AND CURRENT ROW) AS rolling_avg_retention_rate
FROM conversion_rate
The problem is a bit easier than your query makes it seem, you can actually do it with just one subquery and one out query as follows:
select first_event_date
, avg(seven_day_return) as seven_day_return_day_only
, avg( avg(seven_day_return) ) OVER(ORDER BY first_event_date asc ROWS BETWEEN 29 preceding AND CURRENT ROW ) AS thirty_day_rolling_retention
from (
--inner query to get value for user, 1 if they retain and 0 if they do not
select min(timestamp)::date as first_event_date
, case when array_agg(timestamp::date) #> ARRAY[ (min(timestamp)::date + 7) ] then 1 else 0 end as seven_day_return
from log
group by id ) t
group by t.first_event_date;
Note that this weights each day equally rather than each user equally across days. If you want to weight the average by user across days then you can update the outer calculation using more aggregates and windows to compute the value with weightings.
Reference: http://sqlfiddle.com/#!17/ee17e/1/0
If you don't have access to array_agg (but have access to window functions) you can use:
select first_event_date
, avg(seven_day_return) as day_seven_day_return
, avg( avg(seven_day_return) ) OVER(ORDER BY first_event_date asc ROWS BETWEEN 29 preceding AND CURRENT ROW ) AS thirty_day_rolling_retention
from (
--inner query to get value for user
select min(timestamp)::date as first_event_date
, case when exists(select 1 from log l2 where l2.id = log.id and l2.timestamp::date = min(log.timestamp)::date + 7) then 1 else 0 end as seven_day_return
from log
group by id ) t
group by t.first_event_date;

Capture first character of last group of 1s in a binary series

I have a series something like this:
Month J F M A M J J A S O N D
Status 1 0 0 1 0 1 0 0 1 1 1 1
Using t-SQL, I am trying to capture the month corresponding to the first 1 in the last group of 1s, i.e., September in this example.
Here is the code I'm using:
IF OBJECT_ID('tempdb..#Temp1') IS NOT NULL DROP TABLE #Temp1
;WITH PARTITIONED1 AS
(SELECT , t0.ID
, t0.Year_Month
, t0.Status
, LAST_VALUE(t0.Year_Month) OVER (PARTITION BY t0.ID ORDER BY t0.Year_Month) AS D_YM
, ROW_NUMBER() OVER (PARTITION BY t0.ID ORDER BY t0.Year_Month) AS rn1
FROM #Temp0 t0
However, this just returns the first occurence of a 1; January here.
I really can't figure this one out, so any help would be very much appreciated.
Carefull with
although the ordering is performed in a previous stage
The previous sorting does not guarantee the later processing!
Try something like this. It is a very simple approach where you rely on gapless IDs:
DECLARE #tbl TABLE(ID INT IDENTITY,Mnth VARCHAR(100),[Status] TINYINT);
INSERT INTO #tbl VALUES
('J',1)
,('F',0)
,('M',0)
,('A',1)
,('M',0)
,('J',1)
,('J',0)
,('A',0)
,('S',1)
,('O',1)
,('N',1)
,('D',1);
SELECT a.*
FROM #tbl AS a
WHERE a.ID=(SELECT MAX(b.ID)+1 FROM #tbl AS b WHERE b.[Status]=0)
this can also be used :
select top 1 Month from table t where Status=1
and not exists
(select id from table t1 where stat=0 and t1.id>t.id)
order by t.id
I might have overcomplicated this but not knowing the table structure I put the below together:
IF OBJECT_ID('tempdb..#Temp1') IS NOT NULL DROP TABLE #Temp1
CREATE TABLE #Temp1
(
Jan int,
Feb int,
Mar int,
Apr int,
May int,
June int,
July int ,
Aug int,
Sep int,
Oct int,
Nov int,
Dec int
)
insert into #temp1
select
1, 0, 0, 1, 0, 1, 0, 0, 1, 1, 1, 1
IF OBJECT_ID('tempdb..#monthTranslate') IS NOT NULL DROP TABLE #monthTranslate
create table #monthTranslate
(
MonthValue varchar(50),
MonthInt int
)
insert into #monthTranslate
select 'Jan',1
union all select 'Feb',2
union all select 'Mar',3
union all select 'Apr',4
union all select 'May',5
union all select 'June',6
union all select 'July',7
union all select 'Aug',8
union all select 'Sep',9
union all select 'OCt',10
union all select 'Nov',11
union all select 'Dec',12
--find the max month w\ 0 and add 1... becareful on null, it might return January incorrectly. I'd check for that in a a case statement
select max(b.MonthInt)+1
from
(
select
MonthPassVal, months , t.MonthInt
from
(
select Jan, Feb, Mar, Apr, May, June, July, Aug, Sep, Oct, Nov, Dec
from #temp1
) as r
Unpivot
(
MonthPassVal for Months
in (Jan, Feb, Mar, Apr, May, June, July, Aug, Sep, Oct, Nov, Dec)
) as u
inner join #monthTranslate t
on t.MonthValue = months
) as b
where
MonthPassVal=0

Insert subquery date according to day

I would like to insert subquery a date based on it day. Plus, each date can only be used four times. Once it reached fourth times, the fifth value will use another date of same day. In other word, use date of Monday of next week. Example, Monday with 6 JUNE 2016 to Monday with 13 JUNE 2016 (you may check the calendar).
I have a query of getting a list of date based on presentationdatestart and presentationdateend from presentation table:
select a.presentationid,
a.presentationday,
to_char (a.presentationdatestart + delta, 'DD-MM-YYYY', 'NLS_CALENDAR=GREGORIAN') list_date
from presentation a,
(select level - 1 as delta
from dual
connect by level - 1 <= (select max (presentationdateend - presentationdatestart)
from presentation))
where a.presentationdatestart + delta <= a.presentationdateend
and a.presentationday = to_char(a.presentationdatestart + delta, 'fmDay')
order by a.presentationdatestart + delta,
a.presentationid; --IMPORTANT!!!--
For example,
presentationday presentationdatestart presentationdateend
Monday 01-05-2016 04-06-2016
Tuesday 01-05-2016 04-06-2016
Wednesday 01-05-2016 04-06-2016
Thursday 01-05-2016 04-06-2016
The query result will list all possible dates between 01-05-2016 until 04-06-2016:
Monday 02-05-2016
Tuesday 03-05-2016
Wednesday 04-05-2016
Thursday 05-05-2016
....
Monday 30-05-2016
Tuesday 31-05-2016
Wednesday 01-06-2016
Thursday 02-06-2016 (20 rows)
This is my INSERT query :
insert into CSP600_SCHEDULE (studentID,
studentName,
projectTitle,
supervisorID,
supervisorName,
examinerID,
examinerName,
exavailableID,
availableday,
availablestart,
availableend,
availabledate)
select '2013816591',
'mong',
'abc',
'1004',
'Sue',
'1002',
'hazlifah',
2,
'Monday', //BASED ON THIS DAY
'12:00:00',
'2:00:00',
to_char (a.presentationdatestart + delta, 'DD-MM-YYYY', 'NLS_CALENDAR=GREGORIAN') list_date //FOR AVAILABLEDATE
from presentation a,
(select level - 1 as delta
from dual
connect by level - 1 <= (select max (presentationdateend - presentationdatestart)
from presentation))
where a.presentationdatestart + delta <= a.presentationdateend
and a.presentationday = to_char(a.presentationdatestart + delta, 'fmDay')
order by a.presentationdatestart + delta,
a.presentationid;
This query successfully added 20 rows because all possible dates were 20 rows. I would like modify the query to be able to insert based on availableDay and each date can only be used four times for each different studentID.
Possible outcome in CSP600_SCHEDULE (I am removing unrelated columns to ease readability):
StudentID StudentName availableDay availableDate
2013 abc Monday 01-05-2016
2014 def Monday 01-05-2016
2015 ghi Monday 01-05-2016
2016 klm Monday 01-05-2016
2010 nop Tuesday 02-05-2016
2017 qrs Tuesday 02-05-2016
2018 tuv Tuesday 02-05-2016
2019 wxy Tuesday 02-05-2016
.....
2039 rrr Monday 09-05-2016
.....
You may check the calendar :)
I think what you're asking for is to list your students and then batch them up in groups of 4 - each batch is then allocated to a date. Is that right?
In which case something like this should work (I'm using a list of tables as the student names just so I don't need to insert any data into a custom table) :
WITH students AS
(SELECT table_name
FROM all_tables
WHERE rownum < 100
)
SELECT
table_name
,SYSDATE + (CEIL(rownum/4) -1)
FROM
students
;
I hope that helps you
...okay, following your comments, I think this might be a better solution :
WITH students AS
(SELECT table_name student_name
FROM all_tables
WHERE rownum < 100
)
, dates AS
(SELECT TRUNC(sysdate) appointment_date from dual UNION
SELECT TRUNC(sysdate+2) from dual UNION
SELECT TRUNC(sysdate+4) from dual UNION
SELECT TRUNC(sysdate+6) from dual UNION
SELECT TRUNC(sysdate+8) from dual UNION
SELECT TRUNC(sysdate+10) from dual UNION
SELECT TRUNC(sysdate+12) from dual UNION
SELECT TRUNC(sysdate+14) from dual
)
SELECT
s.student_name
,d.appointment_date
FROM
--get a list of students each with a sequential row number, ordered by student name
(SELECT
student_name
,ROW_NUMBER() OVER (ORDER BY student_name) rn
FROM students
) s
--get a list of available dates with a sequential row number, ordered by date
,(SELECT
appointment_date
,ROW_NUMBER() OVER (ORDER BY appointment_date) rn
FROM dates
) d
WHERE 1=1
--allocate the first four students to date rownumber1, next four students to date rownumber 2...
AND CEIL(s.rn/4) = d.rn
;

Postgres: longest streak per developer regardless of Saturdays and Sundays

I got the information I needed from my last post about Postgres: Defining the longest streak (in days) per developer.
However now I want know the longest streak per developer regardless of Saturdays or Sundays. For instance, Bob worked from Thursday 18, Friday 19, Monday 22 and Tuesday 23, hence Bob streak is 4 days.
I understand I can use the DOW window function, which gives me 0 as Sunday , 1 Monday and so on. But
I don’t see how I can apply DOW function in the last solution proposed by Gordon Linoff.
Can some of you help me in this matter? Cheers,
WITH
working_limits AS (
SELECT
MIN(mr_date) AS start_date,
MAX(mr_date) AS end_date
FROM
xxx
),
working_days AS (
SELECT
ROW_NUMBER() OVER () AS day_number,
s.d::date AS date
FROM
GENERATE_SERIES((SELECT start_date FROM working_limits),
(SELECT end_date FROM working_limits),
'1 day') AS s(d)
WHERE
EXTRACT(dow FROM s.d) BETWEEN 1 AND 5),
worked_days AS (
SELECT
ROW_NUMBER() OVER () AS day_number,
developer,
mr_date AS date
FROM
xxx
ORDER BY
developer,
mr_date
)
SELECT
y.developer,
MAX(y.days)
FROM (
SELECT
x.developer,
COUNT(*) AS days
FROM (
SELECT
wngd.date,
wd.developer,
wngd.day_number - wd.day_number AS delta
FROM
working_days wngd INNER JOIN worked_days wd
ON
wngd.date = wd.date) AS x
GROUP BY
x.developer,
x.delta) AS y
GROUP BY
y.developer;