The title must be confusing, but the thing I am trying to do is very easy to understand with an example. I have a table like this:
Code Date_ Ratio
73245 Jan 1 1975 12:00AM 10
73245 Apr 18 2006 12:00AM 4
73245 Dec 26 2007 12:00AM 10
73245 Jan 30 2009 12:00AM 4
73245 Apr 21 2011 12:00AM 2
Basically for each security it gives some ratio for it with a date when the ratio starts to be effective. This table will be much easier to use if instead of just having a start date, it has a pair of start date and end date, like the following:
Code StartDate_ EndDate_ Ratio
73245 Jan 1 1975 12:00AM Apr 18 2006 12:00AM 10
73245 Apr 18 2006 12:00AM Dec 26 2007 12:00AM 4
73245 Dec 26 2007 12:00AM Jan 30 2009 12:00AM 10
73245 Jan 30 2009 12:00AM Apr 21 2011 12:00AM 4
73245 Apr 21 2011 12:00AM Dce 31 2049 12:00AM(or some random date in far future) 2
How do I transform the original table to the table I want using SQL statements? I have little experience with SQL and I could not figure how.
Please help! Thanks!
In SQL Server 2012:
SELECT code,
date_ AS startDate,
LEAD(date_) OVER (PARTITION BY code ORDER BY date_) AS endDate,
ratio
FROM mytable
In SQL Server 2005 and 2008:
WITH q AS
(
SELECT *,
ROW_NUMBER() OVER (PARTITION BY code ORDER BY date_) AS rn
FROM mytable
)
SELECT q1.code, q1.date_ AS startDate, q2.date_ AS endDate, q1.ratio
FROM q q1
LEFT JOIN
q q2
ON q2.code = q1.code
AND q2.rn = q1.rn + 1
Maybe it would also be possible to use OUTER APPLY, something like:
SELECT t1.Code, t1.Date_ AS StartDate_, ISNULL(t2.EndDate_, CAST('20491231' AS DATETIME)) AS EndDate_
FROM t1 AS t1o
OUTER APPLY
(
SELECT TOP 1 Date_ AS EndDate_
FROM t1
WHERE t1.Code = t1o.Code AND t1.Date_ > t1o.Date_
ORDER BY t1.Date_ ASC
) AS t2
Related
I have a table that is structured like the below - this contains details about all customer subscriptions and when they start/end.
SubKey
CustomerID
Status
StartDate
EndDate
29333
102
7
01 jan 2013
1 Jan 2014
29334
102
6
7 Jun 2013
15 Jun 2022
29335
144
6
10 jun 2021
17 jun 2022
29336
144
2
8 oct 2023
10 oct 2025
I am trying to add an indicator flag to this table (either "yes" or "no") which shows me by each row, if when the [EndDate] of the SubKey is the last one for that CustomerID. So for the above example..
SubKey
CustomerID
Status
StartDate
EndDate
IsLast
29333
102
7
01 jan 2013
1 Jan 2014
No
29334
102
6
7 Jun 2013
15 Jun 2022
Yes
29335
144
6
10 jun 2021
17 jun 2022
Yes
29336
144
2
8 oct 2023
10 oct 2025
Yes
The flag is set to No for the first row, because on 1 Jan 2014, customerID 102 had another SubKey (29334) still active at the time (which didn't end until 15 jun 2022)
The rest of the rows are set to "Yes" because these were the last active subscriptions per CustomerID.
I have been reading about the LAG function which may be able to help. I am just not sure how to make it fit in this scenario.
Probably the easiest method would to use exists with a correlation. Can you try the following for your desired results for excluding rows without an overlap:
select *,
case when exists (
select * from t t2
where t2.customerId = t.customerId
and t2.enddate > t.enddate
and t2.startDate < t.Enddate
) then 'No' else 'Yes' end as IsLast
from t;
Imagine you've got a table similar to this:
|email | purchase_date |
|:--------------|:---------------------|
|stan#gmail.com | Jun 30 2020 12:00AM |
|stan#gmail.com | Aug 05 2020 5:00PM |
|stan#gmail.com | Mar 22 2018 3:00AM |
|eric#yahoo.com | Aug 05 2020 5:00PM |
|eric#yahoo.com | Mar 22 2018 3:00PM |
|kyle#gmail.com | Mar 22 2018 3:00PM |
|kyle#gmail.com | Jun 30 2020 12:00AM |
|kyle#gmail.com | Aug 05 2020 5:00PM |
|kenny#gmail.com| Aug 05 2020 5:00PM |
Totally random. The actual database I work with is actually more complex with much more columns.
Both the columns are STRING type. Which is not convenient. The purchase date should be DATE type. Kenny made only one purchase, so there shouldn't be any row for him in the result table.
Also notice that a there's a lot of identical dates.
I'd like to select the email and the 2nd oldest purchase date (named as 'second_purchase') for each email address, so that the result looks like this:
|email | second_purchase |
|:--------------|:-------------------- |
|stan#gmail.com | Jun 30 2020 12:00AM |
|eric#yahoo.com | Aug 05 2021 5:00PM |
|kyle#gmail.com | Jun 30 2020 12:00AM |
I can't seem to get the logic or syntax right. I don't want to put all my codes in here, because I've tried many variations of my idea...
It didn't seem to work somehow. But I'd love to see an example code from someone skilled in SQL. My idea is maybe not that great..:-)
This version is actually SOQL (Salesforce Object Query Language). That could be important.
Sorry for not styling the table properly, I didn't seem to work either, even when I used the recommended styling. I wasn't able to post. That was actually quite frustrating.
Anyway, thank you for any help!
You could try the following sql which uses a dense_rank over each user's email and orders by a casted purchase_date
Query #1
WITH date_converted_table AS (
SELECT
email,
purchase_date,
DENSE_RANK() OVER (
PARTITION BY email
ORDER BY CAST(purchase_date as timestamp) ASC
) dr
FROM
mytable
)
SELECT
email,
purchase_date as second_purchase
FROM
date_converted_table
WHERE dr=2;
email
second_purchase
eric#yahoo.com
Aug 05 2020 5:00PM
kyle#gmail.com
Jun 30 2020 12:00AM
stan#gmail.com
Jun 30 2020 12:00AM
Query #2
SELECT
email,
purchase_date as second_purchase
FROM (
SELECT
email,
purchase_date,
DENSE_RANK() OVER (
PARTITION BY email
ORDER BY CAST(purchase_date as timestamp) ASC
) dr
FROM
mytable
) tb
WHERE dr=2;
email
second_purchase
eric#yahoo.com
Aug 05 2020 5:00PM
kyle#gmail.com
Jun 30 2020 12:00AM
stan#gmail.com
Jun 30 2020 12:00AM
View on DB Fiddle
Update 1
As it pertains to follow up question in comment:
Is it possible to upgrade the result so that there are first_purchase
dates (where dr=1) adn second_purchase dates (where dr=2) in separate
columns?
A case expression and aggregation may assist you as shown below. The having clause ensures that there is both a first and second purchase date.
SELECT
email,
MAX(CASE
WHEN dr=1 THEN purchase_date
END) as first_purchase,
MAX(CASE
WHEN dr=2 THEN purchase_date
END) as second_purchase
FROM (
SELECT
email,
purchase_date,
DENSE_RANK() OVER (
PARTITION BY email
ORDER BY CAST(purchase_date as timestamp) ASC
) dr
FROM
mytable
) tb
GROUP BY email
HAVING
SUM(
CASE WHEN dr=1 THEN 1 ELSE 0 END
) > 0 AND
SUM(
CASE WHEN dr=2 THEN 1 ELSE 0 END
) > 0;
email
first_purchase
second_purchase
eric#yahoo.com
Mar 22 2018 3:00PM
Aug 05 2020 5:00PM
kyle#gmail.com
Mar 22 2018 3:00PM
Jun 30 2020 12:00AM
stan#gmail.com
Mar 22 2018 3:00AM
Jun 30 2020 12:00AM
View on DB Fiddle
Let me know if this works for you.
My dataset:
Date Num_orders
Mar 21 2019 69
Mar 22 2019 82
Mar 24 2019 312
Mar 25 2019 199
Mar 26 2019 2,629
Mar 27 2019 2,819
Mar 28 2019 3,123
Mar 29 2019 3,332
Mar 30 2019 1,863
Mar 31 2019 1,097
Apr 01 2019 1,578
Apr 02 2019 2,353
Apr 03 2019 2,768
Apr 04 2019 2,648
Apr 05 2019 3,192
Apr 06 2019 2,363
Apr 07 2019 1,578
Apr 08 2019 3,090
Apr 09 2019 3,814
Apr 10 2019 3,836
...
I need to calculate the monthly median number of orders from days of the same month:
The desired results:
Month Median_monthly
Mar 2019 1,863
Apr 2019 2,768
May 2019 2,876
Jun 2019 ...
...
I tried to use function date_trunc to extract month from the dataset then group by 'month' but it didn't work out. Thanks for your help, I use Google Bigquery (#standard) environment!
Probably you tried to use PERCENTILE_CONT which can not be used with GROUP BY:
Try to use APPROX_QUANTILES(x, 100)[OFFSET(50)]. It should work with GROUP BY.
SELECT APPROX_QUANTILES](Num_orders, 100)\[OFFSET(50)\] AS median
FROM myTable
GROUP BY Month
Alternativele you can use PERCENTILE_CONT within subquery:
SELECT
DISTINCT Month, median
FROM (
SELECT
Month,
PERCENTILE_CONT(Num_orders, 0.5) OVER(PARTITION BY Month) AS median
FROM myTable
)
This would often be done using DISTINCT:
SELECT DISTINCT DATE_TRUNC(month, date),
PERCENTILE_CONT(Num_orders, 0.5) OVER (PARTITION BY DATE_TRUNC(month, date) AS median
FROM myTable;
Note: There are two percentile functions, PERCENTILE_CONT() and PERCENTILE_DISC(). They have different results when there is a "tie" in the middle of the data.
So I am doing a cohort analysis for customers, where a cohort is a group of people who started using the product in the same month. I then keep track of each cohort's total use for every subsequent month up till present time.
For example, the first "cohort month" is January 2012, then I have "use months" January 12, Feb 12, March 12, ..., March 17(current month). One column is "cohort month", and another is "use month". This process repeats for every subsequent cohort month. The table looks like:
Jan 12 | Jan 12
Jan 12 | Feb 12
...
Jan 12 | Mar 17
Feb 12 | Feb 12
Feb 12 | Mar 12
...
Feb 12 | Mar 17
...
Feb 17 | Feb 17
Feb 17 | Mar 17
Mar 17 | Mar 17
The problem arises because I want to do forecasting for one year out for both existing and future cohorts.
That means for the Jan 12 cohort, I want to do prediction for April 17 to Mar 18.
I also want to do predictions for the April 17 cohort (which doesn't exist yet) from April 17 to Mar 18. And so on till predictions for the Mar 18 cohort in Mar 18.
I can handle the predictions, don't worry about that.
My issue is that I cannot figure out how to add in this list of (April 17 .. Mar 17) in the "use month" column before every cohort switches.
I also need to add in cohorts April 17 to Mar 18, and have the applicable parts of this list of (April 17 ... Mar 17) for each of these future cohorts.
So I want the table to look like:
Jan 12 | Jan 12
Jan 12 | Feb 12
...
Jan 12 | Mar 17
Jan 12 | Apr 17
..
Jan 12 | Mar 18
Feb 12 | Feb 12
Feb 12 | Mar 12
...
Feb 12 | Mar 17
Feb 12 | Apr 17
...
Feb 12 | Mar 18
...
...
Feb 17 | Feb 17
Feb 17 | Mar 17
...
Feb 17 | Mar 18
Mar 17 | Mar 17
...
Mar 17 | Mar 18
I know the first solution to come to mind is to do a create a list of all dates Jan 12 to Mar 18, cross join it to itself, and then left outer join to the current table I have (where cohort / use months range from Jan 12 to Mar 17). However, this is not scalable.
Is there a way I can just iteratively add in this list of the months of the next year?
I am using HP Vertica, could use Presto or Hive if absolutely necessary
I think you should use the query here below to create a temporary table out of nothing, and join it with the rest of your query. You can't do anything in a procedural manner in SQL, I'm afraid. You won't be able to get away without a CROSS JOIN. But here, you limit the CROSS JOIN to the generation of the first-of-month pairs that you need.
Here goes:
WITH
-- create a list of integers from 0 to 100 using the TIMESERIES clause
i(i) AS (
SELECT dt::DATE - '2000-01-01'::DATE
FROM (
SELECT '2000-01-01'::DATE + 0
UNION ALL SELECT '2000-01-01'::DATE + 100
) d(d)
TIMESERIES dt AS '1 day' OVER(ORDER BY d::TIMESTAMP)
)
,
-- limits are Jan-2012 to the first of the current month plus one year
month_limits(month_limit) AS (
SELECT '2012-01-01'::DATE
UNION ALL SELECT ADD_MONTHS(TRUNC(CURRENT_DATE,'MONTH'),12)
)
-- create the list of possible months as a CROSS JOIN of the i table
-- containing the integers and the month_limits table, using ADD_MONTHS()
-- and the smallest and greatest month of the month limits
,month_list AS (
SELECT
ADD_MONTHS(MIN(month_limit),i) AS month_first
FROM month_limits CROSS JOIN i
GROUP BY i
HAVING ADD_MONTHS(MIN(month_limit),i) <= (
SELECT MAX(month_limit) FROM month_limits
)
)
-- finally, CROSS JOIN the obtained month list with itself with the
-- filters needed.
SELECT
cohort.month_first AS cohort_month
, use.month_first AS use_month
FROM month_list AS cohort
CROSS JOIN month_list AS use
WHERE use.month_first >= cohort.month_first
ORDER BY 1,2
;
i have a table which looks like this :
coumn 1 = timestamp : string , column 2 = numOfentites : int
please note i am using hiveql
Fri, 10 Aug 2001 274
Fri, 10 Dec 1999 39
Fri, 10 Mar 2000 107
Fri, 10 May 2002 26
Fri, 10 Nov 2000 351
Fri, 10 Sep 1999 22
Fri, 11 Aug 2000 189
Fri, 11 Dec 1998 1
Fri, 11 Feb 2000 84
Fri, 11 Jan 2002 580
Fri, 11 Jun 1999 12
Fri, 11 May 2001 571
Fri, 12 Apr 2002 41
Now, I retrieved the frequency per year from this table and found out some year XXXX had the most number of entities.
My aim now is to go one level deep and extract the frequency per month for the year XXXX.
I tired using the group by clause on the substring indicating month but it doesn’t work.
can you guys please give me a direction on how to proceed..
Just need a hint not the answer :P trying to learn hiveql here
EDIT
here is the query that i used to extract the frequency of entities on yearly basis.
note that timestamp is the first column of the input.
select dates , count(dates) as numEmails
from (select split(timestamp," ")[3] as dates , count(timestamp)
from dataset
group by timestamp
) mailfreq
group by dates
order by numEmails desc;
I know that hivesql has strange limitations, but won't this work?
select split(timestamp," ")[3] as yr, split(timestamp," ")[2] as mon, count(timestamp)
from dataset
group by split(timestamp," ")[3], split(timestamp," ")[2];