Recursive formulaes in org-mode tables - emacs

I have the following table:
| Year (Beginn) | Price | Increase |
|---------------+----------+----------|
| 2016 | 20000.00 | 1000.00 |
| 2017 | | 1000.00 |
| 2018 | | 1000.00 |
| 2019 | | 1000.00 |
| 2020 | | 1000.00 |
| 2021 | | 1000.00 |
| 2022 | | 1000.00 |
| 2023 | | 1000.00 |
| 2024 | | 1000.00 |
| 2025 | | 1000.00 |
| 2026 | | 1000.00 |
| 2027 | | 1000.00 |
| 2028 | | 1000.00 |
| 2029 | | 1000.00 |
| 2030 | | 1000.00 |
|---------------+----------+----------|
I want to compute the price recursively such that the final table looks like this:
| Year (Beginn) | Price | Increase |
|---------------+----------+----------|
| 2016 | 20000.00 | 1000.00 |
| 2017 | 22000.00 | 1000.00 |
| 2018 | 24000.00 | 1000.00 |
| 2019 | 26000.00 | 1000.00 |
| 2020 | 28000.00 | 1000.00 |
| 2021 | 30000.00 | 1000.00 |
| 2022 | 32000.00 | 1000.00 |
| 2023 | 34000.00 | 1000.00 |
| 2024 | 36000.00 | 1000.00 |
| 2025 | 38000.00 | 1000.00 |
| 2026 | 40000.00 | 1000.00 |
| 2027 | 42000.00 | 1000.00 |
| 2028 | 44000.00 | 1000.00 |
| 2029 | 46000.00 | 1000.00 |
| 2030 | 48000.00 | 1000.00 |
|---------------+----------+----------|
After reading a related SO question I tried the formula
#+TBLFM: #<<<..>$2=#<<..>>$2+2*$3
but it doesn't work. It gives an error and also seems to operate on column one instead of the specified column two. Any idea how to correctly compute column two? I am using org-mode version 8.2.5c with Emacs version 24.5.1.


I recommend using the following range formula:
| Year (Beginn) | Price | Increase |
|---------------+----------+----------|
| 2016 | 20000.00 | 1000.00 |
| 2017 | | 1000.00 |
| 2018 | | 1000.00 |
| 2019 | | 1000.00 |
| 2020 | | 1000.00 |
| 2021 | | 1000.00 |
| 2022 | | 1000.00 |
| 2023 | | 1000.00 |
| 2024 | | 1000.00 |
| 2025 | | 1000.00 |
| 2026 | | 1000.00 |
| 2027 | | 1000.00 |
| 2028 | | 1000.00 |
| 2029 | | 1000.00 |
| 2030 | | 1000.00 |
|---------------+----------+----------|
#+TBLFM: #<<<$2..#>$2=#<<$0+2*vsum(#<<$3..#-1$3);%.2f
You could write a recursive formula, but that would propogate one row at a time. Even org-table-iterate (C-u C-u C-c * on any table cell) would have to be called more than once, since it stops after 10 iterations.

Related

Get data based on latest date

Based on the dataset below, I'm trying to get the lastest cost based on the latest report date.
For example: When the report date=forecast date (column headers) then pick the values as on that report date which can be achived by this formula
IF [Report Date]=[Forecast Date] THEN [Forecasted Cost] END
but I also want to get the subsequent values as of the lastest report date i.e. 2/15/2019. How do I achieve this?
DESIRED OUTPUT
+------------+-----------+-----------+------------+------------+------------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+
| | 8/15/2018 | 9/15/2018 | 10/15/2018 | 11/15/2018 | 12/15/2018 | 1/15/2019 | 2/15/2019 | 3/15/2019 | 4/15/2019 | 5/15/2019 | 6/15/2019 | 7/15/2019 | 8/15/2019 |
+------------+-----------+-----------+------------+------------+------------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+
| Final Cost | 646.00 | 646.00 | 620.00 | 620.00 | 550.00 | 445.00 | 361.00 | 332.50 | 315.40 | 296.40 | 290.70 | 285.00 | 279.30 |
+------------+-----------+-----------+------------+------------+------------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+
DATASET
+------+-------------+-----------+-----------+------------+------------+------------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+
| Item | Report Date | 8/15/2018 | 9/15/2018 | 10/15/2018 | 11/15/2018 | 12/15/2018 | 1/15/2019 | 2/15/2019 | 3/15/2019 | 4/15/2019 | 5/15/2019 | 6/15/2019 | 7/15/2019 | 8/15/2019 |
+------+-------------+-----------+-----------+------------+------------+------------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+
| 4124 | 8/15/2018 | 646.00 | 646.00 | 658.00 | 658.00 | 658.00 | 658.00 | 658.00 | | | | | | |
| 4124 | 9/15/2018 | | 646 | 626 | 626 | 626 | 622 | 622 | 622 | | | | | |
| 4124 | 10/15/2018 | | | 620 | 620 | 620 | 585 | 585 | 585 | 555 | | | | |
| 4124 | 11/15/2018 | | | | 620 | 620 | 610 | 595 | 554.5 | 543.38 | 535.35 | | | |
| 4124 | 12/15/2018 | | | | | 550 | 535 | 505 | 490 | 490 | 490 | 490 | | |
| 4124 | 1/15/2019 | | | | | | 445 | 430 | 420 | 410 | 400 | 390 | 384 | |
| 4124 | 2/15/2019 | | | | | | | 361 | 332.5 | 315.4 | 296.4 | 290.7 | 285 | 279.3 |
+------+-------------+-----------+-----------+------------+------------+------------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+-----------+

First of all, you need to transpose your dataset, i.e. to have 4 columns "Item", "Report Date", "Forecast Date" and "Forecast Cost". Then you create a filter "forecast date >= report date" and show values by forecast date.
Now you will have multiple values for each forecast date. if you only want to get the latest value, then you can use table calculation window_min(date diff).

Check previous and next record

I'm trying to compare different costs from different periods. But I dont no how I can compare the single record with the record before and after. What I need is a yes or no in my dataset when the costs from a records is the same as record before and record after.
My dataset looks like this:
+--------+-----------+----------+------------+-------+-----------+
| Client | Provision | CAK Year | CAK Period | Costs | Serial Nr |
+--------+-----------+----------+------------+-------+-----------+
| 1 | 210 | 2017 | 13 | 150 | 1 |
+--------+-----------+----------+------------+-------+-----------+
| 1 | 210 | 2018 | 1 | 200 | 2 |
+--------+-----------+----------+------------+-------+-----------+
| 1 | 210 | 2018 | 2 | 170 | 3 |
+--------+-----------+----------+------------+-------+-----------+
| 1 | 210 | 2018 | 3 | 150 | 4 |
+--------+-----------+----------+------------+-------+-----------+
| 1 | 210 | 2018 | 4 | 150 | 5 |
+--------+-----------+----------+------------+-------+-----------+
| 1 | 210 | 2018 | 5 | 150 | 6 |
+--------+-----------+----------+------------+-------+-----------+
| 1 | 689 | 2018 | 1 | 345 | 1 |
+--------+-----------+----------+------------+-------+-----------+
| 1 | 689 | 2018 | 2 | 345 | 1 |
+--------+-----------+----------+------------+-------+-----------+
| 1 | 689 | 2018 | 3 | 345 | 1 |
+--------+-----------+----------+------------+-------+-----------+
What i've tried so far:
CASE
WHEN Provision = Provision
AND Costs = LEAD(Costs, 1, 0) OVER(ORDER BY CAK Year, CAK Period)
AND Costs = LAG(Costs, 1, 0) OVER(ORDER BY CAK Year, CAK Period)
THEN 'Yes
ELSE 'No'
END
My expected result:
+--------+-----------+----------+------------+-------+-----------+--------+
| Client | Provision | CAK Year | CAK Period | Costs | Serial Nr | Result |
+--------+-----------+----------+------------+-------+-----------+--------+
| 1 | 210 | 2017 | 13 | 150 | 1 | No
+--------+-----------+----------+------------+-------+-----------+--------+
| 1 | 210 | 2018 | 1 | 200 | 2 | No
+--------+-----------+----------+------------+-------+-----------+--------+
| 1 | 210 | 2018 | 2 | 170 | 3 | No
+--------+-----------+----------+------------+-------+-----------+--------+
| 1 | 210 | 2018 | 3 | 150 | 4 | No
+--------+-----------+----------+------------+-------+-----------+--------+
| 1 | 210 | 2018 | 4 | 150 | 5 | Yes
+--------+-----------+----------+------------+-------+-----------+--------+
| 1 | 210 | 2018 | 5 | 150 | 6 | No
+--------+-----------+----------+------------+-------+-----------+--------+
| 1 | 689 | 2018 | 1 | 345 | 1 | No
+--------+-----------+----------+------------+-------+-----------+--------+
| 1 | 689 | 2018 | 2 | 345 | 1 | Yes
+--------+-----------+----------+------------+-------+-----------+--------+
| 1 | 689 | 2018 | 3 | 345 | 1 | No
+--------+-----------+----------+------------+-------+-----------+--------+
You guys can help me further because I don't get the expected result?

You need to add in partition by Provision otherwise your lag and lead ordering will run across all Provision values:
declare #d table(Client int,Provision int,CAKYear int, CAKPeriod int, Costs int, SerialNr int);
insert into #d values
(1,210,2017,13,150,1)
,(1,210,2018,1,200,2)
,(1,210,2018,2,170,3)
,(1,210,2018,3,150,4)
,(1,210,2018,4,150,5)
,(1,210,2018,5,150,6)
,(1,689,2018,1,345,1)
,(1,689,2018,2,345,1)
,(1,689,2018,3,345,1);
select *
,case when Provision = Provision
and Costs = lead(Costs, 1, 0) over(partition by Provision order by CAKYear, CAKPeriod)
and Costs = lag(Costs, 1, 0) over(partition by Provision order by CAKYear, CAKPeriod)
then 'Yes'
else 'No'
end as Result
from #d
order by Provision
,CAKYear
,CAKPeriod;
Output
+--------+-----------+---------+-----------+-------+----------+--------+
| Client | Provision | CAKYear | CAKPeriod | Costs | SerialNr | Result |
+--------+-----------+---------+-----------+-------+----------+--------+
| 1 | 210 | 2017 | 13 | 150 | 1 | No |
| 1 | 210 | 2018 | 1 | 200 | 2 | No |
| 1 | 210 | 2018 | 2 | 170 | 3 | No |
| 1 | 210 | 2018 | 3 | 150 | 4 | No |
| 1 | 210 | 2018 | 4 | 150 | 5 | Yes |
| 1 | 210 | 2018 | 5 | 150 | 6 | No |
| 1 | 689 | 2018 | 1 | 345 | 1 | No |
| 1 | 689 | 2018 | 2 | 345 | 1 | Yes |
| 1 | 689 | 2018 | 3 | 345 | 1 | No |
+--------+-----------+---------+-----------+-------+----------+--------+

Calculate LAG variable after filtering in Tableau

I have a dataset with 4 columns: ID (unique identifier of user), Year, Country and Level in this format:
+----+------+---------+-------+
| ID | Year | Country | Level |
+----+------+---------+-------+
| 1 | 2015 | USA | 1 |
| 1 | 2016 | China | 2 |
| 2 | 2015 | China | 2 |
| 2 | 2016 | Russia | 2 |
| 3 | 2015 | Russia | 1 |
| 3 | 2016 | China | 2 |
| 4 | 2015 | USA | 2 |
| 4 | 2016 | USA | 3 |
| 5 | 2014 | China | 1 |
| 5 | 2016 | USA | 2 |
| 6 | 2015 | USA | 1 |
| 6 | 2016 | USA | 2 |
| 7 | 2015 | Russia | 2 |
| 7 | 2016 | China | 3 |
+----+------+---------+-------+
The user will be able to filter the dataset by country.
I want to create a table using the country filter that shows in a column if a user was the previous year in any of the countries selected aggregated by the level variable, apart from other variables only affected by the current country filter.
For example E.g., if I select China and USA:
+----+------+---------+-------+-----------------+
| ID | Year | Country | Level | In selection PY |
+----+------+---------+-------+-----------------+
| 1 | 2015 | USA | 1 | No |
| 1 | 2016 | China | 2 | Yes |
| 2 | 2015 | China | 2 | No |
| 3 | 2016 | China | 2 | No |
| 4 | 2015 | USA | 2 | No |
| 4 | 2016 | USA | 3 | Yes |
| 5 | 2014 | China | 1 | No |
| 5 | 2016 | USA | 2 | No |
| 6 | 2015 | USA | 1 | No |
| 6 | 2016 | USA | 2 | Yes |
| 7 | 2016 | China | 3 | No |
+----+------+---------+-------+-----------------+
The aggregated result will be:
+-------+-------------------+-----------------+
| Level | Number of records | In selection PY |
+-------+-------------------+-----------------+
| 1 | 3 | 0 |
| 2 | 6 | 2 |
| 3 | 2 | 1 |
+-------+-------------------+-----------------+
Do you know any way to calculate this aggregated table efficiently? (this would be done in a dataset with millions of rows, with a variable set of countries to be selected)

I found a solution, will post in case it is helpful for someone else:
I change the Country filter to "Add to Context" and created this variable:
In Selection PY: if Year = 2016 then
{fixed [ID]:min(if Year = 2015 then 1 END)}
elseif Year = 2015 then
{fixed [ID]:min(if Year = 2014 then 1 END)}
elseif Year = 2014 then
{fixed [ID]:min(if Year = 2013 then 1 END)}
In this way the variable Selection PY is dynamically calculated according to the country filter.
It is only necessary to know in advance which years are stored in the dataset (or add more years to be safe).

Window function to achieve running sum that resets in Postgres SQL [duplicate]

I wrote a query that creates two columns: the_day, and the amount_raised on that day. Here is what I have:
And I would like to add a column that has a running sum of amount_raised:
Ultimately, I would like the sum column to reset after it reaches 1 million.
The recursive approach is above my pay grade, so if anyone knows a way to reset the sum without creating an entirely new table, please comment (maybe with a RESET function?). Thank you

I'd like to thank Juan Carlos Oropeza for providing a script and SQLFiddle with the test data. George, you should have done that.
The query itself it rather simple.
At first calculate a simple running sum (CTE_RunningSum) and divide it by 1,000,000 to get number of whole millions.
Then calculate the running sum again with partitioning by the number of millions.
SQL Fiddle
I included the columns RunningSum and Millions in the final result to illustrate how the query works.
WITH
CTE_RunningSum
AS
(
SELECT
ID
,day_t
,collect
,SUM(collect) OVER(ORDER BY day_t, id) AS RunningSum
,(SUM(collect) OVER(ORDER BY day_t, id)) / 1000000 AS Millions
FROM myTable
)
SELECT
ID
,day_t
,collect
,RunningSum
,Millions
,SUM(collect) OVER(PARTITION BY Millions ORDER BY day_t, id) AS Result
FROM CTE_RunningSum
ORDER BY day_t, id;
Result
| id | day_t | collect | runningsum | millions | result |
|-----|-----------------------------|---------|------------|----------|---------|
| 90 | March, 11 2015 00:00:00 | 69880 | 69880 | 0 | 69880 |
| 13 | March, 25 2015 00:00:00 | 69484 | 139364 | 0 | 139364 |
| 49 | March, 27 2015 00:00:00 | 57412 | 196776 | 0 | 196776 |
| 41 | March, 30 2015 00:00:00 | 56404 | 253180 | 0 | 253180 |
| 99 | April, 03 2015 00:00:00 | 59426 | 312606 | 0 | 312606 |
| 1 | April, 10 2015 00:00:00 | 65825 | 378431 | 0 | 378431 |
| 100 | April, 27 2015 00:00:00 | 60884 | 439315 | 0 | 439315 |
| 50 | May, 11 2015 00:00:00 | 39641 | 478956 | 0 | 478956 |
| 58 | May, 11 2015 00:00:00 | 49759 | 528715 | 0 | 528715 |
| 51 | May, 17 2015 00:00:00 | 32895 | 561610 | 0 | 561610 |
| 15 | May, 19 2015 00:00:00 | 50847 | 612457 | 0 | 612457 |
| 66 | May, 29 2015 00:00:00 | 66332 | 678789 | 0 | 678789 |
| 4 | June, 04 2015 00:00:00 | 46891 | 725680 | 0 | 725680 |
| 38 | June, 09 2015 00:00:00 | 64732 | 790412 | 0 | 790412 |
| 79 | June, 14 2015 00:00:00 | 62843 | 853255 | 0 | 853255 |
| 37 | June, 28 2015 00:00:00 | 54315 | 907570 | 0 | 907570 |
| 59 | June, 30 2015 00:00:00 | 34885 | 942455 | 0 | 942455 |
| 71 | July, 08 2015 00:00:00 | 46440 | 988895 | 0 | 988895 |
| 31 | July, 10 2015 00:00:00 | 39649 | 1028544 | 1 | 39649 |
| 91 | July, 12 2015 00:00:00 | 65048 | 1093592 | 1 | 104697 |
| 57 | July, 14 2015 00:00:00 | 60394 | 1153986 | 1 | 165091 |
| 98 | July, 20 2015 00:00:00 | 34481 | 1188467 | 1 | 199572 |
| 3 | July, 26 2015 00:00:00 | 58672 | 1247139 | 1 | 258244 |
| 95 | August, 19 2015 00:00:00 | 52393 | 1299532 | 1 | 310637 |
| 74 | August, 20 2015 00:00:00 | 37972 | 1337504 | 1 | 348609 |
| 20 | August, 27 2015 00:00:00 | 36882 | 1374386 | 1 | 385491 |
| 2 | September, 07 2015 00:00:00 | 39408 | 1413794 | 1 | 424899 |
| 14 | September, 09 2015 00:00:00 | 40234 | 1454028 | 1 | 465133 |
| 6 | September, 17 2015 00:00:00 | 65957 | 1519985 | 1 | 531090 |
| 93 | September, 29 2015 00:00:00 | 47213 | 1567198 | 1 | 578303 |
| 35 | September, 30 2015 00:00:00 | 49446 | 1616644 | 1 | 627749 |
| 86 | October, 11 2015 00:00:00 | 34291 | 1650935 | 1 | 662040 |
| 75 | October, 12 2015 00:00:00 | 31448 | 1682383 | 1 | 693488 |
| 19 | October, 14 2015 00:00:00 | 48509 | 1730892 | 1 | 741997 |
| 56 | October, 26 2015 00:00:00 | 30072 | 1760964 | 1 | 772069 |
| 48 | October, 28 2015 00:00:00 | 58527 | 1819491 | 1 | 830596 |
| 40 | November, 05 2015 00:00:00 | 67293 | 1886784 | 1 | 897889 |
| 33 | November, 09 2015 00:00:00 | 41944 | 1928728 | 1 | 939833 |
| 34 | November, 11 2015 00:00:00 | 35516 | 1964244 | 1 | 975349 |
| 85 | November, 20 2015 00:00:00 | 43920 | 2008164 | 2 | 43920 |
| 18 | November, 23 2015 00:00:00 | 44925 | 2053089 | 2 | 88845 |
| 62 | December, 24 2015 00:00:00 | 34678 | 2087767 | 2 | 123523 |
| 67 | December, 25 2015 00:00:00 | 35323 | 2123090 | 2 | 158846 |
| 81 | December, 28 2015 00:00:00 | 37071 | 2160161 | 2 | 195917 |
| 54 | January, 02 2016 00:00:00 | 32330 | 2192491 | 2 | 228247 |
| 70 | January, 06 2016 00:00:00 | 47875 | 2240366 | 2 | 276122 |
| 28 | January, 23 2016 00:00:00 | 40250 | 2280616 | 2 | 316372 |
| 65 | January, 25 2016 00:00:00 | 49404 | 2330020 | 2 | 365776 |
| 73 | January, 26 2016 00:00:00 | 65879 | 2395899 | 2 | 431655 |
| 5 | February, 05 2016 00:00:00 | 53953 | 2449852 | 2 | 485608 |
| 32 | February, 11 2016 00:00:00 | 44988 | 2494840 | 2 | 530596 |
| 53 | February, 25 2016 00:00:00 | 68948 | 2563788 | 2 | 599544 |
| 83 | March, 11 2016 00:00:00 | 47244 | 2611032 | 2 | 646788 |
| 8 | March, 25 2016 00:00:00 | 51809 | 2662841 | 2 | 698597 |
| 82 | March, 25 2016 00:00:00 | 66506 | 2729347 | 2 | 765103 |
| 88 | April, 06 2016 00:00:00 | 69288 | 2798635 | 2 | 834391 |
| 89 | April, 14 2016 00:00:00 | 43162 | 2841797 | 2 | 877553 |
| 52 | April, 23 2016 00:00:00 | 47772 | 2889569 | 2 | 925325 |
| 7 | April, 27 2016 00:00:00 | 33368 | 2922937 | 2 | 958693 |
| 84 | April, 27 2016 00:00:00 | 57644 | 2980581 | 2 | 1016337 |
| 17 | May, 17 2016 00:00:00 | 35416 | 3015997 | 3 | 35416 |
| 61 | May, 17 2016 00:00:00 | 64603 | 3080600 | 3 | 100019 |
| 87 | June, 07 2016 00:00:00 | 41865 | 3122465 | 3 | 141884 |
| 97 | June, 08 2016 00:00:00 | 64982 | 3187447 | 3 | 206866 |
| 92 | June, 15 2016 00:00:00 | 58684 | 3246131 | 3 | 265550 |
| 23 | June, 26 2016 00:00:00 | 46147 | 3292278 | 3 | 311697 |
| 46 | June, 30 2016 00:00:00 | 61921 | 3354199 | 3 | 373618 |
| 94 | July, 03 2016 00:00:00 | 55535 | 3409734 | 3 | 429153 |
| 60 | July, 07 2016 00:00:00 | 63607 | 3473341 | 3 | 492760 |
| 45 | July, 20 2016 00:00:00 | 51965 | 3525306 | 3 | 544725 |
| 96 | July, 20 2016 00:00:00 | 46684 | 3571990 | 3 | 591409 |
| 29 | August, 09 2016 00:00:00 | 37707 | 3609697 | 3 | 629116 |
| 69 | August, 11 2016 00:00:00 | 37194 | 3646891 | 3 | 666310 |
| 80 | August, 19 2016 00:00:00 | 62673 | 3709564 | 3 | 728983 |
| 36 | August, 28 2016 00:00:00 | 48237 | 3757801 | 3 | 777220 |
| 39 | August, 29 2016 00:00:00 | 48159 | 3805960 | 3 | 825379 |
| 25 | August, 30 2016 00:00:00 | 60958 | 3866918 | 3 | 886337 |
| 68 | September, 04 2016 00:00:00 | 50167 | 3917085 | 3 | 936504 |
| 55 | September, 08 2016 00:00:00 | 31193 | 3948278 | 3 | 967697 |
| 64 | September, 10 2016 00:00:00 | 31157 | 3979435 | 3 | 998854 |
| 42 | September, 14 2016 00:00:00 | 52878 | 4032313 | 4 | 52878 |
| 43 | September, 15 2016 00:00:00 | 54728 | 4087041 | 4 | 107606 |
| 77 | September, 18 2016 00:00:00 | 65320 | 4152361 | 4 | 172926 |
| 12 | September, 23 2016 00:00:00 | 43597 | 4195958 | 4 | 216523 |
| 30 | September, 26 2016 00:00:00 | 32764 | 4228722 | 4 | 249287 |
| 10 | September, 27 2016 00:00:00 | 47038 | 4275760 | 4 | 296325 |
| 47 | October, 08 2016 00:00:00 | 46280 | 4322040 | 4 | 342605 |
| 26 | October, 10 2016 00:00:00 | 69487 | 4391527 | 4 | 412092 |
| 63 | October, 30 2016 00:00:00 | 49561 | 4441088 | 4 | 461653 |
| 78 | November, 15 2016 00:00:00 | 40138 | 4481226 | 4 | 501791 |
| 27 | November, 27 2016 00:00:00 | 57378 | 4538604 | 4 | 559169 |
| 21 | December, 01 2016 00:00:00 | 35336 | 4573940 | 4 | 594505 |
| 16 | December, 03 2016 00:00:00 | 39671 | 4613611 | 4 | 634176 |
| 22 | December, 13 2016 00:00:00 | 34574 | 4648185 | 4 | 668750 |
| 72 | January, 29 2017 00:00:00 | 55084 | 4703269 | 4 | 723834 |
| 44 | January, 30 2017 00:00:00 | 36742 | 4740011 | 4 | 760576 |
| 24 | February, 01 2017 00:00:00 | 31061 | 4771072 | 4 | 791637 |
| 76 | February, 12 2017 00:00:00 | 35059 | 4806131 | 4 | 826696 |
| 9 | February, 27 2017 00:00:00 | 39767 | 4845898 | 4 | 866463 |
| 11 | February, 28 2017 00:00:00 | 66007 | 4911905 | 4 | 932470 |

I took a look again and couldnt solve it with a Windows Function so I took the recursive aproach
SQL Fiddle Demo
Sample Data: 100 rows random dates between 2015-2017 amounts between 10k - 70k
DROP TABLE IF EXISTS "myTable";
CREATE TABLE "myTable" (
id SERIAL PRIMARY KEY,
day_t varchar(255),
collect integer NULL
);
INSERT INTO "myTable" (day_t,collect) VALUES ('2015-04-10',65825),('2015-09-07',39408),('2015-07-26',58672),('2015-06-04',46891),('2016-02-05',53953),('2015-09-17',65957),('2016-04-27',33368),('2016-03-25',51809),('2017-02-27',39767),('2016-09-27',47038);
INSERT INTO "myTable" (day_t,collect) VALUES ('2017-02-28',66007),('2016-09-23',43597),('2015-03-25',69484),('2015-09-09',40234),('2015-05-19',50847),('2016-12-03',39671),('2016-05-17',35416),('2015-11-23',44925),('2015-10-14',48509),('2015-08-27',36882);
INSERT INTO "myTable" (day_t,collect) VALUES ('2016-12-01',35336),('2016-12-13',34574),('2016-06-26',46147),('2017-02-01',31061),('2016-08-30',60958),('2016-10-10',69487),('2016-11-27',57378),('2016-01-23',40250),('2016-08-09',37707),('2016-09-26',32764);
INSERT INTO "myTable" (day_t,collect) VALUES ('2015-07-10',39649),('2016-02-11',44988),('2015-11-09',41944),('2015-11-11',35516),('2015-09-30',49446),('2016-08-28',48237),('2015-06-28',54315),('2015-06-09',64732),('2016-08-29',48159),('2015-11-05',67293);
INSERT INTO "myTable" (day_t,collect) VALUES ('2015-03-30',56404),('2016-09-14',52878),('2016-09-15',54728),('2017-01-30',36742),('2016-07-20',51965),('2016-06-30',61921),('2016-10-08',46280),('2015-10-28',58527),('2015-03-27',57412),('2015-05-11',39641);
INSERT INTO "myTable" (day_t,collect) VALUES ('2015-05-17',32895),('2016-04-23',47772),('2016-02-25',68948),('2016-01-02',32330),('2016-09-08',31193),('2015-10-26',30072),('2015-07-14',60394),('2015-05-11',49759),('2015-06-30',34885),('2016-07-07',63607);
INSERT INTO "myTable" (day_t,collect) VALUES ('2016-05-17',64603),('2015-12-24',34678),('2016-10-30',49561),('2016-09-10',31157),('2016-01-25',49404),('2015-05-29',66332),('2015-12-25',35323),('2016-09-04',50167),('2016-08-11',37194),('2016-01-06',47875);
INSERT INTO "myTable" (day_t,collect) VALUES ('2015-07-08',46440),('2017-01-29',55084),('2016-01-26',65879),('2015-08-20',37972),('2015-10-12',31448),('2017-02-12',35059),('2016-09-18',65320),('2016-11-15',40138),('2015-06-14',62843),('2016-08-19',62673);
INSERT INTO "myTable" (day_t,collect) VALUES ('2015-12-28',37071),('2016-03-25',66506),('2016-03-11',47244),('2016-04-27',57644),('2015-11-20',43920),('2015-10-11',34291),('2016-06-07',41865),('2016-04-06',69288),('2016-04-14',43162),('2015-03-11',69880);
INSERT INTO "myTable" (day_t,collect) VALUES ('2015-07-12',65048),('2016-06-15',58684),('2015-09-29',47213),('2016-07-03',55535),('2015-08-19',52393),('2016-07-20',46684),('2016-06-08',64982),('2015-07-20',34481),('2015-04-03',59426),('2015-04-27',60884);
Create a row_number to perform the recursion need consecutive ID's
CREATE TABLE sortDates as
SELECT day_t,
collect,
row_number() over (order by day_t) rn
FROM "myTable";
Recursive Query
If you see the CASE if previous total m.collect is bigger than 1 million the total is reset.
WITH RECURSIVE million(rn, day_t, collect) AS (
(
SELECT rn, day_t, collect
FROM sortDates
WHERE rn = 1
)
UNION
(
SELECT s.rn, s.day_t, CASE WHEN m.collect > 1000000 THEN s.collect
ELSE m.collect + s.collect
END as collect
FROM sortDates s
JOIN million m
ON s.rn = m.rn + 1
)
)
SELECT *
FROM million
WHERE collect > 1000000
Finally just bring the rows where you break the 1 million limit.
OUTPUT
| rn | day_t | collect |
|----|------------|---------|
| 19 | 2015-07-10 | 1028544 |
| 41 | 2015-11-23 | 1024545 |
| 62 | 2016-05-17 | 1027511 |
| 82 | 2016-09-15 | 1006441 |

Timetable grouped by tag

I'm looking for a way to use time tracking information from org-mode agenda files to build a timetable. Time spent in different tasks would be indicated, grouped by tag and restricted to a given time-frame, sort of like a clocktable dynamic block, but grouped by tag instead of file/category/headline.
For example, if my agenda contained the following data (possibly scattered among different files):
* TODO project 1
** TODO task 1 :tag1:
:LOGBOOK:
CLOCK: [2013-06-27 Thu 18:00]--[2013-06-27 Thu 19:04] => 1:04
CLOCK: [2013-06-26 Wed 17:00]--[2013-06-26 Wed 17:32] => 0:32
:END:
** TODO task 2 :tag2:
:LOGBOOK:
CLOCK: [2013-06-27 Thu 17:00]--[2013-06-27 Thu 18:00] => 1:00
CLOCK: [2013-06-27 Thu 15:00]--[2013-06-27 Thu 15:50] => 0:50
:END:
* TODO project 2 :tag2:
:LOGBOOK:
CLOCK: [2013-06-27 Thu 19:04]--[2013-06-27 Thu 21:00] => 1:56
CLOCK: [2013-06-27 Thu 15:50]--[2013-06-27 Thu 17:00] => 1:10
:END:
I would like to get this kind of results:
#+BEGIN: clocktable-by-tag :maxlevel 2 :tags ("p1" "p2") :tstart "2013-06-27" :tend "2013-06-28"
| Tag | Headline | Time | |
|------+-----------------+--------+------|
| tag1 | *Tag time* | *1:04* | |
| | TODO project 1 | 1:04 | |
| | \__ TODO task 1 | | 1:04 |
|------+-----------------+--------+------|
| tag2 | *Tag time* | *4:56* | |
| | TODO project 1 | 1:50 | |
| | \__ TODO task 2 | | 1:50 |
| | TODO project 2 | 3:06 | |
#+END:
Is there any standard way to do this with org? If not, I'm thinking of cycling through agenda files and tags, using org-get-table-data to collect clocking information; would there be another, more efficient way of doing things?

Here is what I've come to: https://gist.github.com/ffevotte/5899058
It's not very optimized, but seems to get the job done and should support most of the clocktable dynamic block arguments.
Sample (anonymized) output on my real org agenda files:
#+BEGIN: clocktable-by-tag :tags ("p_f3c" "p_sc") :tstart "2013-01-01" :tend "2013-05-19" :maxlevel 2
| Tag | Headline | Time (h) | | |
| | | <r> | | |
|-------+------------------------------+----------+-------+------|
| p_f3c | *Tag time* | *18.42* | | |
| | File *xxx.org* | 18.42 | | |
| | . xxxxxxxxxxxxxxxxxxx | | 13.03 | |
| | . \__ xxxxxxxxxxxxx | | | 7.78 |
| | . \__ xxxxxxxxxxxxxxxxxxxxx | | | 3.98 |
| | . xxxxxxxxxxxxxxxxxx | | 5.38 | |
| | . \__ xxxxxxxxxxxxxxx | | | 5.38 |
|-------+------------------------------+----------+-------+------|
| p_sc | *Tag time* | *18.90* | | |
| | File *yyyy.org* | 4.42 | | |
| | . xxxxxxxxxxxxxxxxxxxxxx | | 2.83 | |
| | . xxxxxxxxxxxxxxxxxx | | 1.58 | |
| | . \__ xxxxxxxxxxxxxxxxxxxxxx | | | 1.58 |
| | File *todo.org* | 14.48 | | |
| | . xxxxxxxxxxxxxxxx | | 14.48 | |
| | . \__ xxxxxxxxxxx | | | 2.00 |
| | . \__ xxxxxxxxxxxxx | | | 8.48 |
| | . \__ xxxxx | | | 4.00 |
#+END:

I have come up with an improvement of this solution that allows for a :summary t option and better formatting of the hours (using org-duration-from-minutes). You can find it in this gist. The result with summarising enabled looks like this:
#+BEGIN: clocktable-by-tag :tags ("work" "client1") :summary t
| Tag | Headline | Time (h) |
|---------+------------+----------|
| work | *Tag time* | 1:29 |
|---------+------------+----------|
| client1 | *Tag time* | 0:45 |
#+END:
Note: I came up with this solution while answering a similar question.