To calculate the amount on the basis of the date of

Hello

We must consider the functionality of oracle when it sees in 365 days a year. (for leap years 366 days)

calendar year of 365 days. calendar year of 12 months. Months will track the number of calendar days in the month. For example the Feb has 28 days and Oct. has 31 days.

Example:

For the period from 27/06/12 to 20/08/12

Annual amount of $3214.

Calculation

$3214 / 12 months = $267,83 per month

For June, $267,83 / 30 days in a month = $8.93 daily rate

6/27-6/30 is 4 days of service. x 4 = $35,72 $8.93

7/1-7/31 is considered to be a full month. = $267,83

For August, 8/1 /-8/20 is considered to be 20 days. Per day = 267.83 / 31 = 8.64

20 days = $172.79

TOTAL = $476,34

Please help me on how to do the following calculations.

Concerning

Suresh

Another solution, works better than the previous:

with the data as

(

Select to_date (June 27, 2013 ',' DD/MM/YYYY ') from_dt, to_date (August 20, 2013 ',' DD/MM/YYYY ') to_dt, amt double 3214

)

Select sum (DM)

de)

Select from_dt, to_dt, start_dt, last_dt,

(last_dt - start_dt + 1) *--> multiply applicable days of the month at the daily amount, calculated below

Sum)

round)

(amt/12) /--> calculate a monthly amount

TO_CHAR)

LAST_DAY (curr_dt)

, 'DD '.

)--> Find last day of the month and divide the monthly amount with the last day and calculate the daily amount

2

)--> Around the daily amount to 2 decimal places

) on sm--> sum the amount daily (partition to_char (curr_dt, 'MM'))

de)

Select from_dt, to_dt, TN,

less (add_months (from_dt, level - 1), to_dt) curr_dt,.

decode (level 1, less (add_months (from_dt, level - 1), to_dt), trunc (less (add_months (from_dt, level - 1), to_dt), 'MM')) start_dt;

less (last_day (add_months (from_Dt, level - 1)), to_dt) last_dt

from the data

connect by level<= months_between(trunc(to_dt,="" 'mm'),="" trunc(from_dt,="" 'mm'))="" +="">

)

);

SUM (DM)

----------------------

476.36

This avoids looping of data for all of the Dates if opposed to a loop for each month, which increases its performance. See plans to explain to the two queries:

explain plan for

with the data as

(

Select to_date (June 27, 2013 ',' DD/MM/YYYY ') from_dt, to_date (August 20, 2013 ',' DD/MM/YYYY ') to_dt, amt double 3214

),

div_data as

(

Select from_dt, to_dt, annual_amount from the amt Tower (amt/12, 2) monthly_amount

from the data

)

Select sum (per_day_amt)

de)

Select to_char (level - 1, 'Lun' + from_dt) curr_dt,.

sum (round (monthly_amount/to_number (substr (to_char (last_day (level - 1 + from_dt), 'DDMMYYYY'), 1, 2)), 2)) per_day_amt

of div_data

connect by level<= (to_dt="" -="" from_dt)="" +="">

To_char Group (level - 1, 'Lun' + from_dt)

);

Hash value of plan: 1042012692

----------------------------------------------------------------------------------------------------------------

| ID | Operation | Name | Lines | Bytes | Cost (% CPU). Time |

----------------------------------------------------------------------------------------------------------------

| 0 | SELECT STATEMENT | | 1. 13. 5 (20) | 00:00:01 |

| 1. TRANSFORMATION OF THE TEMPORARY TABLE. | | | | |

| 3. QUICK DOUBLE | | 1. | 2 (0) | 00:00:01 |

| 4. GLOBAL TRI | | 1. 13. | |

| 5. VIEW | | 1. 13. 3 (34) | 00:00:01 |

| 6. HASH GROUP BY. | 1. 16. 3 (34) | 00:00:01 |

|* 7 | CONNECT TO WITHOUT FILTERING. | | | | |

| 9. VIEW | | 1. 16. 2 (0) | 00:00:01 |

| 10. TABLE ACCESS FULL | SYS_TEMP_0FD9D86CF_5F8521E2 | 1. 44. 2 (0) | 00:00:01 |

----------------------------------------------------------------------------------------------------------------

Information of predicates (identified by the operation identity card):

---------------------------------------------------

7 filter (LEVEL<>

explain plan for

with the data as

(

Select to_date (June 27, 2013 ',' DD/MM/YYYY ') from_dt, to_date (August 20, 2013 ',' DD/MM/YYYY ') to_dt, amt double 3214

)

Select sum (DM)

de)

Select from_dt, to_dt, start_dt, last_dt,

(last_dt-start_dt + 1) * sum (round ((amt/12)/to_char (last_day (curr_dt), 'JJ') 2)), in the sm (partition to_char (curr_dt, 'MM'))

de)

Select from_dt, to_dt, TN,

less (add_months (from_dt, level - 1), to_dt) curr_dt,.

decode (level 1, less (add_months (from_dt, level - 1), to_dt), trunc (less (add_months (from_dt, level - 1), to_dt), 'MM')) start_dt;

less (last_day (add_months (from_Dt, level - 1)), to_dt) last_dt

from the data

connect by level<= months_between(trunc(to_dt,="" 'mm'),="" trunc(from_dt,="" 'mm'))="" +="">

)

);

Hash value of plan: 1669308594

-----------------------------------------------------------------------------------------

-----------------------------------------------------------------------------------------

| 0 | SELECT STATEMENT | | 1. 13. 3 (34) | 00:00:01 |

| 1. GLOBAL TRI | | 1. 13. | |

| 2. VIEW | | 1. 13. 3 (34) | 00:00:01 |

| 3. KIND OF WINDOW. | 1. 30. 3 (34) | 00:00:01 |

| 4. VIEW | | 1. 30. 2 (0) | 00:00:01 |

|* 5 | CONNECT TO WITHOUT FILTERING. | | | | |

| 6. QUICK DOUBLE | | 1. | 2 (0) | 00:00:01 |

-----------------------------------------------------------------------------------------

Information of predicates (identified by the operation identity card):

---------------------------------------------------

5 filter (LEVEL<>

Post edited by: PurveshK
Updated with explanation.

Tags: Database

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