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Merge pull request #93 from radibnia77/master
Performance-Forecasting Application Suite
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### Requirements | ||
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1. Java 8 | ||
2. Gradle 6.6.1 | ||
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### Run | ||
This project uses gradle as a build tool. | ||
'gradle tasks' shows different tasks that are handle by jar and war plugins. | ||
'gradle war' to compile and build the project. | ||
Default value for webAppDirName is src/main/webapp | ||
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### War | ||
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The default behavior of the War task is to copy the content of src/main/webapp to the root of the archive. | ||
Your webapp directory may of course contain a WEB-INF sub-directory, which may contain a web.xml file. | ||
Your compiled classes are compiled to WEB-INF/classes. | ||
All the dependencies of the runtime [1] configuration are copied to WEB-INF/lib. | ||
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# BM Version 1.1 | ||
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1. Update build.gradle to version 6.6.1 | ||
2. Add 'es.predictions.inventory.path' to db.properties which indicates the path of h0,h1,h2,h3 in predictions index | ||
3. Add new service to return daily inventory "/api/inventory/daily/count" . | ||
4. Make Day objects immutable | ||
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# BM Version 1.7 | ||
1. Add new API to return daily impressions. The document is in doc/api-daily-count.md | ||
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### Count Inventory | ||
##### Description | ||
> This end-point returns amount of daily inventory for a targeting channel considering time period and price. | ||
> The inventory calculation process considers all the bookings. | ||
> Targeting Channel is a set of attributes that specify a group of users (audience) plus the media. | ||
##### Method: POST | ||
##### URL: http://service-domain/imsservice/api/inventory/daily/count | ||
#####POST Body: | ||
```sh | ||
{ | ||
targeting_channel:<ucdocument>, | ||
ranges: [ { | ||
sd:<start-date date in yyyy-mm-dd>, | ||
ed:<end-date date in yyyy-mm-dd>, | ||
sh:<start-hour in hh>, | ||
eh:<end-hour in hh>} …] | ||
price: <CPC price> numeric format. | ||
} | ||
The following attributes are used in targeting channel: | ||
1) pm: Price Model – CPM/CPC/CPD/CPT | ||
2) ai: Ad slot - list | ||
3) ipl: Geo-location – list of city code | ||
4) r: Resident-location – list of city code | ||
5) g: Gender - list | ||
6) a: Age – list | ||
- 0 - (0,18) | ||
- 1 - [18,24] | ||
- 2 - (24,34] | ||
- 3 - (34,44] | ||
- 4 - (44,54] | ||
- 5 - (55,+) | ||
7) aus: App usage – list of {category?_appusage_state}, state is one of following | ||
a. active_30days | ||
b. activated | ||
c. installed_not_activated | ||
d. not_instatlled | ||
8) ais: App interest – list | ||
9) t: Connection type - list | ||
10) pdas: Pre-defined audiences – list | ||
11) exclude_pdas: Excluded pre-defined audiences - list | ||
12) dms: Device model – list | ||
13) dpc: Device price category range of [0,4] - list | ||
- (0-1500] – 0_1500 | ||
- (1500-2500] – 1500_2500 | ||
- (2500-3500] – 2500_3500 | ||
- (3500-4500] – 3500_4500 | ||
- (4500-+) – 4500 | ||
Excample: | ||
{ | ||
"targetingChannel": { | ||
"g":["g_f"] | ||
}, | ||
"price":0, | ||
"days": [{ | ||
"st": "2020-07-02", | ||
"ed": "2020-07-04", | ||
"sh": 0, | ||
"eh": 23 | ||
}] | ||
} | ||
``` | ||
##### Response: | ||
```sh | ||
{ | ||
"2020-07-03": { | ||
"h0": 0, | ||
"h1": 38739678, | ||
"h2": 419115, | ||
"h3": 505916 | ||
}, | ||
"2020-07-04": { | ||
"h0": 0, | ||
"h1": 10249965, | ||
"h2": 429323, | ||
"h3": 255991 | ||
}, | ||
"2020-07-02": { | ||
"h0": 0, | ||
"h1": 24837972, | ||
"h2": 298850, | ||
"h3": 287530 | ||
} | ||
} | ||
``` |
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