Data Science Toolkit - Log-level custom model feed
The Log-Level Custom Model Feed gives you specific information on models associated with your line items and the values calculated by each model.
Sequence
The columns below are listed in the same order in which they appear in the log-level feed file (top to bottom here, left to right in the file).
Integer key
- tinyint = 1 byte (8 bit)
- smallint = 2 byte (16 bit)
- int = 4 byte (32 bit)
- bigint = 8 byte (64 bit)
Columns
Column Index | Column Name | Type | Description |
---|---|---|---|
01 | date_time |
UNIX Epoch time | The time and date of the impression (e.g., 1526057561 which would need to be translated to Friday, May 11, 2018 4:52:41 PM (UTC)). |
02 | auction_id_64 |
bigint | The AppNexus unique auction identifier. |
03 | buyer_member_id |
int | The member ID of the buyer. |
04 | user_id_64 |
bigint | The AppNexus 64-bit User ID stored in the AppNexus cookie store. This field is 0 when AppNexus does not have a match for this user or the user's browser doesn't accept cookies. It will be -1 for opt-out users.Note: This field has been deprecated from the API Log Level Data service (in compliance with GDPR). |
05 | model_type |
int | Type of the model. Possible values are:1 = expected_value2 = creative_selection3 = ev_click4 = click_imp5 = ev_conv6 = conv_imp7 = conv_click8 = bid_modifier9 = nonvaluation10 = cadence11 = budget_splitter |
06 | model_id |
int | The ID of the custom model used in the auction. When no custom model is used, this defaults to 0 . |
07 | leaf_code |
string | An optional string value that will be passed through to logs and reporting to aid with debugging and performance analysis. leaf_code may be up to seven ASCII (7-bit) characters and is not required to be unique, this defaults to "" . |
08 | origin |
int | Origin indicates whether the model is attached by AppNexus. Possible values are:0 = Model attached by client1 = Model attached by AppNexus Optimization2 = Model attached by Programmable Splits |
09 | experiment |
int | Indicates whether the impression is a test or control impression. This is currently unsupported and will be 0 for all impressions. |
10 | value |
numeric(18,6) | Value calculated by the model |
11 | campaign_group_id |
int | The ID of the Line Item |
12 | hashed_user_id_64 |
bytes | The hashed version of the AppNexus 64-bit User ID which will we provided as a proxy in certain cases where AppNexus is unable to provide the real user_id_64 . You will not be able to target users via their hashed user ID. However you can use this identifier to calculate unique users, user frequency, and user recency. See example for hashed_user_id_64 below. |
Example for hashed_user_id_64
user_id_64:
XXXXXX304391387YYYY
hashed_user_id_64:
0000f47b074866470613d9397f0bd7efa78c7adec992aac5e117cbe2d55993a94767