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@@ -62,3 +62,26 @@ Below is the resulting joined training dataframe. It contains both the original
Three feature rows were successfully joined to the entity dataframe rows. The first row in the entity dataframe was older than the earliest feature rows in the feature view and could not be joined. The last row in the entity dataframe was outside of the TTL window \(the event happened 11 hours after the feature row\) and also couldn't be joined.
## Retrieving features as of the event time
By default, point-in-time joins only constrain the feature's event timestamp. If a data source also has a `created_timestamp_column`, it is used to deduplicate rows that share an event timestamp \(the row with the highest created timestamp wins\), but it is not otherwise filtered. This means a value that was backfilled or corrected *after* an entity dataframe timestamp can still be returned for it.
To restrict retrieval to feature values that were already available at each entity row's timestamp, pass `filter_by_created_timestamp=True`:
```python
training_df = store.get_historical_features(
entity_df=entity_df,
features = [
'driver_hourly_stats:trips_today',
'driver_hourly_stats:earnings_today'
],
filter_by_created_timestamp=True,
)
```
This adds a `created_timestamp <= entity_timestamp` condition to the join, so each entity dataframe row only sees feature values whose created timestamp is at or before its own timestamp. This is useful to keep backfilled values from leaking into training data, and to reproduce what the online store would have served at each event time \(assuming the created timestamp reflects when the value became available online\).
{% hint style="info" %}
Rows with a NULL created timestamp are excluded when the flag is enabled, so the column should be non-null. Not all offline stores support this flag yet; unsupported stores raise an error rather than silently ignoring it.
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feat: Add opt-in filter_by_created_timestamp cutoff to get_historical_features #6617
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feat: Add opt-in filter_by_created_timestamp cutoff to get_historical_features #6617
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