question-mark
Stuck on an issue?

Lightrun Answers was designed to reduce the constant googling that comes with debugging 3rd party libraries. It collects links to all the places you might be looking at while hunting down a tough bug.

And, if you’re still stuck at the end, we’re happy to hop on a call to see how we can help out.

Make TTL optional in FeatureViews

See original GitHub issue

Is your feature request related to a problem? Please describe.

Some of our data are features likes created_at of a shop. This data can be very old even though the shop is still active. Therefore we would rather want to not have a TTL rather than specifying a crazy value like 9999999

There are definitely performance implications that we are aware of 👌 If we take the above example, created_at of a given shop, the dataset grows only when there is a new shop created. Therefore the “lifetime” dataset size remains just all unique shops. So here the performance implications are pretty limited. So the need is there, we just need to use TLL properly for each FeatureView 👌

Describe the solution you’d like A clear and concise description of what you want to happen. Make TTL mandatory but add the possibility to pass None or 0 to explain that there is no TTL during historical retrieval

Describe alternatives you’ve considered A clear and concise description of any alternative solutions or features you’ve considered. Add a very large value like 99999999 as a TTL

Additional context Add any other context or screenshots about the feature request here.

Issue Analytics

  • State:closed
  • Created 2 years ago
  • Comments:8 (3 by maintainers)

github_iconTop GitHub Comments

1reaction
jparthasarthycommented, May 25, 2021

@woop I just really dislike the idea that someone could miss the TTL parameter and instead of throwing an error we would set it to infinity.

I think setting it to infinity should be something that has to be done explicitly by the user. Is there an API that makes sense with that in mind? Do you agree?

0reactions
stale[bot]commented, Sep 22, 2021

This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.

Read more comments on GitHub >

github_iconTop Results From Across the Web

Feature view - Feast
(optional) a TTL, which limits how far back Feast will look when generating historical datasets. Feature views allow Feast to model your existing...
Read more >
feast/feature_store.py at master - GitHub
FeatureView : """. Retrieves a feature view. Args: name: Name of feature view. allow_registry_cache: (Optional) Whether to allow returning this entity from a ......
Read more >
tecton.stream_feature_view
ttl ( str ) – The TTL (or “look back window”) for features defined by this feature view. This parameter determines how long...
Read more >
Creating a Feature Store with Feast | by Kedion - Medium
Create entity DataFrames and use them to save feature views to a ... the difference between end_date and ttl (defined in the feature...
Read more >
Snowflake Feast Integration - SelectFrom
ttl =timedelta(weeks=52), # The list of features as reference during ... At this stage, this is a logical definition of a FeatureView, not...
Read more >

github_iconTop Related Medium Post

No results found

github_iconTop Related StackOverflow Question

No results found

github_iconTroubleshoot Live Code

Lightrun enables developers to add logs, metrics and snapshots to live code - no restarts or redeploys required.
Start Free

github_iconTop Related Reddit Thread

No results found

github_iconTop Related Hackernoon Post

No results found

github_iconTop Related Tweet

No results found

github_iconTop Related Dev.to Post

No results found

github_iconTop Related Hashnode Post

No results found