is_incremental() macro in dbt - Cheat Sheet & Quick Revision

Recall & Review

beginner

What does the is_incremental() macro do in dbt?

The is_incremental() macro checks if the current dbt run is an incremental run, meaning it only processes new or changed data instead of rebuilding the entire table.

beginner

Why use is_incremental() in a dbt model?

You use is_incremental() to write logic that runs only during incremental runs, allowing you to add new data without rebuilding the whole dataset, saving time and resources.

intermediate

Example usage of is_incremental() in a dbt SQL model?

Inside your model SQL, you can write:<br>

select * from source_table<br>{% if is_incremental() %}<br>where updated_at > (select max(updated_at) from {{ this }})<br>{% endif %}

This means only new or updated rows are added during incremental runs.

beginner

What happens if you don't use is_incremental() in an incremental model?

If you don't use is_incremental(), your model will rebuild the entire table every time, losing the benefits of incremental loading and increasing run time.

intermediate

Can is_incremental() be used outside incremental models?

No, is_incremental() returns false in full-refresh or non-incremental runs, so its logic only applies when the model is set to incremental mode.

What does is_incremental() return during a full-refresh run?

A True

B Depends on the model

C An error

D False

is_incremental() returns false during full-refresh runs because the model rebuilds fully, not incrementally.

Why is is_incremental() useful in dbt models?

A To check if the model is running in incremental mode

B To speed up full-refresh runs

C To delete old data automatically

D To create new tables

is_incremental() helps you write code that runs only during incremental loads, improving efficiency.

Which of these is a common use of is_incremental() in SQL?

A Dropping tables before loading

B Filtering rows to only new or updated data

C Creating indexes

D Changing column types

You use is_incremental() to filter data so only new or changed rows are processed during incremental runs.

If you want your model to always rebuild fully, what should is_incremental() return?

A Null

B True

C False

D Depends on the data

During full rebuilds, is_incremental() returns false, meaning incremental logic is skipped.

What happens if you use incremental logic without checking is_incremental()?

A The model may miss data or error

B The model creates duplicate tables

C The model runs faster

D Nothing changes

Without checking is_incremental(), incremental logic might run during full-refresh causing errors or missing data.

Explain what the is_incremental() macro does and why it is important in dbt incremental models.

Think about how incremental models avoid rebuilding everything.

Describe a simple example of how you would use is_incremental() in a dbt model SQL file.

Consider filtering data to only new rows during incremental loads.