Built-in Jinja context variables in dbt - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to access the current model's name using a built-in Jinja variable.

dbt

SELECT * FROM {{ [1].this }}

Drag options to blanks, or click blank then click option'

Amodel

Bref

Cthis

Dconfig

Attempts:

3 left

💡 Hint

Common Mistakes

Using model instead of this.

Trying to use ref which is for referencing other models.

The this variable in dbt's Jinja context refers to the current model's full identifier, which can be used to reference the model itself.

2fill in blank

medium

Complete the code to get the current model's schema using a built-in Jinja variable.

dbt

SELECT schema_name FROM information_schema.schemata WHERE schema_name = '{{ [1].schema }}'

Drag options to blanks, or click blank then click option'

Aadapter

Btarget

Cconfig

Dthis

Attempts:

3 left

💡 Hint

Common Mistakes

Using target.schema which refers to the target schema for the run, not the model's schema.

Using config.schema which is for configuration settings.

The this.schema variable gives the schema name of the current model in dbt.

3fill in blank

hard

Fix the error in the code to correctly access the current model's alias using a built-in Jinja variable.

dbt

SELECT '{{ [1].alias }}' AS model_alias

Drag options to blanks, or click blank then click option'

Athis

Btarget

Cconfig

Dref

Attempts:

3 left

💡 Hint

Common Mistakes

Using target.alias which does not exist.

Using config.alias which is for configuration.

The this.alias variable holds the alias of the current model in dbt.

4fill in blank

hard

Fill both blanks to create a dictionary comprehension that maps each column name to its data type from the current model's columns.

dbt

{ [1]: [2] for col in this.columns }

Drag options to blanks, or click blank then click option'

Acol.name

Bcol.data_type

Ccol.type

Dcol.column_name

Attempts:

3 left

💡 Hint

Common Mistakes

Using col.type which is not a valid attribute.

Using col.column_name which is not the correct attribute.

Each column object has a name and data_type attribute. The comprehension maps column names to their data types.

5fill in blank

hard

Fill all three blanks to create a filter that selects columns with data type 'string' and length greater than 10 from the current model's columns.

dbt

{col.name: col.data_type for col in this.columns if col.data_type == '[1]' and col.character_maximum_length [2] [3]

Drag options to blanks, or click blank then click option'

Ainteger

B>

C10

Dstring

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'integer' instead of 'string' for data type.

Using '<' instead of '>' for length comparison.

This comprehension filters columns where the data type is 'string' and the maximum character length is greater than 10.