Model dependencies and parallelism in dbt - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to define a model that depends on another model using the ref function.

dbt

select * from [1]('customers')

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

Aref

Bsource

Ctable

Dmodel

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'source' instead of 'ref' to link models.

Trying to use 'table' or 'model' which are not dbt functions.

The ref function is used in dbt to refer to another model, establishing a dependency.

2fill in blank

medium

Complete the command to run dbt models with 4 threads for parallel execution.

dbt

dbt run --[1] 4

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

Aparallel

Bjobs

Cthreads

Dworkers

Attempts:

3 left

💡 Hint

Common Mistakes

Using '--jobs' or '--workers' which are not valid dbt flags.

Confusing parallelism flag with other options.

The --threads option tells dbt how many models to run in parallel.

3fill in blank

hard

Fix the error in the model dependency by completing the missing function.

dbt

select * from [1]('orders')

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

Asource

Bload

Cfetch

Dref

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'source' which refers to external tables, not models.

Using 'load' or 'fetch' which are not dbt functions.

The ref function correctly creates a dependency on the 'orders' model.

4fill in blank

hard

Fill both blanks to create a dictionary comprehension that filters models with run time greater than 10 seconds.

dbt

filtered_models = {model: time[1]2 for model, time in run_times.items() if time [2] 10}

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

A**

B>

C>=

D*

Attempts:

3 left

💡 Hint

Common Mistakes

Using '**' instead of '*' for multiplication.

Using '>=' instead of '>' which changes the filter condition.

The dictionary comprehension multiplies time by a factor and filters times greater than 10.

5fill in blank

hard

Fill all three blanks to create a dictionary of model names in uppercase with their run times filtered by greater than 5 seconds.

dbt

result = [1]: [2] for [3], time in run_times.items() if time > 5

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

Amodel.upper()

Btime

Cmodel

Dtime.upper()

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'time.upper()' which is invalid since time is numeric.

Swapping model and time in the comprehension.

This comprehension creates keys as uppercase model names and values as their run times, filtering times greater than 5.