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You run this command:
dbt build --select "source_status:fresher+" --state path/to/prod/artifacts Which two need to happen before it can be executed successfully?
Choose 2 options.
A. Define a freshness block on your source(s).
B. Test your sources with dbt test.
C. Add generic tests to your sources.
D. Invoke either dbt run or dbt build.
E. Invoke the command: dbt source freshness.
Answer: A,E
Explanation:
The selector source_status:fresher+ depends entirely on freshness metadata created by a previous dbt source freshness run. Source freshness results are stored in artifacts, and the --state flag points dbt to the location where these artifacts were previously generated. Without first running dbt source freshness, dbt has no stored freshness status and therefore cannot filter sources by "fresher" status. This makes option A required.
Additionally, source freshness checks only work when sources include a freshness block in their YAML configuration. This block specifies the loaded_at_field and the warn_after / error_after thresholds. If no freshness block exists, dbt does not compute freshness at all, meaning such sources cannot appear in the source_status:fresher+ selector. Therefore D is also required.
Options B and E are unrelated to source freshness artifacts and do not contribute to the preconditions for this selector. Option C does not impact freshness logic, as generic tests have no role in generating freshness metadata.
Thus, the two prerequisites are:
* Running dbt source freshness (to create freshness metadata).
* Defining a freshness configuration on the relevant sources.
NEW QUESTION # 98
You're refactoring a project with long model files containing intertwined logic. Which of the following is NOT a typical sign of a good candidate for applying modularity principles?
A. Portions of the logic form distinct conceptual steps in the transformation process.
B. Renaming code blocks would improve readability.
C. The models are relatively small and perform simple transformations.
D. The same SQL patterns are repeated with minor variations.
Answer: C
Explanation:
Small and simple models might already be sufficiently modular. The other options signal that refactoring into reusable components would be beneficial.
NEW QUESTION # 99
You're working in a highly collaborative environment. How could you manage contributions and updates to complex lineage macros to ensure maintainability and prevent conflicts?
A. All of the above-
B. Establish coding style guides and peer-review processes specifically for macros.
C. Limit the number of people authorized to make changes to sensitive lineage macros-
D. Utilize a robust version control system (e.g., Git) for macro code.
Answer: A
Explanation:
A Version control is essential for tracking changes and collaboratiom B: Style guides and reviews improve code quality and reduce errors. C: Controlled access can be important, while still allowing for collaboration through review processes.
NEW QUESTION # 100
(Multiple Select)
A. Implementing more rigorous access controls and auditing procedures.
B. Scheduling models to run outside normal business hours to reduce resource contention.
C. Potentially running on a different data warehouse or with different database settings.
D. Using credentials with appropriate permissions (likely read-only) to access production data sources.
Answer: A,C,D
Explanation:
A reflects the increased security needs of production environments. B allows scaling or optimization based on workload. C prevents accidental changes in production. D is a strategy, but not a fundamental difference.
NEW QUESTION # 101
Examine the configuration for the source:
sources:
- name: jaffle_shop
schema: jaffle_shop_raw_current
tables:
- name: orders
identifier: customer_orders
Which reference to the source is correct?
A. {{ source('jaffle_shop_raw_current', 'customer_orders') }}
B. {{ source('jaffle_shop', 'orders') }}
C. {{ source('jaffle_shop', 'customer_orders') }}
D. {{ source('jaffle_shop_raw_current', 'orders') }}
Answer: B
Explanation:
In dbt, the source() function resolves a source by its declared source name and table name, not by the physical schema or identifier in the warehouse. The YAML block defines a source named jaffle_shop, and under that source, a table named orders. The identifier: customer_orders field tells dbt that although the logical table name is orders, the actual physical object in the warehouse is named customer_orders.
dbt always expects the syntax:
{{ source(source_name, table_name) }}
Here, the correct reference uses jaffle_shop as the source name and orders as the table name because these are the logical names assigned in the YAML. dbt internally resolves the physical table name via the identifier field, so the model should not reference customer_orders directly.
Option A and B are incorrect because the first argument is not the schema; dbt does not use schemas in the source() call. Option D is incorrect because customer_orders is the warehouse identifier, not the logical table name recognized by dbt.
Therefore, the correct reference is:
{{ source('jaffle_shop', 'orders') }}
This ensures consistent modeling, dependency tracking, and accurate documentation.
NEW QUESTION # 102
......
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