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Free LookML Developer Exam Braindumps (page: 3)

Page 2 of 13
PDF with 50 Questions

A LookML developer creates a new model and a test dashboard from the model. The developer shares the link to the new dashboard with users, but the users report that all they see is the “Model Not Found” error.

What is a possible cause of this issue?

  1. The developer has not pushed the new model to Production Mode.
  2. The developer has not added users to the new model set.
  3. The users do not have permission to access this dashboard.
  4. The new model is missing an Explore definition.

Answer(s): B



After running the LookML Validator, a developer sees the following error message in the Looker development environment:

“Measures with Looker aggregations (sum, average, min, max, list types) may not reference other measures”.

What could be causing this error?

  1. A measure of type: count has a sql parameter defined.
  2. A measure of type: sum adds up other measures in the sql parameter.
  3. A measure of type: sum has a SUM function written in the sql parameter.
  4. A measure of type: number has a SUM function written in the sql parameter.

Answer(s): A


Reference:

https://help.looker.com/hc/en-us/articles/360038371614--Error-Measures-with-Looker-Aggregations-Sum-Average-Min-Max-List-Types-May-Not-Reference-Other-Measures



A user is seeing an error in the Explore that indicates the primary key defined for a one-million-row table is not unique.

How can the developer use SQL Runner to troubleshoot quickly?

  1. Create a query that selects all the fields from the table, and sort by primary key.
  2. Create a query that selects the primary key from the base view, and look for duplicates.
  3. Create a query that counts how many occurrences of the primary key value are in the base view, and sort by count.
  4. Create a query that concatenates two columns to create a compound primary key.

Answer(s): D


Reference:

https://help.looker.com/hc/en-us/articles/360037732513-Error-Non-Unique-value-primary-key-or-sql-distinct-key-value-overflow-or-collision-when-computing-sum



The daily_forecast Explore used by the sales team needs to be cached for 24 hours. All other Explores used by the sales team need to be cached for one hour.

What is a scalable way to configure this caching logic?

  1. Define two datagroups for the model. Apply persist_with at the model level with the datagroup for 1-hour caching, and apply persist_with to daily_forecast with the datagroup for 24-hour caching.
  2. Define max_cache_age on daily_forecast Explores of 24 hours. Define max_cache_age on all other Explores for one hour.
  3. Define two datagroups for the model. Create a persistent derived table (PDT) for the daily_forecast Explore, and apply datagroup_trigger to it using the datagroup for 24-hour caching.
  4. Define for the model one datagroup that caches for 1 hour. Create a persistent derived table (PDT) for the daily_forecast Explore, and apply sql_trigger_value to it selecting the current date.

Answer(s): A


Reference:

https://docs.looker.com/reference/explore-params/persist_for-for-explore






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