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?
A. Create a query that selects all the fields from the table, and sort by primary key.
B. Create a query that selects the primary key from the base view, and look for duplicates.
C. Create a query that counts how many occurrences of the primary key value are in the base view, and sort by count.
D. Create a query that concatenates two columns to create a compound primary key.
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?
A. Define two datagroups for the model. Apply persist_with at the model level with the datagroup for 1hour caching, and apply persist_with to daily_forecast with the datagroup for 24-hour caching.
B. Define max_cache_age on daily_forecast Explores of 24 hours. Define max_cache_age on all other Explores for one hour.
C. 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.
D. 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.
A user needs to create a report that shows a count of all orders and of orders over $100. Which solution should the developer implement to meet these requirements?
A. An always_filter parameter
B. A front-end filter in the Explore
C. A sql_always_where parameter
D. A filtered measure
The code below shows a view order_items with its measures total_revenue and user_count
Which code correctly represents a new measure that calculates average revenue per user?
A. Option A
B. Option B
C. Option C
D. Option D
A developer has created a persistent derived table that tracks new or updated orders and they want to cache the results. The cache should be refreshed whenever some new order is available on the underlying datasource table my tablename or at least every 24 hours.
Which datagroup definition will refresh the cache as expected?
A. Option A
B. Option B
C. Option C
D. Option D
A developer would like to add a new dimension of type: yesno for the enabled column in their users table. The column is of type: string in the database and returns yes and no values.
How should the developer define the yesno dimension?
A. Option A
B. Option B
C. Option C
D. Option D
A developer wants to create a new Explore based on the order_items view. The developer creates an
Explore in the ecommerce model file with the following definition:
explore: order_items {}
After saving and validations, the developer receives this LookML validator error:
Inaccessible view “inventory_items”, “inventory_items” is not accessible in explore” “order_items”. Check
for typos and missing joins in explore “order_items”.
What caused this error to appear?
A. A field in the order_items view references a field in the inventory_items view.
B. A field in the inventory_items view references a field in the order_items view.
C. There is an Explore named inventory_items which references the order_items view.
D. There is another Explore named order_items which references the inventory_items view.
A developer commits changes after adding LookML for a new measure. Upon pulling from production, the developer notices the following lines in the LookML:
A. Remove “andlt;<<<<< HEAD”, “======”, and “andgt;>>>>> branch ‘master’”
B. Remove “andlt;<<<<< HEAD”, “======”, and everything following “======”
C. Remove everything between “andlt;<<<<< HEAD” and “======”, and “andgt;>>>>> branch ‘master’”
D. Remove everything between “andlt;<<<<< HEAD” and “andgt;>>>>> branch ‘master’”
Users report that every time they change the filter on their Explore, the filters take a very long time to populate.
How can the developer improve the filtering experience with this Explore?
A. Limit the filter suggestions using the suggestions parameter.
B. Add an always_filter parameter to restrict the filter suggestions.
C. Use an access_filter parameter to automatically apply filters.
D. Add persistence to the base view of the Explore.
A developer is defining the users table within a view file in Looker. The users table will be available as an individual Explore and it will also be joined into other Explores, such as the products Explore. The developer needs to limit the fields visible in the products Explore without affecting the visibility of the fields in the users Explore.
How should the developer meet this requirement?
A. Use the fields parameter at the join level for the products Explore to specify which fields should be included and leave the users Explore as is.
B. Create duplicate dimensions and measures, one for the users Explore and one for the products Explore, and use the hidden parameter to modify the visibility of the fields.
C. Create two view files for the users table. One view file will have all possible fields for the users Explore, and the other will have only the fields required for the products Explore.
D. Use the hidden parameter in the users view file for the fields that should not come over to the products Explore and leave the users Explore as is.
