LOOKML-DEVELOPER Online Practice Questions and Answers

A user reports that a query run against the orders Explore takes a long time to run. The query includes only fields from the users view. Data for both views is updated in real time. The developer runs the following query in SQL Runner and quickly receives results:

SELECT * FROM users.

What should the developer do to improve the performance of the query in the Explore?

A. Create an Explore with users as the base table.

B. Create a persistent derived table from the user's query.

C. Create an ephemeral derived table from the user's query.

D. Add persist_for: “24 hours” to the orders Explore.

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?

A. A measure of type: count has a sql parameter defined.

B. A measure of type: sum adds up other measures in the sql parameter.

C. A measure of type: sum has a SUM function written in the sql parameter.

D. A measure of type: number has a SUM function written in the sql parameter.

Only users with department attributes of Finance and Executive should be able to access the revenue view. Only users with the value of Executive for the department user attribute should be able to view the total_revenue field.

Given the code snippet below: How should the required access grants be structured to set up this system of access?

A. required_access_grants: [grant_b] in the revenue view, required_access_grants: [grant_a] in the total_revenue field

B. required_access_grants: [grant_a] in the revenue view, required_access_grants: [grant_a, grant_b] in the total_revenue field

C. required_access_grants: [grant_b] in the financial_data Explore, required_access_grants: [grant_a] in the total_revenue field

D. required_access_grants: [grant_a, grant_b] in the revenue view, required_access_grants: [grant_a] in the total_revenue field

Users report that the main dashboard has been slow to show results.

Which two options should the developer evaluate to improve dashboard performance? (Сhoose two.)

A. Number of databases used by dashboard elements

B. Number of queries used by the dashboard

C. Ratio of visualizations to text tiles D. Format used to deliver these reports

E. Amount of data rendered for each query

The developer has moved the orders Explore (shown below) from model_a to model_b, where both models are in the same project, and all users have access to both models.

Connection: “demo” include: “.view” explore: orders {}

What will happen after making this change?

A. Dashboard tiles and Looks will be automatically pointed to the orders Explore in model_b.

B. Dashboard tiles and Looks will redirect to the new database connection.

C. Dashboard tiles and Looks that rely on this Explore will be deleted.

D. Dashboard tiles and Looks that rely on this Explore will return an error.

A developer needs to implement three persistent derived tables (PDTs) as described below.

The PDTs need to be refreshed after the daily ETL pipeline adds incremental loads to the underlying

tables.

Each PDT is built off of one underlying table in the database (one PDT per table).

The underlying tables for each PDT are updated one after the other, and a new row is added to an ETL log

table each time a table is updated.

Due to the unpredictable nature of the ETL pipeline, each PDT does not refresh at the same time from day

to day.

Each PDT takes over an hour to build, and to save on compute costs each PDT should only be refreshed

once per day.

How can the developer set up the PDTs according to these requirements?

A. Create one datagroup tied to all three PDTs that runs when the total row count across all three tables changes.

B. Create one datagroup tied to all three PDTs that parameterizes the view name for each PDT in the SQL trigger condition.

C. Create three separate datagroups tied to three PDTs that run when each corresponding table's row count changes.

D. Create three separate datagroups tied to three PDTs that run when a new row is added to the ETL log table.

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 has the dimensions enrollment_month and graduation_month already defined in the view. Both were created as part of dimension_groups of type: time. The developer need to use these two dimensions in the sql_start and sql_end parameters of a dimension group of type: duration.

Which LookML should be used to calculate the number of month and years between enrollment month and graduation month?

A. Option A

B. Option B

C. Option C

D. Option D

A developer wants to calculate the ratio of total sales from the orders view and total users from the users view.

Which two methods can be used to create a measure that meets these requirements? (Choose two.)

A. Option A

B. Option B

C. Option C

D. Option D

E. Option E