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問題 #1

A LookML developer has a transactions view with several measures that each perform complex calculations involving multiple fields. The LookML developer creates an Explore based on the transactions view. The product team wants to perform further functions on these measures, such as SUM, AVG, MIN, MAX, and RANK. The team wants these further functions to be performed at different levels of detail: weekly, monthly, and yearly.
How can the LookML developer model these requirements and minimize the amount of code rewriting?

A. Add measures to the transactions view of type: number to apply the required functions.
B. Create a constant for each measure so it can be reused across other areas of the LookML project.
C. Change the existing measures in the transactions view to dimensions, and add measures of the different required types.
D. Create native derived tables using transactions as the explore_source.

問題 #2

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 that rely on this Explore will return an error.
B. Dashboard tiles and Looks will redirect to the new database connection.
C. Dashboard tiles and Looks will be automatically pointed to the orders Explore in model_b.
D. Dashboard tiles and Looks that rely on this Explore will be deleted.

問題 #3

The developer is creating an Explore that includes the product users, and orders views that will meet the following guidelines.
Joins between the orders and users views should not incur high performance costs.
Users of this Explore will primarily be looking at data from the orders view.
Users of this Explore should only be able to see orders from the retailer "Fashion.ly".
The only field the users need from the products view is product.name.
Which LookML should the developer use?
A)

B)

C)

D)

A. Option D
B. Option B
C. Option C
D. Option A

問題 #4

A developer has User Specific Time Zones enabled for a Looker instance, but wants to ensure that queries run in Looker are as performant as they can be. The developer wants to add a datatype: date parameter to all dimension_group definitions without time data in a table-based view, so that time conversions don't occur for these fields.
How can the developer determine to which fields this parameter should be applied through SQL Runner?

A. Use the CAST function in SQL Runner to ensure that all underlying fields are dates and conversions are not applied.
B. Use the Describe feature in SQL Runner to determine which fields include time data.
C. Open the Explore query in SQL Runner to determine which fields are converted.
D. Open the Explore query in SQL Runner and validate whether removing the conversion from date fields changes the results.

問題 #5

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.

問題與答案：