A developer needs to model out LookML to convert existing reports into Looker. The existing reports are:
Report 1: A report with order and order_items data, which finds the order with the largest total value of the order_item prices.
Report 2: A report with order and order_items data, which finds the order with the largest total number of products ordered.
Report 3: A report with data on every product, whether or not it has been ordered.
Each database table used is updated in real time as orders are made.
How should the developer construct an Explore using the order_items view as the base view?

• A.Create one persistent derived table to calculate Report 1, create one persistent derived table to calculate Report 2, and join in the products view with a full_outer join.
• B.Create one persistent derived table to calculate Reports 1 and 2, and join in the products view with a full_outer join.
• C.Create one ephemeral derived table to calculate Reports 1 and 2, and join in the products view with a full_outer join.
• D.Create one ephemeral derived table to calculate Report 1, create one ephemeral derived table to calculate Report 2, and join in the products view with a left_outer join.

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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 three separate datagroups tied to three PDTs that run when a new row is added to the ETL log table.
• B.Create one datagroup tied to all three PDTs that runs when the total row count across all three tables changes.
• C.Create one datagroup tied to all three PDTs that parameterizes the view name for each PDT in the SQL trigger condition.
• D.Create three separate datagroups tied to three PDTs that run when each corresponding table's row count changes.

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A developer creates a derived table and wants to add persistence to it. Because the table is not used on a frequent basis, the developer wants the table to be cached for 12 hours, but only when a user has queried it.
Which persistence parameter should be added to the derived table's definition in order to satisfy this use case?

• A.persist_for: "12 hours"
• B.datagroup: 12_hours {
  max_cache_age: "12 hours"
  }
• C.sql_trigger_value: SELECT FLOOR{UNIX_TIMESTAMP{} / {6*60*60}} ;;
• D.persist_with: "12 hours"

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