Looker LookML Developer Practice Test

The parameter that is used with measure types that perform aggregations on non-repeated values is indeed referred to as the "sql_distinct_key." This parameter is essential for defining how the measure will aggregate values when there are duplicate entries in the dataset.

When a measure is defined with this parameter, it enables Looker to compute distinct values instead of summing all values indiscriminately. This ensures that the aggregation reflects the unique count of entries rather than the total count, which would include repeats. This is particularly useful in scenarios where you want to analyze unique contributions, such as counting unique users or distinct transactions.

The other options presented do not fulfill this specific function. For instance, the sql_group_key is generally used for grouping fields in queries, while the sql_average_key and sql_total_key are associated with specific types of aggregations rather than handling distinct values. Thus, the sql_distinct_key specifically targets the need for aggregation on non-repeated values, making it the correct choice in this context.