You have a fact table named PowerUsage that has 10 billion rows. PowerUsage contains data about customer power usage dur

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You have a fact table named PowerUsage that has 10 billion rows. PowerUsage contains data about customer power usage during the last 12 months. The usage data is collected every minute. PowerUsage contains the columns configured as shown in the following table.LocationNumber has a default value of 1. The MinuteOfMonth column contains the relative minute within each month. The value resets at the beginning of each month.A sample of the fact table data is shown in the following table.There is a related table named Customer that joins to the PowerUsage table on the CustomerId column. Sixty percent of the rows in PowerUsage are associated to less than 10 percent of the rows in Customer. Most queries do not require the use of the Customer table. Many queries select on a specific month.You need to minimize how long it takes to find the records for a specific month.What should you do?

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A. Implement partitioning by using the MonthKey column. Implement hash distribution by using the CustomerId column.
B. Implement partitioning by using the CustomerId column. Implement hash distribution by using the MonthKey column.
C. Implement partitioning by using the MinuteOfMonth column. Implement hash distribution by using the MeasurementId column.
D. Implement partitioning by using the MonthKey column. Implement hash distribution by using the MeasurementId column.