You have a Microsoft Azure SQL data warehouse that has a fact table named FactOrder. FactOrder contains three columns named Customerld,
Orderld, and OrderDateKey. FactOrder is hash distributed on Customerld. Orderld is the unique identifier for FactOrder. FactOrder contains 3 million rows.
Orders are distributed evenly among different customers from a table named dimCustomers that contains 2 million rows.
You often run queries that join FactOrder and dimCustomers by selecting and grouping by the OrderDateKey column.
You add 7 million rows to FactOrder. Most of the new records have a more recent OrderDateKey value than the previous records.
You need to reduce the execution time of queries that group on OrderDateKey and that join dimCustomers and FactOrder,
What should you do?
A. Change the distribution for the FactOrder table to round robin.
B. Update the statistics for the OrderDateKey column.
C. Change the distribution for the FactOrder table to be based on Orderld.
D. Change the distribution for the dimCustomers table to OrderDateKey,
