You have a Microsoft Azure SQL data warehouse that has a fact table named FactOrder. FactOrder contains
three columns named CustomerId, OrderId, and OrderDateKey. FactOrder is hash distributed on CustomerId.
OrderId 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 OrderId.
D.
Change the distribution for the dimCustomers table to OrderDateKey.
Explanation:
https://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-tables-statistics