HOTSPOT -
You have an on-premises data warehouse that includes the following fact tables. Both tables have the following columns: DataKey, ProductKey, RegionKey.
There are 120 unique product keys and 65 unique region keys.
Queries that use the data warehouse take a long time to complete.
You plan to migrate the solution to use Azure Synapse Analytics. You need to ensure that the Azure-based solution optimizes query performance and minimizes processing skew.
What should you recommend? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Hot Area:
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Suggested Answer:
Box 1: Hash-distributed -
Box 2: ProductKey -
ProductKey is used extensively in joins.
Hash-distributed tables improve query performance on large fact tables.
Box 3: Round-robin -
Box 4: RegionKey -
Round-robin tables are useful for improving loading speed.
Consider using the round-robin distribution for your table in the following scenarios:
✑ When getting started as a simple starting point since it is the default
✑ If there is no obvious joining key
✑ If there is not good candidate column for hash distributing the table
✑ If the table does not share a common join key with other tables
✑ If the join is less significant than other joins in the query
✑ When the table is a temporary staging table
Note: A distributed table appears as a single table, but the rows are actually stored across 60 distributions. The rows are distributed with a hash or round-robin algorithm.
Reference:
https://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-tables-distribute
This question is in DP-201 Designing an Azure Data Solution Exam
For getting Microsoft Certified: Azure Data Engineer Associate Certificate
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