You implement an enterprise data warehouse in Azure Synapse Analytics.
You have a large fact table that is 10 terabytes (TB) in size.
Incoming queries use the primary key SaleKey column to retrieve data as displayed in the following table:
 
You need to distribute the large fact table across multiple nodes to optimize performance of the table.
Which technology should you use?

A. hash distributed table with clustered index

B. hash distributed table with clustered Columnstore index

C. round robin distributed table with clustered index

D. round robin distributed table with clustered Columnstore index

E. heap table with distribution replicate






 

Suggested Answer: B

Hash-distributed tables improve query performance on large fact tables.
Columnstore indexes can achieve up to 100x better performance on analytics and data warehousing workloads and up to 10x better data compression than traditional rowstore indexes.
Incorrect Answers:
C, D: Round-robin tables are useful for improving loading speed.
Reference:
https://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-tables-distribute
 https://docs.microsoft.com/en-us/sql/relational-databases/indexes/columnstore-indexes-query-performance

This question is in DP-203 Data Engineering on Microsoft Azure Exam
For getting Microsoft Certified: Azure Data Engineer Associate Certificate


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