
Explanation:
In Azure Synapse Analytics (formerly SQL Data Warehouse), resource classes are used to manage memory allocation and concurrency for different workloads. The scenario involves ensuring automated data loads complete successfully despite concurrent ad hoc queries consuming resources.
Option A (Hash distribute large fact tables):
Option B (Assign smaller resource class):
Option D (Create sampled statistics):
In Azure Synapse Analytics, using workload management through resource classes is the recommended approach for prioritizing critical operations like automated data loads over less critical ad hoc queries. This ensures business-critical ETL processes complete reliably while maintaining system availability for user queries.
Ultimate access to all questions.
You have an Azure data solution with an enterprise data warehouse named DW1 in Azure Synapse Analytics. Multiple users run concurrent ad hoc queries on DW1. You also perform regular automated data loads to DW1. You need to guarantee that the automated data loads have sufficient memory resources to complete quickly and successfully while the ad hoc queries are executing. What should you do?
A
Hash distribute the large fact tables in DW1 before performing the automated data loads.
B
Assign a smaller resource class to the automated data load queries.
C
Assign a larger resource class to the automated data load queries.
D
Create sampled statistics for every column in each table of DW1.
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