
Explanation:
To identify data skew in a dedicated SQL pool table, the most appropriate approach is to connect to the specific dedicated SQL pool (Pool1) and run the DBCC PDW_SHOWSPACEUSED command. This command provides detailed information about space usage and data distribution across distributions, which directly helps identify data skew by showing how data is distributed among the compute nodes.
Why Option B is optimal:
DBCC PDW_SHOWSPACEUSED is specifically designed for Azure Synapse Analytics dedicated SQL pools to show space usage statisticsWhy other options are less suitable:
sys.dm_pdw_nodes_db_partition_stats can provide partition statistics, connecting to the built-in pool (serverless SQL pool) to query this DMV against a dedicated pool is not supported. Serverless pools cannot access dedicated pool DMVs directly.sys.dm_pdw_node_status provides information about node health and status, not detailed data distribution or space usage metrics needed to identify data skew.sys.dm_pdw_sys_info contains system-level information about the SQL pool but doesn't provide the granular table-level distribution details required to measure data skew.The DBCC PDW_SHOWSPACEUSED command is the most direct and reliable method for identifying data skew in dedicated SQL pool tables, as it specifically shows how data is distributed across the 60 distributions, which is fundamental to detecting and quantifying data skew.
Ultimate access to all questions.
You have an Azure Synapse Analytics dedicated SQL pool named Pool1 that contains a fact table named Table1. You need to determine the extent of data skew in Table1. What should you do in Synapse Studio?
A
Connect to the built-in pool and query sys.dm_pdw_nodes_db_partition_stats.
B
Connect to Pool1 and run DBCC PDW_SHOWSPACEUSED.
C
Connect to Pool1 and query sys.dm_pdw_node_status.
D
Connect to the built-in pool and query sys.dm_pdw_sys_info.
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