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Snowflake

SOL-C01 · Question #169

You have a Snowflake table named 'SALES DATA' that you load data into daily from a CSV file using Snowsight. Recently, the load times have increased significantly. You suspect the Virtual Warehouse si

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Virtual Warehouses

Question

You have a Snowflake table named 'SALES DATA' that you load data into daily from a CSV file using Snowsight. Recently, the load times have increased significantly. You suspect the Virtual Warehouse size is the bottleneck. You have the following Virtual Warehouse sizes available: X- Small, Small, Medium, Large, X-Large. Choosing the best size depends on cost and speed. You examine the Query History in Snowsight and notice that the COPY INTO commands are consistently using only a small fraction of the X-Large warehouse's compute resources. Which of the following actions would be the MOST cost- effective while also potentially improving (or at least maintaining) the data loading performance?

Options

  • AIncrease the Virtual Warehouse size to 2X-Large. This will guarantee faster load times.
  • BDecrease the Virtual Warehouse size to Small or Medium. Since the current warehouse is
  • CEnable auto-suspend on the X-Large warehouse if it isn't already enabled. This will reduce costs
  • DKeep the X-Large warehouse but investigate other potential bottlenecks, such as the file format
  • ESwitch to using Snowpipe for continuous data ingestion instead of COPY INTO. This may improve

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Topics

#Warehouse sizing#Query History analysis#COPY INTO performance#Cost optimization
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