DEA-C02 · Question #95
A Data Engineer is using Snowpark to perform data transformations on large data sets in Snowflake. The Engineer wants to optimize the transformation process by minimizing the amount of data distribute
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Question
A Data Engineer is using Snowpark to perform data transformations on large data sets in Snowflake. The Engineer wants to optimize the transformation process by minimizing the amount of data distributed across nodes, and leveraging Snowflake’s compute resources most effectively. Which combination of strategies should the Engineer use to meet these requirements?
Options
- ALoad data using read, apply sorting operations before filtering, and use
- BPerform joins using the default settings, apply transformations across all columns simultaneously,
- CUse the method to store results temporarily, apply filtering operations
- DCreate data samples with session.createDataFrame(), merge datasets using unionAll(),
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