A JSON file, that contains lots of dates and arrays, needs to be processed in Snowflake. The user wants to ensure optimal performance while querying the data.
How can this be achieved?
A.
Flatten the data and store it in structured data types in a flattened table. Query the table.
B.
Store the data in a table with a variant data type. Query the table.
C.
Store the data in a table with a vai : ant data type and include STRIP_NULL_VALUES while loading the table. Query the table.
D.
Store the data in an external stage and create views on top of it. Query the views.
Storing JSON data in a table with a VARIANT data type is optimal for querying because it allows Snowflake to leverage its semi-structured data capabilities. This approach enables efficient storage and querying without the need for flattening the data, which can be performance-intensive1.
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