DEA-C02 Exam Dumps | You are tasked with migrating data from a legacy SQL Server database to Snowflake. One of the tables,

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Question 19/149

You are tasked with migrating data from a legacy SQL Server database to Snowflake. One of the tables, 'ORDERS' , contains a column 'ORDER DETAILS that holds concatenated string data representing multiple order items. The data is formatted as 'iteml :qtyl ;item2:qty2;...'. You need to transform this string data into a JSON array of objects, where each object represents an item with 'name' and 'quantity' fields. Which of the following steps and functions would you use in Snowflake to achieve this transformation, in addition to loading the data?

A. Use to split the string into rows, then use 'SPLIT to separate item name and quantity, and finally use 'OBJECT_CONSTRUCT and to create the JSON array.

B. Use ' to extract item names and quantities, then use 'ARRAY_CONSTRUCT and 'OBJECT_CONSTRUCT to create the JSON array.

C. Use ' STRTOK TO ARRAY' to split the string into an array, then iterate through the array using a JavaScript UDF to create the JSON objects.

D. Use 'SPLIT with ';' as delimiter, then apply 'SPLIT again with ':' as delimiter. Finally, construct the JSON array using 'ARRAY_AGG' and 'OBJECT CONSTRUCT

E. Utilize a Java UDF to parse the string and directly generate the JSON array.

Correct Answer: A,D

Options A and D correctly outline the process. (A) and multiple 'SPLIT calls (D) are valid approaches to break down the concatenated string. Then, 'OBJECT_CONSTRUCT builds the individual JSON objects, and aggregates them into a JSON array. While Javascript or Java UDFs (C, E) could solve the problem, they are generally less efficient than Snowflake's built-in functions. (B) might work but is overkill for this simple splitting task, also you would still need to combine the extracted arrays for items and quantities.

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