What is the process of developing a BigQuery UDF function for UNNESTing various REPEATED levels?

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Understand the data structure: Before developing a BigQuery UDF function for UNNESTing various REPEATED levels, it's important to understand the data structure. This includes identifying the repeated fields, determining how many levels of nesting exist, and identifying the data type of each field.

Define the input and output schema: Next, define the input and output schema for the UDF function. The input schema should match the data structure of the input data, including any repeated fields. The output schema should define the structure of the unnested data, including any new fields that will be created.

Write the function code: Using the SQL language, write code for the UDF function that takes in the input schema, unnests the repeated fields to the desired level, and outputs the data in the defined output schema. This may require using multiple UNNEST() functions and joining data from different tables.

Test the function: Once the function code is written, test it on a small sample of data to ensure that it's working as expected. This may involve tweaking the code and adjusting the output schema until the UDF function is functioning correctly.

Deploy the function: Once the function has been tested and is functioning correctly, deploy it to the production environment. This may involve creating an SQL script that calls the UDF function or incorporating it into a larger ETL pipeline.

Monitor and optimize the function: Finally, monitor the UDF function and optimize it as needed to improve performance or address any issues that arise. This may involve adjusting the code or changing the input/output schema to better suit the data.