BigQuery's Powerful Feature: Efficient ARRAY Support and Modelling

The benefits of using ARRAYS in BigQuery include efficient storing and modeling one-to-many relationships and having deep performance implications. They are particularly useful in scenarios where other database systems might require storing data in a separate table or using workarounds like list-like strings or JSON. ARRAYS help in maintaining structured data within a single column, which can be advantageous for both storage and query performance.

Working with ARRAYS in BigQuery becomes straightforward once you understand the basics. The most common operation with ARRAYS is to UNNEST them. This operation takes an ARRAY and returns a table with a row for each element in the ARRAY. It is essential for performing operations on the data within the ARRAY, such as finding the earliest enrollment date or counting distinct activities members are enrolled in. To ensure readability and maintain context, it's recommended to give the UNNESTed items a proper logical name, like activity if you're UNNESTing activities.

When UNNESTing ARRAYS in BigQuery, the way you join the UNNESTed column determines whether you keep members with no activities or not. To retain members who do not have any activities, you should use a LEFT JOIN. This join includes all records from the left table (members), even if there are no matching records in the right table (activities). Conversely, using a CROSS JOIN, a comma (which is also considered a CROSS JOIN), or an INNER JOIN will exclude members without activities, as these joins only include rows with matching records in both tables.