FaunaDB aggregation query

FaunaDB is a distributed, Multi-model database that provides rich aggregate query functions. The following are some aggregation queries supported by FaunaDB and their examples: 1. Count: The Count function is used to calculate the number of documents in a collection. Example: Counting the number of documents in a collection. Count(Documents(Collection("my_collection"))) 2. Sum: The Sum function is used to calculate the sum of a certain field in a set. Example: Calculate the sum of a field in a set. Sum(Select(["data", "field"], Paginate(Documents(Collection("my_collection"))))) 3. Avg (average value): The Avg function is used to calculate the average value of a field in a set. Example: Calculate the average value of a field in a set. Avg(Select(["data", "field"], Paginate(Documents(Collection("my_collection"))))) 4. Min: The Min function is used to find the minimum value of a field in a set. Example: Find the minimum value of a field in a set. Min(Select(["data", "field"], Paginate(Documents(Collection("my_collection"))))) 5. Max: The Max function is used to find the maximum value of a field in a set. Example: Find the maximum value of a field in a set. Max(Select(["data", "field"], Paginate(Documents(Collection("my_collection"))))) 6. GroupBy: The GroupBy function is used to group a collection based on the value of a specified field. Example: Grouping a collection based on the value of a certain field and calculating the number of documents in each group. Let( { groups: GroupBy( Lambda("doc", Get(Var("doc"))), Paginate(Documents(Collection("my_collection"))) ) }, { group: Select(["data", "group"], Var("groups")), count: Count(Select(["data"], Var("group"))) } ) Please note that the 'my_collection' in the above example represents a collection that you need to replace with the corresponding set name, field name, and document data based on your own table structure and data. These aggregation query examples are only a small part of the functionality of FaunaDB, as well as other aggregation functions such as Distinct, Union, Intersection, etc. You can use these functions to create more complex aggregate queries based on actual needs.