DataStax Enterprise Graph Aggregation Query

DataStar Enterprise (DSE) Graph is a distributed Graph database that provides powerful query functions and supports multiple aggregate queries. The following are some aggregation queries supported by DSE Graph and their implementation examples. 1. Count (Statistics) -Syntax: ` g. V(). count()` -Example: Counting the number of vertices in a graph g.V().count() 2. Group -Syntax: ` g. V(). group(). by ('property ')` -Example: Grouping by specific attributes of vertices and counting the number of each group g.V().group().by('country').by(__.count()).next() 3. Sum -Syntax: ` g. V(). values ('property '). sum()` -Example: Calculate the sum of specific attributes for all vertices g.V().values('age').sum() 4. Average -Syntax: ` g. V(). values ('property '). mean()` -Example: Calculate the average value of specific attributes for all vertices g.V().values('price').mean() 5. Max -Syntax: ` g. V(). values ('property '). max()` -Example: Find the maximum value of a specific attribute among all vertices g.V().values('temperature').max() 6. Min (minimum value) -Syntax: ` g. V(). values ('property '). min()` -Example: Find the minimum value of a specific attribute among all vertices g.V().values('population').min() 7. OrderBy -Syntax: ` g. V(). values ('property '). order()` -Example: Sort vertices in ascending order by specific attributes g.V().values('name').order() It should be noted that the table structure and sample data in the above examples are not mentioned because DSE Graph is based on the model of the Graph database and is uncertain about the specific table structure and data model. You can define vertices and edges in the graph based on your own application scenario, and use corresponding attributes to perform aggregation queries. The above examples can be constructed and executed based on specific requirements and data models.