Amazon Neptune Aggregation Query

Amazon Neptune is a high-performance Graph database, which is mainly used to store and query highly connected data. It supports multiple aggregation queries, including COUNT, MIN, MAX, SUM, and AVG. The following is a sample table structure and sample data (use Gremlin diagram to traverse Query language): graph.addVertex('person').property('name', 'Alice').property('age', 25).property('salary', 50000) graph.addVertex('person').property('name', 'Bob').property('age', 30).property('salary', 60000) graph.addVertex('person').property('name', 'Charlie').property('age', 35).property('salary', 70000) graph.addVertex('person').property('name', 'David').property('age', 40).property('salary', 80000) Now, let's take a look at how to implement various aggregated queries. 1. COUNT query: used to calculate the number of vertices or edges that match specific conditions. groovy //Count the number of all person vertices g.V().hasLabel('person').count() 2. MIN and MAX queries: used to find the minimum or maximum values of vertices or edges that match specific conditions. groovy //Find minimum and maximum ages g.V().hasLabel('person').values('age').min() g.V().hasLabel('person').values('age').max() 3. SUM query: used to calculate the sum of numerical values of vertices or edges that match specific conditions. groovy //Calculate the total salary of all person vertices g.V().hasLabel('person').values('salary').sum() 4. AVG query: used to calculate the average numerical value of vertices or edges that match specific conditions. groovy //Calculate the average age of all person vertices g.V().hasLabel('person').values('age').mean() These are some basic aggregation query examples supported by Neptune. According to actual needs, you can use Gremlin language for more complex queries and aggregation operations. Please note that the above example only provides a way to demonstrate query syntax, and actual queries may require more detailed and complex filtering conditions and auxiliary steps.