Module overview
Aggregation in Cypher means that during a query, the data retrieved is collected or counted. The aggregation of values or counts are either returned from the query or are used as input for the next part of a multi-step query. If you view the execution plan for the query, you will see that rows are returned for a step in the query. The rows that are returned in a query step are an aggregation of property values, nodes, relationships, or paths in the graph. There are some best practices for aggregating data during your query that you can better understand with examples and explanations of how the query works at runtime.
In this module, you will learn how aggregation works at runtime when using:
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collect() -
collect()vs. subqueries -
Using
count() -
Using pattern comprehension
Data model for this course
This course uses the recommendations dataset for all the queries you will be running and writing. This is the same dataset that will be used for the application development courses in GraphAcademy.
Here is the graph data model:
You can view the data model in the sandbox to the right by executing this query:
CALL db.schema.visualization()The node labels for the graph include:
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Person
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Actor
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Director
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Movie
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Genre
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User
The relationships for the graph include:
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ACTED_IN (with an optional role property)
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DIRECTED (with an optional role property)
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RATED (with rating and timestamp properties)
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IN_GENRE
Also notice that the nodes have a number of properties, along with the type of data that will be used for each property. It is important that you understand the property types defined in the data model.
You can view the property types for nodes in the graph by executing this query:
CALL db.schema.nodeTypeProperties()You can view the property types for relationships in the graph by executing this query:
CALL db.schema.relTypeProperties()