projection

An in-memory copy of part of your database that graph algorithms run against. You choose which Full definition for node (opens in a new tab)A vertex in a graph. In a property graph it can carry labels and properties. and Full definition for relationship (opens in a new tab)A named, directed connection between two nodes. Every relationship has a type, a start node and an end node. it holds.

Also written: projections, graph projection, graph projections

Learn more in Project a graph

Example

The database holds customers, products and categories.

cypher

MATCH (source:Customer)-[:BOUGHT]->(target:Product)
WITH gds.graph.project('purchases', source, target) AS g
RETURN g.graphName, g.nodeCount, g.relationshipCount

purchases holds four nodes and three relationships: the two customers, the two products and the [:BOUGHT] relationships joining them.

The (:Category) node and both [:IN_CATEGORY] relationships are not included.

Lessons that use this term

The lesson and course links below open in a new tab.

86 lessons use this term. The 40 with the highest term density are listed here.

Intermediate Cypher Queries11 mentions

Top MoviesPipelining Queriesquery uses WITH to return a map projection of the top 10 movies by IMDb3 mentions
Adding GenresPipelining Queriesthis query to add the genres to the map projection2 mentions

Building Neo4j Applications with Spring Data42 mentions

Spring Data Neo4j ProjectionsCustom Cypher for Read and Writelesson covers the basics of projections in Spring Data19 mentions
DTO-based projectionsCustom Cypher for Read and Writeyou can use DTO-based projections similarly to interface-based projections with a subset of existing domain class properties, DTO-based projections11 mentions
Interface-based projectionsCustom Cypher for Read and WriteInterface-based projections are a great place to7 mentions

Get started with Graph Data Science273 mentions

Project a graphGDS basic conceptslesson focuses exclusively on Step 1: Projection—the foundation of all GDS22 mentions
Challenge: Aggregated projection and analysisEssential projection techniqueslearned how to aggregate relationships during projection using count(r) to count relationships between node9 mentions
Practice bipartite projectionsGDS basic conceptsgraph structure and graph labels, and when to preserve labels in your projections, it's time to practice creating bipartite25 mentions
Challenge: Monopartite projectionGDS basic conceptslearned how to create various monopartite projections8 mentions
Challenge: Multipartite projectionsGDS basic conceptslearned how to create projections with multiple node7 mentions
Projection modeling for algorithmsEssential projection techniqueslearned how to create projections and how to configure15 mentions
Module recap and what's nextGDS basic conceptscreate an in-memory projection, run algorithms on it, and write results back to your database or use them in8 mentions
Challenge: Projection modeling and analysisEssential projection techniquesthe previous lesson, you learned how to design projections based on analytical16 mentions
Understand relationship aggregationEssential projection techniqueslearned how to use existing relationship properties as weights in your projections15 mentions
Projecting monopartite graphsGDS basic conceptsthe previous lesson, you learned how to create basic Cypher projections19 mentions
Module recap and what's nextWorking with algorithmsView results directly without storing them Mutate - Store results in the projection for chaining algorithms Write - Persist results back to the database Estimate - Check memory requirements8 mentions
Practice relationship aggregationEssential projection techniquesyou'll practice building aggregated projections using count(r) to count relationships between node6 mentions
Module recapEssential projection techniquesView results directly without storing them Mutate - Store results in the projection for chaining algorithms Write - Persist results back to the database Estimate - Check memory requirements11 mentions
Practice monopartite projectionsGDS basic conceptsand graph labels, it's time to practice creating true monopartite projections17 mentions
Projecting bipartite and multipartite graphsGDS basic conceptsthe previous lessons, you learned that GDS creates unlabelled projections by default—preserving graph structure but stripping away node labels and relationship12 mentions
List and drop graphsGDS basic conceptsthat you've practiced creating various types of projections—monopartite, bipartite, and multipartite—it's time to learn how to manage them9 mentions
Understand the GDS workflowGDS basic conceptsExecute algorithms on the projection10 mentions
Configuring projections for undirected relationshipsWorking with algorithmsthis lesson, you'll configure your projection to use undirected relationships and run PageRank and Leiden to see how the results10 mentions
Configuring projections with unweighted relationshipsWorking with algorithmsand without weights How weights affect community detection When weighted projections are6 mentions

Aura Graph Analytics fundamentals43 mentions

Implicit sessionsAura Graph Analytics in the Aura WorkspaceHow to spin up a session and projection at the same time — known as an "implicit10 mentions
Standalone sessions from DataFramesFrom the Python clientBuild a small actor-collaboration projection from two DataFrames Visualize your projection with neo4j-viz Run PageRank on your projection Write everything8 mentions
Aura Graph Analytics workflowAura Graph Analytics in the Aura Workspacein AuraDB, an Aura Graph Analytics session created with get_or_create(), and graph projections created inside the9 mentions
The AGA workflow end to endFrom the Python clientthis step, and you'll either get a session too small for the projection or one larger than you need to pay7 mentions

Analyze Graph Data with Python55 mentions

GDS Workflows in PythonGDS Python ClientExecute the standard five-step GDS workflow in Python Create graph projections and inspect them using the Graph object Choose the right execution mode for different situations Work with15 mentions
From Cypher to Native ProjectionGDS Python ClientYou may have been using Cypher projections when working with GDS in the9 mentions
Running AlgorithmsGDS Python ClientChain algorithms together using mutate mode Stream combined results from projections Estimate memory requirements before3 mentions

Understand centrality algorithms27 mentions

Create your session and projectionsUnderstand centrality algorithmsfundamentals](/courses/aga-fundamentals/) lab explains the technical basics of projection7 mentions

Graph Data Science in Practice90 mentions

Projection Configuration for AlgorithmsGDS FoundationsSome algorithms need specific projection configurations to work correctly--or at23 mentions
The GDS WorkflowGDS Foundationsdata from analysis, enabling fast, iterative experimentation on an in-memory projection of your graph without modifying your original13 mentions
Projection PracticeGDS Foundationscreate both types of projections you learned10 mentions
Graph Projections and StructureGDS Foundationsshowing graph projection process affecting algorithm14 mentions
Algorithm CategoriesGDS FoundationsBefore diving into projections and hands-on work, let's map the3 mentions
Reducing Search Space with LouvainCommunity Detection for FraudCreate a heterogeneous graph projection for fraud analysis Run Louvain in stats and write modes Identify communities containing known fraudsters Focus6 mentions

AI on Your Lakehouse: Context Comes in Shapes, Not Queries12 mentions

Build the Themes ToolSurface Themes - Communitiesbuild skill/scripts/themes.py: the pipeline and renderer are given; the projection query is marked9 mentions

Path Finding with GDS4 mentions

Challenge: Source-Target Shortest PathUsing the Graph Data Science libraryuses the projection you created in the previous1 mention

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