Algorithms section & degree docs

.wordlist.txt

@@ -348,6 +348,9 @@ hostnames
 bigmac
 calmcode
 io
+influencers
+analytics
+Pathfinding
 kafka
 readme
 github

algorithms/degree.md

@@ -0,0 +1,170 @@
+---
+title: "Degree"
+description: "Measures the number of incoming or outgoing conections for all nodes."
+parent: "Algorithms"
+---
+
+# Degree Procedure Documentation
+
+## Introduction
+
+The **Degree Procedure** calculates the degree of nodes in a graph based on the specified parameters.
+This allows users to analyze the connectivity of nodes in terms of incoming or outgoing edges, filtered by node labels and relationship types.
+
+---
+
+## Use Cases
+
+Here are some practical scenarios where the **Degree Procedure** can be applied:
+
+1. **Social Network Analysis**: Identify influencers or highly connected individuals by calculating the degree of `Person` nodes in a social graph.
+2. **Infrastructure Planning**: Determine bottlenecks in a transportation network by analyzing nodes with high incoming or outgoing connections.
+3. **E-commerce Recommendations**: Identify popular products or categories by computing the degree of `Product` or `Category` nodes based on customer interactions.
+4. **Fraud Detection**: Spot suspicious activities by analyzing nodes with unusually high degrees in financial transaction graphs.
+
+---
+
+## Syntax
+
+The procedure has the following call signature:
+```procedure input:
+CALL algo.dgree({
+	'srcLabels':      		[<label>, ...],
+	'dir':         	  		'incoming' / 'outgoing' / 'both',
+	'relationshipTypes':    [<type>, ...],
+	'destLabels':     		[<label>, ...],
+})
+```
+
+### Parameters
+
+| Name                | Type                  | Description                                | Default   |
+|---------------------|-----------------------|--------------------------------------------|-----------|
+| `srcLabels`      	  | [optional] [string[]] | type of nodes for which degree is computed | All Nodes |
+| `dir`         	  | [optional] [string]   | 'incoming', 'outgoing', or 'both'          | outgoing  |
+| `relationshipTypes` | [optional] [string[]] | the type of edges to consider              | All edges |
+| `destLabels` 		  | [optional] [string[]] | type of reachable nodes                    | All Nodes |
+
+---
+
+## Output
+
+The procedure returns a result set where each row corresponds to a node and includes the following fields:
+
+| Field    | Type | Description                      |
+| -------- | ---- | -------------------------------- |
+| `node`   | Node | The Node object.                 |
+| `degree` | Int  | The computed degree of the node. |
+
+---
+
+## Setting Up the Graph
+
+To run the examples below, create the following graph structure:
+
+### Nodes:
+
+| ID | Label  |
+| -- | ------ |
+| 1  | Person |
+| 2  | Person |
+| 3  | City   |
+| 4  | City   |
+
+### Relationships:
+
+| Source | Target | Type    |
+| ------ | ------ | ------- |
+| 1      | 2      | FRIEND  |
+| 1      | 3      | VISITED |
+| 2      | 3      | VISITED |
+| 2      | 4      | VISITED |
+
+Create this graph using the following commands:
+
+```plaintext
+CREATE (:Person {id: 1})
+CREATE (:Person {id: 2})
+CREATE (:City {id: 3})
+CREATE (:City {id: 4})
+CREATE (p1:Person {id: 1})-[:FRIEND]->(p2:Person {id: 2})
+CREATE (p1)-[:VISITED]->(c1:City {id: 3})
+CREATE (p2)-[:VISITED]->(c1)
+CREATE (p2)-[:VISITED]->(c2:City {id: 4})
+```
+
+![Example Graph](../images/person_city.png)
+---
+
+## Examples and Results
+
+### Example 1: Compute the outgoing degree for all nodes
+
+```plaintext
+CALL algo.degree()
+```
+
+#### Result:
+
+| Node | Degree |
+| ---- | ------ |
+| 1    | 2      |
+| 2    | 3      |
+| 3    | 0      |
+| 4    | 0      |
+
+---
+
+### Example 2: Compute the outgoing degree for specific node types
+
+```plaintext
+CALL algo.degree({srcLabels: ['Person']})
+```
+
+#### Result:
+
+| Node | Degree |
+| ---- | ------ |
+| 1    | 2      |
+| 2    | 3      |
+
+---
+
+### Example 3: Compute the total degree for a specific relationship type
+
+```plaintext
+CALL algo.degree({srcLabels: ['Person'], relationshipTypes: ['FRIEND'], dir: 'total'})
+```
+
+#### Result:
+
+| Node | Degree |
+| ---- | ------ |
+| 1    | 1      |
+| 2    | 1      |
+
+---
+
+### Example 4: Compute the incoming degree for reachable nodes of a specific type
+
+```plaintext
+CALL algo.degree({srcLabels: ['Person'], relationshipTypes: ['VISITED'], dir: 'incoming', destLabels: ['City']})
+```
+
+#### Result:
+
+| Node | Degree |
+| ---- | ------ |
+| 3    | 2      |
+| 4    | 1      |
+
+## Usage Notes
+
+- When `both` is specified, the in and out degrees of the node are summed. So if 
+    (a)-[:R]->(b) and (b)-[:R]->(a) then (a) would have a degree of 2 when 
+    `both` is specified.
+- When multiple labels are specified, the nodes' degrees accross each of those 
+    labels are summed together.
+- This algorithm counts multi-edges and self-edges towards the degree.
+- Computationally cheapest when computing the outdegree, especially on 
+    undirected graphs.

algorithms/index.md

@@ -0,0 +1,59 @@
+---
+title: "Graph Algorithms"
+description: Graph Algorithms
+nav_order: 4
+has_children: true
+---
+
+# FalkorDB Algorithms Documentation
+
+Welcome to the FalkorDB Algorithms Documentation! This guide provides an overview of all algorithms available within FalkorDB, enabling powerful graph analytics and insights. Each algorithm is designed to help you process and analyze graph data efficiently for a variety of use cases.
+
+## Available Algorithms
+
+Below is the list of supported algorithms in FalkorDB. Click on an algorithm to view its detailed documentation, including syntax, examples, and practical use cases:
+
+### Traversal Algorithms
+- [BFS](algorithms/BFS)
+  - Performs a Breadth-First Search traversal of the graph.
+
+### Centrality Algorithms
+- [PageRank](algorithms/page_rank)
+  - Measures the importance of nodes based on incoming connections.
+
+### Connectivity Algorithms
+- [Degree](algorithms/degree)
+  - Calculates the degree of nodes, focusing on connectivity based on edge direction and type.
+
+### Pathfinding Algorithms
+- [Shortest Path](algorithms/shortest_path)
+  - Finds the shortest path between two nodes.
+
+### Community Detection Algorithms
+- [Label Propagation](algorithms/label_propagation)
+  - Identifies communities based on label diffusion through the graph.
+
+---
+
+## Getting Started
+
+To begin using any of the algorithms:
+1. Ensure FalkorDB is installed and running.
+2. Load your graph data into FalkorDB.
+3. Refer to the detailed documentation for each algorithm to configure and execute it.
+
+For example, to calculate node degrees:
+
+```plaintext
+CALL algo.degree({})
+```
+
+---
+
+## Feedback and Contributions
+
+We welcome feedback and contributions! If you encounter issues or have suggestions for new algorithms, please visit our [GitHub repository](https://github.com/FalkorDB/FalkorDB).
+
+Happy graph analytics with FalkorDB!
+
+

bolt_support.md

@@ -1,6 +1,6 @@
 ---
 title: "BOLT protocol support"
-nav_order: 10
+nav_order: 11
 description: "Connecting to FalkorDB using BOLT protocol."
 ---
 

clients.md

@@ -1,6 +1,6 @@
 ---
 title: "Client Libraries"
-nav_order: 4
+nav_order: 5
 description: >
     FalkorDB Clients
 ---

cypher/index.md

@@ -1,6 +1,6 @@
 ---
 title: "Cypher Language"
-nav_order: 7
+nav_order: 9
 description: >
     Cypher Language documentation 
 has_children: true

datatypes.md

@@ -1,7 +1,7 @@
 ---
 title: "Data types"
 description: "FalkorDB supports a number of distinct data types, some of which can be persisted as property values and some of which are ephemeral."
-nav_order: 5
+nav_order: 6
 ---
 
 # Graph types

docker-examples/README.md

@@ -1,6 +1,6 @@
 ---
 title: Building Docker
-nav_order: 6
+nav_order: 8
 description: "Building docker container examples"
 ---
 

integration/index.md

@@ -2,7 +2,7 @@
 title: "Integration"
 description: "Learn how to integrate FalkorDB into your applications with REST APIs"
 has_children: true
-nav_order: 5
+nav_order: 7
 ---
 
 # Integration

llm_support.md

@@ -1,6 +1,6 @@
 ---
 title: "LLM frameworks support"
-nav_order: 8
+nav_order: 10
 description: "FalkorDB supports a number of LLM frameworks."
 ---
 

operations/index.md

@@ -1,6 +1,6 @@
 ---
 title: "Operations"
-nav_order: 10
+nav_order: 12
 description: "Configuring FalkorDB Docker"
 ---
 

redisgraph-to-falkordb.md

@@ -1,6 +1,6 @@
 ---
 title: "RedisGraph to FalkorDB"
-nav_order: 11
+nav_order: 13
 description: "Migrate from RedisGraph to FalkorDB."
 ---