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Neo4j

https://neo4j.com/

Graph database that uses a Cypher language for querying.

Key Points

  • Use Case is complex queries that would be too expensive with many cartesian product joins in RDBMS
  • Not as suited to simple aggregates / large set-oriented / graph global operations
  • Labeled Property Graph (LPG) Database of nodes and relationships
  • Small footprint
  • powerful traversal framework
  • Cypher - declarative query language (SQL for graphs but instead uses ASCII art to represent patterns)
  • Gremlin Traversal Language
  • ACID compliant
  • granular modelling (don't use rich properties, split in to entities and link them to allow for more flexible querying)
  • avoid dense/super nodes - too highly connected as this impacts traversal performance
    • create artificial "meta" nodes of 100 relationships to fan out the user base to an artist
  • Community Edition - Single Server (no horizontal scalability)
  • Enterprise Edition:
    • Clustering (HA & LB) - Master -> Slaves, LB different queries to different slaves to get shard caching of subsets of the graph on each node for better performance (3.0+) - HA master election is based on Paxos
    • advanced monitoring
    • advanced caching
    • online backups

graph local -> anchor vertex (node), traverse edges (relationships) from there

  • specialised graph modelling required based on use case queries
  • highly flexible schema / dynamic schema evolution

Example:

  • news index ElasticSearch tokenize nouns -> neo4j <- clients Sentiment

Quickstart

neo4j start

Browse to:

http://localhost:7474

Nodes <--- Relationships ---> Nodes

Nodes + Relationships each have Properties (key:value pairs)

node.property / relationship.property - boolean, numeric, string or array of boolean, numeric, string

Label - organizes nodes into groups (added in 2.0 late 2013)

nouns => entities verbs => relationships adjectives => properties

Monitoring

Nagios TODO:

  • neo4j replication lag check

ETL

Talend -> JDBC -> Rest API (inefficient)

1. Small - Neo4j web page

Generate Cypher create statements on the Neo4j web page.

2. Medium - Neo4j-shell-tools

  • reads nodes + relationships CSV, generate CSVs + import using:
import-cypher -d ',' -i 'nodes.csv' -o 'nodes-output.log' 'CREATE (n:#{Label}) {id:{Node},name:{Name}}) RETURN *';
import-cypher -d ',' -i 'rels.csv' -o 'rels-output.log' 'MATCH (from {id:{From}}), (to {id:{To}}) CREATE from-[:#{Relationship Type}]->to RETURN *;'

3. Medium - Neo4j Browser Tool

LOAD CSV WITH HEADERS FROM "file:/path/to/file.csv" AS NODES CREATE (n {id: nodes.Node, name: nodes.Name, type: nodes.Label}) RETURN n;

For 200k+ rows

LOAD CSV WITH HEADERS FROM "file:/path/to/file.csv" AS RELS MATCH (from {id: rels.From}), (to {id: rels.To}) CREATE from-[:REL {type: rels {type: rels.`Relationship Type`}]->to RETURN from,to;

Assign labels:

MATCH (m {type:"Male"}), (f {type:"Female"}) SET m:Male, f:Female RETURN m,f;

Create relationships:

MATCH (n)-[r1 {type:"MOTHER_OF"}]->(m), (s)-[r2 {type:"FATHER_OF"}]->(t) CREATE n[:MOTHER_OF]->m, s-[:FATHER_OF]->(t) RETURN *;

Remove duplicate relationships:

MATCH ()->[r:REL]-() delete r;

4. Large - Bulk batch graph.db writer

https:/jexp/batch-import

  • can append, default overwrite
  • tsv nodes - node name label
  • rels - start end type
import.sh test.db nodes.tsv rels.tsv &&
mv test.db "$NEO4J_HOME/data" &&
neo4j start

Cypher

The query language used by Neo4j.

Identifier used for query reference purpose to RETURN identifier.properties

Syntax Description
(a) Nodes given identifier a
(a) --> (b) Nodes a have a relationship to nodes b
(a) -[r]-> (b) Relationship given identifier r between nodes a and b
(a)-[:ACTED_IN]->(m) Find nodes a that have an ACTED_IN type relationship to nodes m. Relationship type is by convention all UPPERCASE_WITH_UNDERSCORES
(m {title:"The Matrix"}) Find nodes where the title property equals "The Matrix"

Query Template

MATCH (node:Label)-[relationship_id:relationship_type)->(node2:Label)

RETURN node.propertyA, node2.propertyB, relationship_id.propertyC, type(relationship_id) ;

WHERE - both these queries are equivalent ways

MATCH (node:Label) WHERE node.property = "value" AND node.property2 = "value2"

MATCH (node:Label {property:"value", property2:"value2"} )
CREATE INDEX ON :Label(property);

Find all a nodes with any relationships to any other nodes:

MATCH (a) ---> ( )
RETURN a
Command Description
MATCH Matches the given graph pattern in the graph data
WHERE Filters using predicates or anchors pattern elements
RETURN Returns and projects result data, also handles aggregation
ORDER BY Sorts the query result
SKIP/LIMIT Paginates the query result

Updating the Graph

Command Description
CREATE Creates nodes and relationships
MERGE Creates nodes uniquely
CREATE UNIQUE Creates relationships uniquely
DELETE Removes nodes, relationships
SET Updates properties and labels
REMOVE Removes properties and labels
FOREACH Performs updating actions once per element in a list
WITH Divides a query into multiple, distinct parts and passes results from one to the next
INDEX
DISTINCT 
MATCH (actor)-[:ACTED_IN]->(movie)<-[:DIRECTED]-(director)
RETURN actor.name, movie.title, director.name;

Path:

MATCH p=(a)-->(b)
RETURN p

Return just the nodes or the relationships:

RETURN nodes(p)
RETURN rels(p)
MATCH (a)-[:ACTED_IN]->(m)
RETURN a.name, m.title
SKIP 10
LIMIT 10;
MATCH (p:Person)
RETURN p.name
ORDER BY p.born
LIMIT 5;

Explore

Browse nodes:

MATCH (n) RETURN (n) LIMIT 20;

See Labels:

MATCH (n) WHERE has(n.name) RETURNS labels(n);

See types of relationships:

MATCH (n:Person)-[r]->() RETURN DISTINCT type(r);
MATCH (a)-[:ACTED_IN]->()
RETURN DISTINCT a
ORDER BY a.born
LIMIT 5

Aggregate functions:

count(x)
min(x)
max(x)
avg(x)
sum(x)
collect(x) # Collect all the values into a list

Libraries

Ported from private Knowledge Base page 2013+