Neo4J Learning Notes
neo4j desktop provide free multi graph databases support, enable you to create and use multiple graph datases at once
to query undirected relationships:
match () – (p) return p
create fulltext index
create fulltext index lucene for (n:Person) on each [n.title, n.description]
call db.index.fulltext.queryNodes(“titlesAndDescriptions”, “Full Metal Jacket”) yield node, score return node, score
calculate customer rating cosine similarity for recommendation:
https://neo4j.com/graphgists/northwind-recommendation-engine
match (c1:customer)-[r1:rated]-(:product)-[r2:rated]-(c2:customer)
with sum(r1.score*r2.score) as dot_product,
sqrt(reduce(x=0, a in r1.score | x+a^2)) as r1_length,
sqrt(reduce(y=0, b in r2.score | y+b^2)) as r2_length
merge (c1)-[s:similarity}]-(c2)
set s += {score:dot_product/(r1_length*r2_length)
use collect to turn maps into lists:
match (p) return collect(p.names)
exist subquery:
match (n:Person) where exists {
match (n) –(t:Tech)
where size((t)-[:likes]-(:Person)) >2
}
return n.name
list comprehension:
return [x in range(0,10) where x%3 = 0| x/2] as list
return [x in range(0,10) where not x in range(4,10) |x ] as list
to use conditional matches or regular expressions:
match () – (p) where p.name in [“helen”] or p.name =~ “.chinese.” return p
create index on properties:
create index for (n:Category) on (n.categoryName)
asterisks:
load csv:
load csv with headers from “http://localhost/person.csv” as line
call {with line
merge (n:person {id: toInteger(line.id)})
set n.name = line.name
} in transactions of 2 rows
count nodes:
match (n) return count(n)
match relationship patterns:
match (n) -[:friend|hater*3]->(p) return p limit 20
node can have multiple labels, while relationship can only have one type, both specified after the colon.
simple case expression:
match(n)
return
case n.eyes
when “blue” then 1
when “brown” then 2
else 3
end as result
generic case expression
match (n)
return
case
when n.eyes = “blue” then 1
when n.age > 40 then 2
else 3 // if without else then return null
end as result
inequality symbol: <>
mutating updating node properties:
match(n)
set n+={name:“helen”} // if using = the properties will be totally replaced instead of update.
return n.name
merge can only ensure the existance of one node or pattern at a time, no comma
plus can concatenate strings
tenporal dataformat can be used as numbers to compute.
Map operators
. for static value access by key, [] for dynamic value access by key
List operators
- for concatenation, IN to check existence of an element in a list, [] for accessing element(s) dynamically
recommendation steps:
first find targets by meta relatonships
next sort recommendation by frequency, ratings or occurance
third filter items by topics or properties