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https://neo4j-contrib.github.io/neo4j-apoc-procedures/#_virtual_nodes_rels
提供的函数存储过程应有尽有，也可以自行实现添加
CALL apoc.help("dijkstra")
Apoc配置：
apoc.trigger.enabled=false/true  :  Enable triggers
apoc.ttl.enabled=false/true:  Enable time to live background task
apoc.jdbc.<key>.uri=jdbc-url-with-credentials :  配置数据库连接串
apoc.es.<key>.uri=es-url-with-credentials：  ES连接
apoc.mongodb.<key>.uri=mongodb-url-with-credentials： mongodb连接
apoc.couchbase.<key>.uri=couchbase-url-with-credentials： couchbase连接
apoc.jobs.scheduled.num_threads=number-of-threads： APOC调度器的线程池
apoc.jobs.pool.num_threads=number-of-threads: 执行器的线程池

有用的函数方法：

解析域名： WITH 'http://www.example.com/all-the-things' AS url RETURN apoc.data.domain(url) // will return 'www.example.com'
日期函数：
apoc.date.parse(<span class="hljs-string">'2015/03/25 03-15-59'</span>,[<span class="hljs-string">'s'</span>],[<span class="hljs-string">'yyyy/MM/dd HH/mm/ss'</span>])
apoc.date.add(<span class="hljs-number">12345</span>, <span class="hljs-string">'ms'</span>, <span class="hljs-number">-365</span>, <span class="hljs-string">'d'</span>) 
格式转换：
<span class="hljs-keyword">return</span> apoc.number.format(<span class="hljs-number">12345.67</span>) <span class="hljs-keyword">as</span> value
<span class="hljs-keyword">return</span> apoc.number.format(<span class="hljs-number">12345</span>, <span class="hljs-string">'#,##0.00;(#,##0.00)'</span>, <span class="hljs-string">'it'</span>) <span class="hljs-keyword">as</span> value
数学运算：
<span class="hljs-keyword">RETURN</span> apoc.number.exact.add(stringA,stringB)
<span class="hljs-keyword">RETURN</span> apoc.number.exact.sub(stringA,stringB)
ETURN apoc.number.exact.mul(stringA,stringB,[prec],[roundingModel]
<span class="hljs-keyword">RETURN</span> apoc.number.exact.div(stringA,stringB,[prec],[roundingModel])
<span class="hljs-keyword">RETURN</span> apoc.number.exact.toInteger(string,[prec],[roundingMode])
<span class="hljs-keyword">RETURN</span> apoc.number.exact.toFloat(string,[prec],[roundingMode])
<span class="hljs-keyword">RETURN</span> apoc.number.exact.toExact(number)
比较节点不同：
apoc.diff.nodes([leftNode],[rightNode])
路径扩展(选择走哪些边， 哪些节点， 几层， 什么时候结束等等)：
CALL apoc.path.expand(startNode &lt;id&gt;|Node, relationshipFilter, labelFilter, minLevel, maxLevel )
MATCH (user:User) WHERE user.id = <span class="hljs-number">460</span>
CALL apoc.path.expandConfig(user,{relationshipFilter:<span class="hljs-string">"RATED"</span>,minLevel:<span class="hljs-number">3</span>,maxLevel:<span class="hljs-number">3</span>,bfs:<span class="hljs-keyword">false</span>,uniqueness:<span class="hljs-string">"NONE"</span>}) <span class="hljs-keyword">YIELD</span> path
<span class="hljs-keyword">RETURN</span> count(*);
apoc.path.subgraphAll(startNode &lt;id&gt;Node/<span class="hljs-keyword">list</span>, {maxLevel, relationshipFilter, labelFilter, bfs:<span class="hljs-keyword">true</span>, filterStartNode:<span class="hljs-keyword">true</span>, limit:<span class="hljs-number">-1</span>}) <span class="hljs-keyword">yield</span> nodes, relationships
MATCH (user:User) WHERE user.id = <span class="hljs-number">460</span>
CALL apoc.path.subgraphNodes(user, {}) <span class="hljs-keyword">YIELD</span> node
<span class="hljs-keyword">RETURN</span> node;
Closeness Centrality：
CALL apoc.algo.closeness([<span class="hljs-string">'TYPE'</span>],nodes,<span class="hljs-string">'INCOMING'</span>) <span class="hljs-keyword">YIELD</span> node, score
Betweenness Centrality：
CALL apoc.algo.betweenness([<span class="hljs-string">'TYPE'</span>],nodes,<span class="hljs-string">'BOTH'</span>) <span class="hljs-keyword">YIELD</span> node, score
pageRank:
CALL apoc.algo.pageRank(nodes) <span class="hljs-keyword">YIELD</span> node, score
<span class="hljs-comment">// only compute over relationships of types TYPE_1 or TYPE_2</span>
CALL apoc.algo.pageRankWithConfig(nodes,{types:<span class="hljs-string">'TYPE_1|TYPE_2'</span>}) <span class="hljs-keyword">YIELD</span> node, score
<span class="hljs-comment">// peroform 10 page rank iterations, computing only over relationships of type TYPE_1</span>
CALL apoc.algo.pageRankWithConfig(nodes,{iterations:<span class="hljs-number">10</span>,types:<span class="hljs-string">'TYPE_1'</span>}) <span class="hljs-keyword">YIELD</span> node, score
dijkstra:
apoc.algo.dijkstra(startNode, endNode, <span class="hljs-string">'KNOWS|&lt;WORKS_WITH|IS_MANAGER_OF&gt;'</span>, <span class="hljs-string">'distance'</span>) <span class="hljs-keyword">YIELD</span> path, weight
apoc.algo.dijkstraWithDefaultWeight(startNode, endNode, <span class="hljs-string">'KNOWS|&lt;WORKS_WITH|IS_MANAGER_OF&gt;'</span>, <span class="hljs-string">'distance'</span>, <span class="hljs-number">10</span>) <span class="hljs-keyword">YIELD</span> path, weight
example:
    MATCH (from:Loc{name:<span class="hljs-string">'A'</span>}), (to:Loc{name:<span class="hljs-string">'D'</span>})
    CALL apoc.algo.dijkstra(from, to, <span class="hljs-string">'ROAD'</span>, <span class="hljs-string">'d'</span>) <span class="hljs-keyword">yield</span> path <span class="hljs-keyword">as</span> path, weight <span class="hljs-keyword">as</span> weight
    <span class="hljs-keyword">RETURN</span> path, weight
community: 标签传播的社区发现算法
apoc.algo.community(times,labels,partitionKey,type,direction,weightKey,batchSize)
example:  遍历<span class="hljs-number">25</span>轮， 
    CALL apoc.algo.community(<span class="hljs-number">25</span>,<span class="hljs-keyword">null</span>,<span class="hljs-string">'partition'</span>,<span class="hljs-string">'X'</span>,<span class="hljs-string">'OUTGOING'</span>,<span class="hljs-string">'weight'</span>,<span class="hljs-number">10000</span>)
aStar: A*遍历算法
apoc.algo.aStar(startNode, endNode, <span class="hljs-string">'KNOWS|&lt;WORKS_WITH|IS_MANAGER_OF&gt;'</span>, <span class="hljs-string">'distance'</span>,<span class="hljs-string">'lat'</span>,<span class="hljs-string">'lon'</span>) <span class="hljs-keyword">YIELD</span> path, weight
cliques： 聚类社区算法：
apoc.algo.cliques(minSize) <span class="hljs-keyword">YIELD</span> clique
apoc.algo.cliquesWithNode(startNode, minSize) <span class="hljs-keyword">YIELD</span> clique
各种距离算法：
apoc.algo.cosineSimilarity([vector1], [vector2])   cosin相似度
apoc.algo.euclideanDistance([vector1], [vector2])  欧几里得距离
apoc.algo.euclideanSimilarity([vector1], [vector2])  欧几里得相似度
Virtual Nodes/Rels: 虚拟节点， 关系  类似视图的概念
MATCH (a)-[r]->(b)
WITH head(labels(a)) AS l, head(labels(b)) AS l2, type(r) AS rel_type, count(*) as count
CALL apoc.create.vNode([l],{name:l}) yield node as a
CALL apoc.create.vNode([l2],{name:l2}) yield node as b
CALL apoc.create.vRelationship(a,rel_type,{count:count},b) yield rel
RETURN *;
CALL apoc.create.vPattern({_labels:['Person'],name:'Mary'},'KNOWS',{since:2012},{_labels:['Person'],name:'Michael'})
CALL apoc.create.vPattern({_labels:['Person', 'Woman'],name:'Mary'},'KNOWS',{since:2012},{_labels:['Person', 'Man'],name:'Michael'})
CALL apoc.create.vPatternFull(['British','Person'],{name:'James', age:28},'KNOWS',{since:2009},['Swedish','Person'],{name:'Daniel', age:30})

Cypher Exectuion： 批量执行脚本

CALL apoc.cypher.runFiles([files or urls],{config}) yield row, result   
runs each statement in the files, all semicolon separated
CALL apoc.cypher.runFile(file or url,{config}) yield row, result

runs each statement in the file, all semicolon separated - currently no schema operations

Manual Index:  手工索引， 默认不会自动更新

synchronously同步更新 只有创建索引时指定autoUpdate:true， 才会真正生效， 更新图时性能上会有影响
apoc.autoIndex.enabled=<span class="hljs-keyword">true</span>  
asynchronously异步更新
apoc.autoIndex.async=<span class="hljs-keyword">true</span>  
默认的异步更新参数：<span class="hljs-number">50000</span> operations <span class="hljs-keyword">or</span> <span class="hljs-number">5000</span> milliseconds 触发
apoc.autoIndex.queue_capacity=<span class="hljs-number">100000</span>
apoc.autoIndex.async_rollover_opscount=<span class="hljs-number">50000</span>
apoc.autoIndex.async_rollover_millis=<span class="hljs-number">5000</span>
apoc.autoIndex.tx_handler_stopwatch=<span class="hljs-keyword">false</span>
添加多个节点属性缩影 配合search用， 重复执行会先删除再创建： apoc.index.addAllNodes('index-name',{label1:['prop1',…],…}, {options})
options的选择(map形式给入)：
type： fulltext/exact  全文索引/精确索引
to_lower_case： <span class="hljs-keyword">false</span>/<span class="hljs-keyword">true</span>
analyzer： classname   用哪种classname of lucene analyzer 
similarity： classname   相似度计算的方式 classname <span class="hljs-keyword">for</span> lucene similarity 
autoUpdate：  <span class="hljs-keyword">true</span>/<span class="hljs-keyword">false</span>  是否自动更新
添加一个节点的属性索引(可以不存在这个属性字段) apoc.index.addNode(node,['prop1',…])
对于给定的标签，添加节点索引(索引名称的Label和node可以不一致)： apoc.index.addNodeByLabel('Label',node,['prop1',…])
给索引命名 默认是Label作为名称：  apoc.index.addNodeByName('name',node,['prop1',…])
apoc.index.addNodeMap(node,{key:value})
apoc.index.addNodeMapByName(index, node,{key:value})
关系索引： apoc.index.addRelationship(rel,['prop1',…])
apoc.index.addRelationshipByName('name',rel,['prop1',…])
apoc.index.addRelationshipMap(rel,{key:value})
apoc.index.addRelationshipMapByName(index, rel,{key:value})
删除节点索引 apoc.index.removeNodeByName('name',node) remove node from an index for the given name
索引模糊查询(计算编辑距离)  apoc.index.search('index-name', 'query') YIELD node, weight
apoc.index.nodes('Label','prop:value*') YIELD node, weight
apoc.index.relationships('TYPE','prop:value*') YIELD rel, weight
没理解： apoc.index.between(node1,'TYPE',node2,'prop:value*') YIELD rel, weight
match (p:Person) call apoc.index.addNode(p,["name","age"]) RETURN count(*); // 129s for 1M People
call apoc.index.nodes(<span class="hljs-string">'Person'</span>,<span class="hljs-string">'name:name100*'</span>) <span class="hljs-keyword">YIELD</span> node, weight <span class="hljs-keyword">return</span> * limit <span class="hljs-number">2</span>
Index Management：
CALL apoc.index.remove('Thing') 
展示： CALL apoc.index.list()
CALL apoc.index.forNodes('name',{config}) YIELD type,name,config
CALL apoc.index.forRelationships('name',{config}) YIELD type,name,config

Triggers ： 触发器

apoc.trigger.enabled=true
Locking： 锁
call apoc.lock.nodes([nodes])
call apoc.lock.rels([relationships])
call apoc.lock.all([nodes],[relationships])

Meta Graph: 展示节点， 关系标签的概览图

CALL apoc.meta.graphSample()
CALL apoc.meta.graph
有选择的展示一部分结果： CALL apoc.meta.subGraph({labels:[labels],rels:[rel-types],excludes:[label,rel-type,…]})
表格形式展示数据： CALL apoc.meta.data
Map形式展示数据： CALL apoc.meta.schema
快速查看图中各种存在的节点，边： CALL apoc.meta.stats yield labelCount, relTypeCount, propertyKeyCount, nodeCount, relCount, labels, relTypes, stats

Sehema:  查看各种索引， 约束

apoc.schema.assert({indexLabel:[indexKeys],…},{constraintLabel:[constraintKeys],…}, dropExisting : true) yield label, key, unique, action
apoc.schema.nodes() yield name, label, properties, status, type
apoc.schema.relationships() yield name, type, properties, status
apoc.schema.node.indexExists(labelName, properties)
apoc.schema.node.constraintExists(labelName, properties)
apoc.schema.relationship.constraintExists(type, properties)

Streaming Data to Gephi： 导出数据到Gephi

apoc.gephi.add(url-or-key, workspace, data, weightproperty, ['exportproperty'])
原文地址：https://www.jianshu.com/p/851ab29420fd