Neo4j Cypher查询性能优化

Question

我有以下Neo4j Cypher查询

MATCH (dg:DecisionGroup)-[:CONTAINS]->(childD:Decision) 
WHERE dg.id = 1 
MATCH (childD)-[relationshipValueRel4:HAS_VALUE_ON]-(filterCharacteristic4:Characteristic) 
WHERE filterCharacteristic4.id = 4 
WITH relationshipValueRel4, childD, dg 
WHERE  (ANY (id IN [2,3] 
WHERE id IN relationshipValueRel4.optionIds ))  
WITH childD, dg  
OPTIONAL MATCH (childD)-[vg:HAS_VOTE_ON]->(c:Criterion) 
WHERE c.id IN [2, 3] 
WITH childD, dg, vg.avgVotesWeight as weight, vg.totalVotes as totalVotes 
WITH childD , dg , toFloat(sum(weight)) as weight, toInt(sum(totalVotes)) as totalVotes  
ORDER BY  weight DESC 
SKIP 0 LIMIT 10 
WITH * MATCH (childD)-[ru:CREATED_BY]->(u:User) OPTIONAL MATCH (childD)-[rup:UPDATED_BY]->(up:User)  
RETURN ru, u, rup, up, childD AS decision, weight, totalVotes, 
[ (dg)<-[:DEFINED_BY]-(entity)<-[:COMMENTED_ON]-(comg:CommentGroup)-[:COMMENTED_FOR]->(childD) | {entityId: toInt(entity.id),  types: labels(entity), totalComments: toInt(comg.totalComments)} ] AS commentGroups, 
[ (dg)<-[:DEFINED_BY]-(c1)<-[vg1:HAS_VOTE_ON]-(childD) | {criterionId: toInt(c1.id),  weight: vg1.avgVotesWeight, totalVotes: toInt(vg1.totalVotes)} ] AS weightedCriteria, [ (dg)<-[:DEFINED_BY]-(ch1:Characteristic)<-[v1:HAS_VALUE_ON]-(childD)  WHERE  NOT ((ch1)<-[:DEPENDS_ON]-())  | {characteristicId: toInt(ch1.id),  optionIds: v1.optionIds, valueIds: v1.valueIds, value: v1.value, available: v1.available, totalHistoryValues: v1.totalHistoryValues, totalFlags: v1.totalFlags, description: v1.description, valueType: ch1.valueType, visualMode: ch1.visualMode} ] AS valuedCharacteristics

我对这个查询执行的性能不太满意。

这是配置文件输出：

Cypher version: CYPHER 3.3, planner: COST, runtime: INTERPRETED. 3296130 total db hits in 2936 ms

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有没有可能优化这个查询性能？

Answer 1

如果没有数据集、图的知识以及要搜索的内容，要优化这个查询将会有点困难。

性能取决于：

1. Query本身
2. 模式(索引和约束)
3. 图建模
4. Neo4j configuration Schema

您的查询没有什么大问题，即使它对我来说可以写成更易读的状态(例如:一个大的match，在match中的where子句上使用clause语法，将any替换为or，等等)，但是它不会改变查询计划。

请确保对此查询使用查询参数，以避免每次都重新计算此长查询的查询计划。

您的查询大部分时间都会传递到(childD)-[relationshipValueRel4:HAS_VALUE_ON]-(:Characteristic) +其上的where子句中(即。1.5M *2个数据库命中)。因此，一个解决方案可以通过创建如下关系来更改模型：HAS_VALUE_ON_WITH_OPTID_1，HAS_VALUE_ON_WITH_OPTID_2 ...