以下查询需要1.5秒到9秒,取决于{keywords}
match (pr:Property)
WHERE (pr.name in {keywords})
with pr
MaTCH (pr) <--(it:Item)
MaTCH (it)-->(pr2)<-[:CAT]-(ca)
return distinct pr2 as prop,count(distinct it) as sum , ca.name as rType
limit 10
每个Item
都与100 Properties
。
服务器上的示例配置文件:
neo4j-sh (?)$ profile match (pr:Property)
WHERE (pr.name in ["GREEN","SHORT","PLAIN","SHORT-SLEEVE"])
with pr
MaTCH (pr) <--(it:Item)
MaTCH (it)-->(pr2)<-[:CAT]-(ca)
return distinct pr2 as prop,count(distinct it) as sum , ca.name as rType
limit 40;
+------------------------------------------------------------------------------------------40 rows
ColumnFilter(symKeys=["prop", "rType", " INTERNAL_AGGREGATE58d28d0e-5727-4850-81ef-7298d63d7be8"], returnItemNames=["prop", "sum", "rType"], _rows=40, _db_hits=0)
Slice(limit="Literal(40)", _rows=40, _db_hits=0)
EagerAggregation(keys=["Cached(prop of type Node)", "Cached(rType of type Any)"], aggregates=["( INTERNAL_AGGREGATE58d28d0e-5727-4850-81ef-7298d63d7be8,Distinct(Count(it),it))"], _rows=40, _db_hits=0)
Extract(symKeys=["it", "ca", " UNNAMED122", "pr", "pr2", " UNNAMED130", " UNNAMED99"], exprKeys=["prop", "rType"], _rows=645685, _db_hits=645685)
SimplePatternMatcher(g="(it)-[' UNNAMED122']-(pr2),(ca)-[' UNNAMED130']-(pr2)", _rows=645685, _db_hits=0)
Filter(pred="hasLabel(it:Item(0))", _rows=6258, _db_hits=0)
SimplePatternMatcher(g="(it)-[' UNNAMED99']-(pr)", _rows=6258, _db_hits=0)
Filter(pred="any(-_-INNER-_- in Collection(List(Literal(GREEN), Literal(SHORT), Literal(PLAIN), Literal(SHORT-SLEEVE))) where Property(pr,name(1)) == -_-INNER-_-)", _rows=4, _db_hits=1210)
NodeByLabel(identifier="pr", _db_hits=0, _rows=304, label="Property", identifiers=["pr"], producer="NodeByLabel")
neo4j版本:2.0.1
堆大小:最大3.2 GB(甚至不接近它......)
DataBase磁盘使用量:270MB
NumOfNodes:4368
NumOf Relationships:395693
计算机:AWS EC2 c3.large。 但是,尝试在4倍速的计算机上运行它,结果是一样的..
在查看JConsole时,我可以看到堆从50mb变为70mb,然后由GC清理。
无论如何要让它更快?这种表现对我来说太慢了......
修改 正如我所建议的那样,我尝试组合匹配,但它在配置文件中看起来比较慢:
neo4j-sh(?)$ profile match(pr:Property) WHERE(pr .name in [“GREEN”,“SHORT”,“PLAIN”,“SHORT-SLEEVE”]) 与公关 MaTCH(pr)&lt; - (it:Item) - &gt;(pr2)&lt; - [:CAT] - (ca) 返回distinct pr2作为prop,count(distinct it)为sum,ca.name为rType 限制40;
ColumnFilter(symKeys=["prop", "rType", " INTERNAL_AGGREGATEa6eaa53b-5cf4-4823-9e4d-0d1d66120d51"], returnItemNames=["prop", "sum", "rType"], _rows=40, _db_hits=0)
Slice(limit="Literal(40)", _rows=40, _db_hits=0)
EagerAggregation(keys=["Cached(prop of type Node)", "Cached(rType of type Any)"], aggregates=["( INTERNAL_AGGREGATEa6eaa53b-5cf4-4823-9e4d-0d1d66120d51,Distinct(Count(it),it))"], _rows=40, _db_hits=0)
Extract(symKeys=[" UNNAMED111", "it", "ca", " UNNAMED119", "pr", "pr2", " UNNAMED99"], exprKeys=["prop", "rType"], _rows=639427, _db_hits=639427)
Filter(pred="(hasLabel(it:Item(0)) AND hasLabel(it:Item(0)))", _rows=639427, _db_hits=0)
SimplePatternMatcher(g="(ca)-[' UNNAMED119']-(pr2),(it)-[' UNNAMED99']-(pr),(it)-[' UNNAMED111']-(pr2)", _rows=639427, _db_hits=0)
Filter(pred="any(-_-INNER-_- in Collection(List(Literal(GREEN), Literal(SHORT), Literal(PLAIN), Literal(SHORT-SLEEVE))) where Property(pr,name(1)) == -_-INNER-_-)", _rows=4, _db_hits=1210)
NodeByLabel(identifier="pr", _db_hits=0, _rows=304, label="Property", identifiers=["pr"], producer="NodeByLabel")
答案 0 :(得分:2)
首先,确保对Property标签上的name属性建立索引。据我所知,索引不能与IN语句一起使用,但这应该在将来的版本中解决。表现会很快好起来。
CREATE INDEX ON :Property(name)
您可以按如下方式缩小查询:
MATCH (pr:Property)
WHERE (pr.name in {keywords})
MATCH (pr)<--(it:Item)-->(pr2)<-[:CAT]-(ca)
RETURN distinct pr2 as prop,count(distinct it) as sum , ca.name as rType
LIMIT 10
答案 1 :(得分:2)
两个你可以做&#34;解决方法&#34;,直到IN为索引修复:
将其拆分为两个查询,
第一个使用索引查找和所有这些的联合,如
MATCH (pr:Property {keyword:{keyword1}) return id(pr)
UNION ALL
MATCH (pr:Property {keyword:{keyword2}) return id(pr)
...
等
然后在第二个查询中执行:
MATCH (pr) WHERE ID(pr) IN {ids}
MaTCH (pr) <--(it:Item)
MaTCH (it)-->(pr2)<-[:CAT]-(ca)
return distinct pr2 as prop,count(distinct it) as sum , ca.name as rType
limit 10
为&#34;关键字&#34;创建node_auto_index;然后使用lucene查询语法进行初始查找。
START pr=node:node_auto_index('keyword:("GREEN" "SHORT" "PLAIN" "SHORT-SLEEVE")')
MaTCH (pr) <--(it:Item)
MaTCH (it)-->(pr2)<-[:CAT]-(ca)
return distinct pr2 as prop,count(distinct it) as sum , ca.name as rType
limit 10