Question

设定：

Neo4j - 1.9.3
~7,000个节点
~180万人关系

我有以下cypher查询，我想提高性能：

START a=node(2) MATCH (a)-[:knowledge]-(x)-[:depends]-(y)-[:knowledge]-(end) RETURN COUNT(DISTINCT end);

返回471（188171 ms）。

现在我只得到一个计数，但后来我可能想得到这些值（本例中为471）。问题是运行大约需要3-4分钟。

图表与许多关系密切相关。运行以下内容可显示节点a（2）中存在多少“知识”类型的边。

START a=node(2) MATCH (a)-[:knowledge]-(x) RETURN COUNT(a);

返回4350（103毫秒）。

对我来说，这似乎不是很多边缘要检查。我能否以某种方式将其拆分以提高性能？

编辑：根据评论，以下是使用个人资料运行查询的结果：

profile START a=node(2) MATCH (a)-[:knowledge]-(x)-[:depends]-(y)-[:knowledge]-(end) RETURN COUNT(DISTINCT end);
==> +---------------------+
==> | COUNT(DISTINCT end) |
==> +---------------------+
==> | 471                 |
==> +---------------------+
==> 1 row
==> 
==> ColumnFilter(symKeys=["  INTERNAL_AGGREGATEcd2aff18-1c9d-47a8-9217-588cb86bbc1a"], returnItemNames=["COUNT(DISTINCT end)"], _rows=1, _db_hits=0)
==> EagerAggregation(keys=[], aggregates=["(  INTERNAL_AGGREGATEcd2aff18-1c9d-47a8-9217-588cb86bbc1a,Distinct)"], _rows=1, _db_hits=0)
==>   TraversalMatcher(trail="(a)-[  UNNAMED7:knowledge WHERE true AND true]-(x)-[  UNNAMED8:depends WHERE true AND true]-(y)-[  UNNAMED9:knowledge WHERE true AND true]-(end)", _rows=25638262, _db_hits=25679365)
==>     ParameterPipe(_rows=1, _db_hits=0)

Answer 1

我最终做了以下工作以提高性能：

profile START a=node(2) MATCH (a)-[:knowledge]-(x) WITH DISTINCT x MATCH (x)-[:depends]-(y) WITH DISTINCT y MATCH (y)-[:knowledge]-(end) WITH DISTINCT end RETURN COUNT(end);
==> +------------+
==> | COUNT(end) |
==> +------------+
==> | 471        |
==> +------------+
==> 1 row
==> 
==> ColumnFilter(symKeys=["  INTERNAL_AGGREGATE1967576a-d357-457a-b799-adbb16b93048"], returnItemNames=["COUNT(end)"], _rows=1, _db_hits=0)
==> EagerAggregation(keys=[], aggregates=["(  INTERNAL_AGGREGATE1967576a-d357-457a-b799-adbb16b93048,Count)"], _rows=1, _db_hits=0)
==>   Distinct(_rows=471, _db_hits=0)
==>     PatternMatch(g="(end)-['  UNNAMED3']-(y)", _rows=403437, _db_hits=0)
==>       Distinct(_rows=735, _db_hits=0)
==>         PatternMatch(g="(x)-['  UNNAMED2']-(y)", _rows=1653, _db_hits=0)
==>           Distinct(_rows=177, _db_hits=0)
==>             TraversalMatcher(trail="(a)-[  UNNAMED1:knowledge WHERE true AND true]-(x)", _rows=4350, _db_hits=4351)
==>               ParameterPipe(_rows=1, _db_hits=0)

通过使每个步骤在整体中占很小的一部分，它降低了整体复杂性，并且只跟随匹配的边缘。

在长时间的比赛中提高Neo4j Cypher的性能

1 个答案: