与 mysql 相比，neo4j 的性能(如何改进?)
这是无法重现/验证图形数据库和行动手册中的neo4j 中的性能声明的后续行动.我已经更新了设置和测试，不想对原来的问题改动太多.
This is a follow up to can't reproduce/verify the performance claims in graph databases and neo4j in action books. I have updated the setup and tests, and don't want to change the original question too much.
整个故事(包括脚本等)在 https://baach.de/Members/jhb/neo4j-performance-compared-to-mysql
The whole story (including scripts etc) is on https://baach.de/Members/jhb/neo4j-performance-compared-to-mysql
简短版本:在尝试验证图形数据库"一书中的性能声明时，我得出了以下结果(查询包含 n 个人的随机数据集，每个人有 50 个朋友):
Short version: while trying to verify the performance claims made in the 'Graph Database' book I came to the following results (querying a random dataset containing n people, with 50 friends each):
My results for 100k people
depth neo4j mysql python
1 0.010 0.000 0.000
2 0.018 0.001 0.000
3 0.538 0.072 0.009
4 22.544 3.600 0.330
5 1269.942 180.143 0.758
"*": 仅单次运行
My results for 1 million people
depth neo4j mysql python
1 0.010 0.000 0.000
2 0.018 0.002 0.000
3 0.689 0.082 0.012
4 30.057 5.598 1.079
5 1441.397* 300.000 9.791
"*": 仅单次运行
在 64 位 ubuntu 上使用 1.9.2 我已经用这些值设置了 neo4j.properties:
Using 1.9.2 on a 64bit ubuntu I have setup neo4j.properties with these values:
neostore.nodestore.db.mapped_memory=250M
neostore.relationshipstore.db.mapped_memory=2048M
和neo4j-wrapper.conf:
and neo4j-wrapper.conf with:
wrapper.java.initmemory=1024
wrapper.java.maxmemory=8192
我对 neo4j 的查询如下所示(使用 REST api):
My query to neo4j looks like this (using the REST api):
start person=node:node_auto_index(noscenda_name="person123") match (person)-[:friend]->()-[:friend]->(friend) return count(distinct friend);
Node_auto_index 到位，很明显
Node_auto_index is in place, obviously
我能做些什么来加速neo4j(比mysql更快)?
还有 Stackoverflow 中的另一个基准测试 有同样的问题.
And also there is another benchmark in Stackoverflow with same problem.
推荐答案
很抱歉您无法重现结果.但是，在 MacBook Air(1.8 GHz i7，4 GB RAM)上有 2 GB 堆、GCR 缓存，但没有缓存升温，也没有其他调整，具有类似大小的数据集(100 万用户，每人 50 个朋友)，我在 1.9.2 上使用遍历框架反复获得大约 900 毫秒:
I'm sorry you can't reproduce the results. However, on a MacBook Air (1.8 GHz i7, 4 GB RAM) with a 2 GB heap, GCR cache, but no warming of caches, and no other tuning, with a similarly sized dataset (1 million users, 50 friends per person), I repeatedly get approx 900 ms using the Traversal Framework on 1.9.2:
public class FriendOfAFriendDepth4
{
private static final TraversalDescription traversalDescription =
Traversal.description()
.depthFirst()
.uniqueness( Uniqueness.NODE_GLOBAL )
.relationships( withName( "FRIEND" ), Direction.OUTGOING )
.evaluator( new Evaluator()
{
@Override
public Evaluation evaluate( Path path )
{
if ( path.length() >= 4 )
{
return Evaluation.INCLUDE_AND_PRUNE;
}
return Evaluation.EXCLUDE_AND_CONTINUE;
}
} );
private final Index<Node> userIndex;
public FriendOfAFriendDepth4( GraphDatabaseService db )
{
this.userIndex = db.index().forNodes( "user" );
}
public Iterator<Path> getFriends( String name )
{
return traversalDescription.traverse(
userIndex.get( "name", name ).getSingle() )
.iterator();
}
public int countFriends( String name )
{
return count( traversalDescription.traverse(
userIndex.get( "name", name ).getSingle() )
.nodes().iterator() );
}
}
Cypher 速度较慢，但远没有您建议的那么慢:大约 3 秒:
Cypher is slower, but nowhere near as slow as you suggest: approx 3 seconds:
START person=node:user(name={name})
MATCH (person)-[:FRIEND]->()-[:FRIEND]->()-[:FRIEND]->()-[:FRIEND]->(friend)
RETURN count(friend)
亲切的问候
安
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