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.
这是无法在图形数据库和动作书籍中复制/验证性能声明的后续操作。我已经更新了设置和测试，不想对原来的问题做太多修改。
The whole story (including scripts etc) is on https://baach.de/Members/jhb/neo4j-performance-compared-to-mysql
整个故事(包括脚本等)是在https://baach.de/members/jhb/neo4j -performance- comparedto mysql
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):
短版本:在尝试验证“图形数据库”书中的性能声明时，我得到了以下结果(查询一个包含n个人的随机数据集，每个人有50个朋友):
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
"*": single run only
“*”:单只运行
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
"*": single run only
“*”:单只运行
Using 1.9.2 on a 64bit ubuntu I have setup neo4j.properties with these values:
我在64位ubuntu上使用1.9.2安装了neo4j。与这些值属性:
neostore.nodestore.db.mapped_memory=250M
neostore.relationshipstore.db.mapped_memory=2048M
and neo4j-wrapper.conf with:
和neo4j-wrapper。配置:
wrapper.java.initmemory=1024
wrapper.java.maxmemory=8192
My query to neo4j looks like this (using the REST api):
我对neo4j的查询如下(使用REST api):
start person=node:node_auto_index(noscenda_name="person123") match (person)-[:friend]->()-[:friend]->(friend) return count(distinct friend);
Node_auto_index is in place, obviously
显然，Node_auto_index已经就位。
Is there anything I can do to speed neo4j up (to be faster then mysql)?
我能做些什么来加快neo4j的速度(加快mysql的速度)吗?
And also there is another benchmark in * with same problem.
在*中还有一个基准测试也有同样的问题。
2 个解决方案
#1
4
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:
很抱歉你不能重现结果。然而,MacBook Air(1.8 GHz i7,4 GB RAM)2 GB堆,GCR缓存,缓存但是没有变暖,和没有其他调优,与一个同样大小的数据集(100万用户,每人50位朋友),我多次获得大约900毫秒1.9.2使用遍历框架:
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 is slower, but nowhere near as slow as you suggest: approx 3 seconds:
Cypher较慢，但远不及你建议的慢:约3秒:
START person=node:user(name={name})
MATCH (person)-[:FRIEND]->()-[:FRIEND]->()-[:FRIEND]->()-[:FRIEND]->(friend)
RETURN count(friend)
Kind regards
亲切的问候
ian
伊恩
#2
3
Yes, I believe the REST API is significantly slower than the regular bindings and therein lies your performance problem.
是的，我认为REST API要比常规绑定慢得多，这就是性能问题所在。
#1
4
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:
很抱歉你不能重现结果。然而,MacBook Air(1.8 GHz i7,4 GB RAM)2 GB堆,GCR缓存,缓存但是没有变暖,和没有其他调优,与一个同样大小的数据集(100万用户,每人50位朋友),我多次获得大约900毫秒1.9.2使用遍历框架:
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 is slower, but nowhere near as slow as you suggest: approx 3 seconds:
Cypher较慢，但远不及你建议的慢:约3秒:
START person=node:user(name={name})
MATCH (person)-[:FRIEND]->()-[:FRIEND]->()-[:FRIEND]->()-[:FRIEND]->(friend)
RETURN count(friend)
Kind regards
亲切的问候
ian
伊恩
#2
3
Yes, I believe the REST API is significantly slower than the regular bindings and therein lies your performance problem.
是的，我认为REST API要比常规绑定慢得多，这就是性能问题所在。