I have two nodes in neo4j say:
Node start = // set to some node;
Node end = // set to some other node;
And, I want to find if there is an edge between them that have the attribute key, "name" with val = "bubba".
What is the most efficient way to do this?
Thanks.
Notes:
Do not use Gremlin
Do not use Cypher
Use only Java API
Assuming you haven't got those relationship indexed in a manual index, just figure out which of the two nodes has got the least relationships of the type(s) you're looking for and iterate over those to see if the node on the other side of that relationship is the expected one and the relationship has got that property (check in that order since "other node" check is cheaper than property lookup).
Related
Setup:
Neo4j and Cypher version 2.2.0.
I'm querying Neo4j as an in-memory instance in Eclipse created TestGraphDatabaseFactory().newImpermanentDatabase();.
I'm using this approach as it seems faster than the embedded version and I assume it has the same functionality.
My graph database is randomly generated programmatically with varying numbers of nodes.
Background:
I generate cypher queries automatically. These queries are used to try and identify a single 'target' node. I can limit the possible matches of the queries by using known 'node' properties. I only use a 'name' property in this case. If there is a known name for a node, I can use it to find the node id and use this in the start clause. As well as known names, I also know (for some nodes) if there are names known not to belong to a node. I specify this in the where clause.
The sorts of queries that I am running look like this...
START
nvari = node(5)
MATCH
(target:C5)-[:IN_LOCATION]->(nvara:LOCATION),
(nvara:LOCATION)-[:CONNECTED]->(nvarb:LOCATION),
(nvara:LOCATION)-[:CONNECTED]->(nvarc:LOCATION),
(nvard:LOCATION)-[:CONNECTED]->(nvarc:LOCATION),
(nvard:LOCATION)-[:CONNECTED]->(nvare:LOCATION),
(nvare:LOCATION)-[:CONNECTED]->(nvarf:LOCATION),
(nvarg:LOCATION)-[:CONNECTED]->(nvarf:LOCATION),
(nvarg:LOCATION)-[:CONNECTED]->(nvarh:LOCATION),
(nvari:C4)-[:IN_LOCATION]->(nvarg:LOCATION),
(nvarj:C2)-[:IN_LOCATION]->(nvarg:LOCATION),
(nvare:LOCATION)-[:CONNECTED]->(nvark:LOCATION),
(nvarm:C3)-[:IN_LOCATION]->(nvarg:LOCATION),
WHERE
NOT(nvarj.Name IN ['nf']) AND NOT(nvarm.Name IN ['nb','nj'])
RETURN DISTINCT target
Another way to think about this (if it helps), is that this is an isomorphism testing problem where we have some information about how nodes in a query and target graph correspond to each other based on restrictions on labels.
Question:
With regards to optimisation:
Would it help to include relation variables in the match clause? I took them out because the node variables are sufficient to distinguish between relationships but this might slow it down?
Should I restructure the match clause to have match/where couples including the where clauses from my previous example first? My expectation is that they can limit possible bindings early on. For example...
START
nvari = node(5)
MATCH
(nvarj:C2)-[:IN_LOCATION]->(nvarg:LOCATION)
WHERE NOT(nvarj.Name IN ['nf'])
MATCH
(nvarm:C3)-[:IN_LOCATION]->(nvarg:LOCATION)
WHERE NOT(nvarm.Name IN ['nb','nj'])
MATCH
(target:C5)-[:IN_LOCATION]->(nvara:LOCATION),
(nvara:LOCATION)-[:CONNECTED]->(nvarb:LOCATION),
(nvara:LOCATION)-[:CONNECTED]->(nvarc:LOCATION),
(nvard:LOCATION)-[:CONNECTED]->(nvarc:LOCATION),
(nvard:LOCATION)-[:CONNECTED]->(nvare:LOCATION),
(nvare:LOCATION)-[:CONNECTED]->(nvarf:LOCATION),
(nvarg:LOCATION)-[:CONNECTED]->(nvarf:LOCATION),
(nvarg:LOCATION)-[:CONNECTED]->(nvarh:LOCATION),
(nvare:LOCATION)-[:CONNECTED]->(nvark:LOCATION)
RETURN DISTINCT target
On the side:
(Less important but still an interest) If I make each relationship in a match clause an optional match except for relationships containing the target node, would cypher essentially be finding a maximum common sub-graph between the query and the graph data base with the constraint that the MCS contains the target node?
Thanks a lot in advance! I hope I have made my requirements clear but I appreciate that this is not a typical use-case for Neo4j.
I think querying with node properties is almost always preferable to using relationship properties (if you had a choice), as that opens up the possibility that indexing can help speed up the query.
As an aside, I would avoid using the IN operator if the collection of possible values only has a single element. For example, this snippet: NOT(nvarj.Name IN ['nf']), should be (nvarj.Name <> 'nf'). The current versions of Cypher might not use an index for the IN operator.
Restructuring a query to eliminate undesirable bindings earlier is exactly what you should be doing.
First of all, you would need to keep using MATCH for at least the first relationship in your query (which binds target), or else your result would contain a lot of null rows -- not very useful.
But, thinking clearly about this, if all the other relationships were placed in separate OPTIONAl MATCH clauses, you'd be essentially saying that you want a match even if none of the optional matches succeeded. Therefore, the logical equivalent would be:
MATCH (target:C5)-[:IN_LOCATION]->(nvara:LOCATION)
RETURN DISTINCT target
I don't think this is a useful result.
I need to find the N nodes "nearest" to a given node in a graph, meaning the ones with least combined weight of relationships along the path from given node.
Is is possible to do so with a pure Cypher only solution? I was looking about path functions but couldn't find a viable way to express my query.
Moreover, is it possible to assign a default weight to a relationship at query time, according to its type/label (or somehow else map the relationship type to the weight)? The idea is to experiment with different weights without having to change a property for every relationship.
Otherwise I would have to change the weight property's value to each relationship and re-do it to before each query, which is very time-consuming (my graph has around 10M relationships).
Again, a pure Cypher solution would be the best, or please point me in the right direction.
Please use variable length Cypher queries to find the nearest nodes from a single node.
MATCH (n:Start { id: 0 }),
(n)-[:CONNECTED*0..2]-(x)
RETURN x
Note that the syntax [CONNECTED*0..2] is a range parameter specifying the min and max relationship distance from a given node, with relationship type CONNECTED.
You can swap this relationship type for other types.
In the case you wanted to traverse variably from the start node to surrounding nodes but constrain via a stop criteria to a threshold, that is a bit more difficult. For these kinds of things it is useful to get acquainted with Neo4j's spatial plugin. A good starting point to learn more about Neo4j spatial can be found in this blog post: http://neo4j.com/blog/neo4j-spatial-part1-finding-things-close-to-other-things
The post is a little outdated but if you do some Google searching you can find more updated materials.
GitHub repository: https://github.com/neo4j-contrib/spatial
I'm very new in using Neo4j and have a question regarding the computation of intersections of nodes.
Let's suppose, I have the three properties A,B,C and I want to select only the nodes that have all three properties.
I created an index for the properties and thus, I can get all nodes having one of the properties. However, afterwards I have to merge the IndexHits. Is there a way to select directly all nodes having the three properties?
My second idea was to create a node for each property and connect other nodes by relationships. I can then iterate over all relationships and get for each property a list of nodes which are connected. But again, I have to compute the intersection afterwards.
Is there a function I miss here, since I suppose it's a standard problem.
Thanks a lot,
Benny
Do you also have the values you look for? You would start with the property that limits the amount of found nodes most.
MATCH (a:Label {property1:{value1}})
WHERE a.property2 = {value2} AND a.property3 = {value3}
RETURN a
For the Java API and lucene indexes:
gdb.index().forNodes("foo").query("p1:value1 p2:value2 p3:value3")
Lucene query syntax
I have a Neo4J database mapped with COMPANY as nodes and RELATED as edges. COMPANY has a CODE property. I want to query the database and get the first node that matches the regexp COMPANY.CODE =~ '12345678.*', i.e., a COMPANY whose first 8 letters of CODE is equal a given string literal.
After several attempts, the best I could come up with was the following query:
START p=node(*) where p.CODE =~ '12345678.*' RETURN p;
The result is the following exception:
org.neo4j.cypher.EntityNotFoundException:
The property 'CODE' does not exist on Node[0]
It looks like Node[0] is a special kind of node in the database, that obviously doesn't have my CODE property. So, my query is failing because I'm not choosing the appropriate type of node to query upon. But I couldn't figure out how to specify the type of node to query on.
What's the query that returns what I want?
I think I need an index on CODE to run this query, but I'd like to know whether there's a query that can do the job without using such an index.
Note: I'm using Neo4J version 1.9.2. Should I upgrade to 2.0?
You can avoid the exception by checking for the existence of the property,
START p=node(*)
WHERE HAS(p.CODE) AND p.CODE =~ '12345678.*'
RETURN p;
You don't need an index for the query to work, but an index may increase performance. If you don't want indices there are several other options. If you keep working with Neo4j 1.9.x you may group all nodes representing companies under one or more sorting nodes. When you query for company nodes you can then retrieve them from their sorting node and filter on their properties. You can partition your graph by grouping companies with a certain range of values for .code under one sorting node, and a different range under another; and you can extend this partitioning as needed if your graph grows.
If you upgrade to 2.0 (note: not released yet, so not suitable for production) you can benefit from labels. You can then assign a Company label to all those nodes and this label can maintain it's own index and uniqueness constraints.
The zero node, called 'reference node', will not remain in future versions of Neo4j.
I am using Neo4j 1.8.2 with Neo4j Spatial 0.9 for 1.8.2 (http://m2.neo4j.org/content/repositories/releases/org/neo4j/neo4j-spatial/0.9-neo4j-1.8.2/)
Followed the example code from here http://architects.dzone.com/articles/neo4jcypher-finding-football with one change- instead of SpatialIndexProvider.SIMPLE_WKT_CONFIG, I used SpatialIndexProvider.SIMPLE_POINT_CONFIG_WKT
Everything works fine until you execute the following query:
START n=node:stadiumsLocation('withinDistance:[53.489271,-2.246704, 5.0]')
RETURN n.name, n.wkt;
n.name is null. When I explored the graph, I found this data:
Node[80]{lon:-2.20024,lat:53.483,id:79,gtype:1,bbox:-2.20024,53.483,-2.20024,53.483]}
Node[168]{lon:-2.29139,lat:53.4631,id:167,gtype:1,bbox:-2.29139,53.4631,-2.29139,53.4631]}
For Node 80 returned, it looks like this is the node created for the spatial record, which contains a property id:79. Node 79 is the actual stadium record from the example.
As per the source of IndexProviderTest, the comments
//We not longer need this as the node we get back already a 'Real' node
// Node node = db.getNodeById( (Long) spatialRecord.getProperty( "id" ) );
seem to indicate that this feature isn't available in the version I am using.
My question is, what is the recommended way to use withinDistance with other match conditions? There are a couple of other conditions to be fulfilled but I can't seem to get a handle on the actual node to actually match them.
Should I explicitly create relations? Not use Cypher and use the core API to do a traversal? Split the queries?
Two options:
a) Use GeoPipline.startNearestNeighborLatLonSearch to get a starting set of nodes, supply to subsequent Cypher query to do matching/filtering on other properties
b) Since my lat/longs are common across many entities [using centroid of an area], I can create a relation from the spatial node to all entities that are located in that area and then use one Cypher query such as:
START n=node:stadiumsLocation('withinDistance:[53.489271,-2.246704, 5.0]')
MATCH (n)<-[:LOCATED_IN]-(something)
WHERE something.someProp=5
RETURN something
As advised by Peter, went with option b.
Note though, there is no way to get the spatially indexed node back so that you can create relations from it. Had to do a withinDistance query for 0.0 distance.
can you execute the enhanced testcase I did at https://github.com/neo4j/spatial/blob/2803093d544f56d7dfe8f1d122e049fa73489d8a/src/test/java/org/neo4j/gis/spatial/IndexProviderTest.java#L199 ? It shows how to find a location, and traverse with cypher to the next node.