I know that neo4j stores data structured in graphs rather than in tables. In RDBMS we will be having schemas of the tables but in neo4j we will not be having the tables. Only nodes, relations and properties are defined. So is there any concept of metadata in neo4j. Like is there any information stored about nodes, relationships in the database? If yes, how and what it stores in the metadata? Also where can we find the metadata related information in the graph database (location)
Thanks,
Neo4J doesn't directly store metadata in the way that you're looking for. The NeoProfiler tool was written precisely for this purpose. You can run it on a Neo4J database, and it will pull out as much information on labels, indexes, constraints, properties, nodes, and relationships as it can. The way that this works isn't too far off of the queries that #ulkas suggests in the other answer here, the output is just much better.
More broadly, in an RDBMS the schema information you pull out substantially constrains the database. The schema there is like a set of rules; you can't insert data unless it conforms to that schema. In Neo4J, because it's so flexible, even if there was a schema it would just be documentation of what's there, it would not be a set of constraints on what you can put in. At any time, you can insert new data that has nothing to do with the present schema (except that you can't violate things like uniqueness constraints).
If you want to see an equivalent schema for your database in neo4j, check out neoprofiler linked above. A few people out there have written about "metagraphs" - that is, they talk about representing a neo4j schema as a graph itself, where for example a node refers to a label. Relationships from that "label node" then go out to other kinds of label nodes, specifying what sorts of relationships can exist between nodes. For example, nodes labeled "Employee" may frequently have "works_for" relationships to nodes of label "Company".
no, direct metadata are not present. the maximum you can do is to query all the structure types and have a small inside what kind of graph could be stored in the db.
START r=rel(*)
RETURN type(r), count(*)
START n=node(*)
RETURN labels(n), count(*)
the specific database files are stored in the folder data/graph.db but besides some index and key files they are binary and not easy to read.
Meanwhile there is the official APOC Library.
This includes functions like apoc.meta.graph, apoc.meta.schema and others.
The link above describes the installation, if you run into sandbox errors, check the answers in this question
Related
How to ensure that all nodes of a label have some common properties ?
For example, I want to create a property "name" for all nodes of a label "Person", but I can make a mistake in writing of property name (namee ! for example)
There is no such mechanism built in Neo4j today (the current version of Neo4j at the time of writing is 2.1.6). What you are describing is some sort of schema (if you compare e.g. DDL for a RDBMS) and Neo4j is basically schema free. This type of structural integrity is quite often handled in the application layer for NoSQL databases.
The only schema operations that are available today for Neo4j are described here.
Currently they include:
Unique - e.g. CREATE CONSTRAINT ON (p:Person) ASSERT p.name IS UNIQUE
Indexes - create an index on a label e.g. CREATE INDEX ON :Person(name)
A comment on this answer from Michael Hunger who is part of team behind Neo4j indicates that more constraints will be available for Neo4j in the future. Furthermore, Michael points to the following alternatives:
Take a look at Structr, a layer above Neo4j that among other things enforces a stricter schema (check the schema docs here)
SylvaDB, an easy-to-use layer above Neo4j that also has schema support. Seems very
In addition to this, FrobberOfBits pointed to the tool NeoProfiler that contains a number of profilers, most of which run very simple Cypher queries against your database and provide summary statistics. Some profilers will actually discover data in your graph and then spawn other profilers which will run later. For example, if a label called "Person" is discovered in the data, a label profiler will be added to the run queue to inspect the population of nodes with that label.
We are working on a system where users can define their own nodes and connections, and can query them with arbitrary queries. A user can create a "branch" much like in SCM systems and later can merge back changes into the main graph.
Is it possible to create an efficient data model for that in Neo4j? What would be the best approach? Of course we don't want to duplicate all the graph data for every branch as we have several million nodes in the DB.
I have read Ian Robinson's excellent article on Time-Based Versioned Graphs and Tom Zeppenfeldt's alternative approach with Network versioning using relationnodes but unfortunately they are solving a different problem.
I Would love to know what you guys think, any thoughts appreciated.
I'm not sure what your experience level is. Any insight into that would be helpful.
It would be my guess that this system would rely heavily on tags on the nodes. maybe come up with 5-20 node types that are very broad, including the names and a few key properties. Then you could allow the users to select from those base categories and create their own spin-offs by adding tags.
Say you had your basic categories of (:Thing{Name:"",Place:""}) and (:Object{Category:"",Count:4})
Your users would have a drop-down or something with "Thing" and "Object". They'd select "Thing" for instance, and type a new label (Say "Cool"), values for "Name" and "Place", and add any custom properties (IsAwesome:True).
So now you've got a new node (:Thing:Cool{Name:"Rock",Place:"Here",IsAwesome:True}) Which allows you to query by broad categories or a users created categories. Hopefully this would keep each broad category to a proportional fraction of your overall node count.
Not sure if this is exactly what you're asking for. Good luck!
Hmm. While this isn't insane, think about the type of system you're replacing first. SQL. In SQL databases you wouldn't use branches because it's data storage. If you're trying to get data from multiple sources into one DB, I'd suggest exporting them all to CSV files and using a MERGE statement in cypher to bring them all into your DB at once.
This could manifest similar to branching by having each person run a script on their own copy of the DB when you merge that takes all the nodes and edges in their copy and puts them all into a CSV. IE
MATCH (n)-[:e]-(n2)
RETURN n,e,n2
Then comparing these CSV's as you pull them into your final DB to see what's already there from the other copies.
IMPORT CSV WITH HEADERS FROM "file:\\YourFile.CSV" AS file
MERGE (N:Node{Property1:file.Property1, Property2:file.Property2})
MERGE (N2:Node{Property1:file.Property1, Property2:file.Property2})
MERGE (N)-[E:Edge]-(N2)
This will work, as long as you're using node types that you already know about and each person isn't creating new data structures that you don't know about until the merge.
I have a relational database (about 30 tables) and I would like to transpose it in a neo4j graph database, and I don't know where to start...
Is there a general way to transpose tables and/or tuples into a graph model ? (relations properties, one or more graphs ?) What are the best sources of documentation ?
Thanks for any help,
Best regards
First, if at all possible, I'd suggest NOT using your relational DB as your "reference" for transposing to a graph model. All too often, mistakes and pitfalls from relational modelling get transferred over to the graph model and introduce other oddities. In fact, if you have a source ER diagram, that might be an even better starting point as it's really already a graph. And maybe even consider a re-modelling exercise for your domain!
That said, from a basic point of view, you can think of most tables as representing a node type (e.g. "User" or "Movie") with join tables and keys representing relationship types.
A great starting point, from my perspective anyway, is to determine some questions your graph/data source should answer. Write those questions down, and try to come up with Cypher queries that represent the questions. Often times, a graph model naturally arises from such an effort, and it's really not that difficult.
If you haven't already, I'd strongly recommend picking up a (free) copy of the Graph Databases ebook from here: http://graphdatabases.com/
It's jam-packed with a lot of good info on where to start with modelling your domain and even things to consider when you're used to doing things in a relational manner. It also contains some material on Cypher, although the Neo4j site (neo4j.org) has a reference manual with plenty of up-to-date info on Cypher.
Hope this helps!
There's not going to be a one-stop-shop for this kind of conversion, as not all data models are appropriate for graph modeling, and every application is a unique special snowflake...but with that said.....
Generally, your 'base' tables (e.g. User, Role, Order, Product) would become nodes, and your 'join tables' (a.k.a. buster tables) would be candidates for your relationships (e.g. UserRole, OrderLineItem). The key thing to remember that in a graph, generally, you can only have one relationship of a given type between two specific nodes - so in the above example, if your system allows the same product to be in an order twice - it would cause issues.
Foreign keys are your second source of relationships, look to them to see if it makes sense to be a relationship or just a property.
Just keep in mind what you are trying to solve by your data model - if it's traversing your objects to find relationships and distance, etc... then graphs may be a good fit. If you are modeling an eCommerce app, where you are dealing with manipulating a single nested object (e.g. order -> line item -> product -> sku), then a relational model may be the right fit.
Hope my $0.02 helps...
As has been already said, there is no magical transformation from a relational database model to a graph database model.
You should look for the original entities and how they are related in order to find your nodes, properties and relations. And always keeping in mind what type of queries you are going to perform.
As BtySgtMajor said, "Graph Databases" is a good book to start, and it is free.
Can u please share any links/sample source code for generating the graph using neo4j from Oracle database tables data .
And my use case is oracle schema table names as Nodes and columns are properties. And also need to genetate graph in tree structure.
Make sure you commit the transaction after creating the nodes with tx.success(), tx.finish().
If you still don't see the nodes, please post your code and/or any exceptions.
Use JDBC to extract your oracle db data. Then use the Java API to build the corresponding nodes :
GraphDatabaseService db;
try(Transaction tx = db.beginTx()){
Node datanode = db.createNode(Labels.TABLENAME);
datanode.setProperty("column name", "column value"); //do this for each column.
tx.success();
}
Also remember to scale your transactions. I tend to use around 1500 creates per transaction and it works fine for me, but you might have to play with it a little bit.
Just do a SELECT * FROM table LIMIT 1000 OFFSET X*1000 with X being the value for how many times you've run the query before. Then keep those 1000 records stored somewhere in a collection or something so you can build your nodes with them. Repeat this until you've handled every record in your database.
Not sure what you mean with "And also need to genetate graph in tree structure.", if you mean you'd like to convert foreign keys into relationships, remember to just index the key and in stead of adding the FK as a property, create a relationship to the original node in stead. You can find it by doing an index lookup. Or you could just create your own little in-memory index with a HashMap. But since you're already storing 1000 sql records in-memory, plus you are building the transaction... you need to be a bit careful with your memory depending on your JVM settings.
You need to code this ETL process yourself. Follow the below
Write your first Neo4j example by following this article.
Understand how to model with graphs.
There are multiple ways of talking to Neo4j using Java. Choose the one that suits your needs.
I am playing around with Neo4j but trying to get my head around the graph concepts. As a learning process I want to port a small Postgres relational database schema to Neo4j. Is there any way I can port it and issues "equivalent" relational queries to Neo4j?
Yes, you can port your existing schema to a graph database. Keep in mind that this is not necessarily the best model for your data, but it is a starting point.
How easy it is depends a lot on the quality of your existing schema.
The tables corresponding to entities in an entity-relationship-diagram define your types of nodes. In the upcoming neo4j 2.0, you can labels them with the name of the entity to make a lookup easier. In older versions you can use an index or a manual label property.
Assuming a best case, where all your relationships between data is modelled using foreign keys, any 1:1 relationship between nodes can be identified and ported next.
For tables modelling n:m relationships, identify the corresponding nodes and add a direct relationship between them.
So as an example assume tables Author[id, name, publisher foreign key], Publisher[id, name] and Book[id, title] and written_by[author foreign key, book foreign key].
Every row in Author, Publisher and Book becomes a node.
Every Author node gets a relationship to the publisher identified by the foreign key relationship.
For every row in written_by you add a relationship between the Author node and Book node referenced
For queries in neo4j I recommend cypher due to its expressiveness. A (2.0) query looking for books by some author would look like:
MATCH (author:Author)-[:written_by]-(book:Book)
WHERE author.name='Hugh Laurie'
RETURN book.title
You actually have several options at hand:
use the Talend connector for Neo4J
export your schema+data in CSV files consumable by the batch importer
or you can do it programmatically
I'm afraid not. The relational data model and the graph data model are two different ways of modelling a real-world domain. It requires a human brain (at least as of 2013) to understand the domain in order to model it.
I suggest that you take a piece of paper and capture, using circles and arrows, what your entities are (nodes) and how they relate to each other (relationships). Then, have a look at that piece of paper. Voila, your new Neo4j data model.
Then, take a query that you want to be answered and try to figure out how you would do that without a computer, just by tracing your nodes and relationships with a finger on that piece of paper. Once you've figured that out, translate what you've done to a Cypher query.
Have a look at neo4j.org, there are plenty of examples.
Check this out:
The musicbrainz -> neo4j
https://github.com/redapple/sql2graph/tree/master/examples/musicbrainz
Neo4j Sql-importer
https://github.com/peterneubauer/sql-import
Good Luck!
This tool does exactly that.
Import any relational db into neo4j
https://github.com/jexp/neo4j-rdbms-import