About Michael Hunger

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User Defined Functions in Neo4j 3.1.0-M10

on Oct 6, 2016 in apoc, cypher

Neo4j 3.1 brings some really neat improvements in Cypher alongside other cool features

I already demonstrated the – GraphQL inspired – map projections and pattern comprehensions in my last blog post.

User Defined Procedures

In the 3.0 release my personal favorite was user defined procedures which can be implemented using Neo4j’s Java API and called directly from Cypher.
You can tell, because I wrote about half of the 270 procedures for the APOC procedure collection “, with the remainder provided by other contributors.

Remember the syntax: …​ CALL namespace.procedure(arg1, arg2) YIELD col1, col2 AS alias …​

MATCH (from:Place {coords:{from}}), (to:Place {coords:{to}})

CALL apoc.algo.dijkstra(from, to, "ROAD", "cost") YIELD path, weight

RETURN nodes(path)
ORDER BY weight LIMIT 10;

Procedures improvements in 3.1.

As of 3.1, the named procedure parameters can now have default values.
This means you can leave them off during the call (from right to left), e.g.

@Name(value="costProperty", defaultValue="cost") String prop

The annotations for the database mode were folded into the @Procedure annotation.
You can also now set DBMS as mode, which encompasses Schema operations like creating indexes or constraints. @Procedure(value="namespace.procedure",mode=READ|WRITE|DBMS).

Based on the security work in Neo4j Enterprise, procedures can now get an additional set of roles configured in the allowed attribute of the @Procedure annotation, that also permit users with that role (or only that role) to execute the procedure.

The last change is dropping the support for result objects without columns, which we sometimes used for changing the cardinality of a query (between 0 and 1) for boolean operations.
But that’s handled now much better by boolean functions (predicates) as discussed below.

User Defined Functions

If you used or wrote procedures in the past, you most probably came across instances where it felt quite unwieldy to call a procedure just to compute something, convert a value or provide a boolean decision.

For example:

CREATE (v:Value {id:{id}, data:{data}})
CALL apoc.date.formatDefault(timestamp(), "ms") YIELD value as created
SET v.created = created

You’d rather write it as a function:

CREATE (v:Value {id:{id}, data:{data}, created: apoc.date.format(timestamp()) })

Now in 3.1 that’s possible, and you can also leave off the "ms" and use a single function name, because the unit and format parameters have a default value.

Functions are more limited than procedures: they can’t execute writes or schema operations and are expected to return a single value, not a stream of values.
But this makes it also easier to write and use them.

By having information about their types, the Cypher Compiler can also check for applicability.

The signature of the procedure above changed from:

public Stream<StringResult> formatDefault(@Name("time") long time, @Name("unit") String unit) {
   return Stream.of(format(time, unit, DEFAULT_FORMAT));

to the much simpler function signature (ignoring the parameter name and value annotations):

public String format(@Name("time") long time,
                     @Name(value="unit", defaultValue="ms") String unit,
                     @Name(value="format", defaultValue=DEFAULT_FORMAT) String format) {
   return getFormatter().format(time, unit, format);

This can then be called in the manner outlined above.

In our APOC procedure library we already converted about 50 procedures into functions from the following areas:

package # of functions example function

date & time conversion



number conversion



general type conversion



type information and checking



collection and map functions



JSON conversion



string functions



hash functions



You can list user defined functions with call dbms.functions()


We also started to add default values for parameters and deprecate procedures that required alternative names because of a wider parameter set.

We also moved the Description annotation from APOC’s own to the one now provided within Neo4j, so you’ll see the descriptions for all functions and procedures in dbms.procedures().

All of this is available now, if you run Neo4j 3.1.0-M10 and use this latest APOC release.

You can follow the development of APOC for Neo4j 3.1 in the 3.1 branch.


Neo4j 3.0 Stored Procedures

on Feb 29, 2016 in cypher, java

One of the many exciting features of Neo4j 3.0 are “Stored Procedures” that, unlike the existing Neo4j-Server extensions are directly callable from Cypher.

At the time of this writing it is only possible to call them in a stand-alone statement with CALL package.procedure(params)
but the plan is to make them a fully integrated part of Cypher statements.
Either [...]


Using XRebel 2 with Neo4j

on May 5, 2015 in neo4j

At Spring.IO in Barcelona I met my pal Oleg from ZeroTurnaround and we looked at how the new XRebel 2
integrates with Neo4j, especially with the remote access using the transactional Cypher http-endpoint.

As you probably know, Neo4j currently offers a remoting API based on HTTP requests (a new binary protocol is in development).

Our JDBC driver utilizes [...]


Neo4j Server Extension for Single Page Experiments

on Apr 24, 2015 in neo4j, server

Sometimes you have a nice dataset in Neo4j and you’d want to provide a self-contained way of quickly exposing it to the outside world without a multi-tier setup.

So for experiments and proofs of concepts it would be helpful to be able to extend Neo4j Browser to accomodate new types of frames and commands.
Unfortunately we’re not [...]


How To: Neo4j Data Import – Minimal Example

on Apr 18, 2015 in import, neo4j

We want to import data into Neo4j, there are too many resources with a lot of information which makes it confusing.
Here is the minimal thing you need to know.

Imagine the data coming from the export of a relational or legacy system, just plain CSV files without headers (this time).





Graph Model

Our graph Model would be very [...]


On Neo4j Indexes, Match & Merge

on Apr 11, 2015 in cypher, neo4j

We at Neo4j do our fair share to cause confusion of our users. I’m talking about indexes my friends.
My trusted colleagues Nigel Small – Index Confusion and Stefan Armbruster – Indexing an Overview already did a great job explaining the indexing situation in Neo4j,
I want to add a few more aspects here.

Since the release of [...]


Natural Language Analytics made simple and visual with Neo4j

on Jan 8, 2015 in cypher, fun

I was really impressed by this blog post on Summarizing Opinions with a Graph from Max and always waited for Part 2 to show up :)

The blog post explains an really interesting approach by Kavita Ganesan which uses a graph representation of sentences of review content to extract the most significant statements about a product.

Each [...]


Spring Data Neo4j 3.3.0 – Improving Remoting Performance

on Dec 9, 2014 in neo4j, spring-data-neo4j

With the first milestone of the Spring Data “Fowler” release train, Spring Data Neo4j 3.3.0.M1 was released. Besides a lot of smaller fixes, it contains one big improvement. I finally found some time to work on the remoting performance of the library, i.e. when used in conjunction with Neo4j Server. This blog post explains the [...]


The Story of GraphGen

on Nov 1, 2014 in community, development, neo4j

This is the story behind the really useful and ingenious Neo4j example graph data generator developed by Christophe Willemsen.

I don’t just want to show you the tool but also tell the story how it came to be.

First of all: The Neo4j Community is awesome.
There are so many enthusiastic and creative people, that it is often [...]



on Oct 18, 2014 in cypher, import, neo4j

pre { word-wrap: normal; white-space:pre; overflow-x:scroll; }

I have to admit that using our LOAD CSV facility is trickier than you and I would expect.
Several people ran into issues that they could not solve on their own.

My first blog post on LOAD CSV is still valid in it own right, and contains important aspects that I [...]

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