Another Word For It Patrick Durusau on Topic Maps and Semantic Diversity

Cypher basics: Matching Traversal Patterns with MATCH by Wes Freeman.

From the post:

“Because friends don’t let friends write atrocious recursive joins in SQL.” –Max De Marzi

The match clause is one of the first things you learn with Cypher. Once you’ve figured out how to look up your starting bound identifiers with start, you usually (but not always) want to match a traversal pattern, which is one of Cypher’s most compelling features.

The goal of this post is not to go over the syntax for all of the different cases in match–for that the docs do a good job: Cypher MATCH docs. Rather, I hoped to explain more the how of how match works.

First, you need to understand the difference between bound and unbound identifiers (sometimes we call them variables, too, in case I slip up and forget to be consistent). Bound identifiers are the ones that you know the value(s) of–usually you set these in the start clause, but sometimes they’re passed through with with. Unbound identifiers are the ones you don’t know the values of: the part of the pattern you’re matching. If you don’t specify an identifier, and instead just do a-->(), or something of that sort, an implicit unbound identifier is created for you behind the scenes, so Cypher can keep track of the values it’s found. The goal of the match clause is to find real nodes and relationships that match the pattern specified (find the unbound identifiers), based on the bound identifiers you have from the start.

Wes is creating enough of these mini-tutorials that you will find his Cypher page, a welcome collection point.

Cypher basics: it all starts with the START by Wes Freeman.

From the post:

“It all starts with the START” -Michael Hunger, Cypher webinar, Sep 2012

The start clause is one of those things that seems quite simple initially. You specify your start point(s) for the rest of the query. Typically, you use an index lookup, or if you’re just messing around, a node id (or list of node ids). This sets the stage for you to match a traversal pattern, or just filter your nodes with a where. Let’s start with a simple example–here we’re going to find a single node, and return it (later we’ll get into why start is sort of like a SQL from):

Wes continues his excellent introduction to Cypher.

Cypher for SQL Professionals by Michael Hunger. (video)

From the webpage:

Cypher is a graph query language used in Neo4j. Much like SQL, it’s a declarative language used for querying databases.

What does a join look like in Cypher? What about an left outer join? There are a lot of similarities between the two, Cypher is heavily influenced by SQL. We’ll talk about what these common concepts and differences are, what Cypher gives you that SQL leaves you wanting. Come along and see how Neo4j and Cypher can make your daily grind much easier and more fun.

You’ll learn how to use your current SQL knowledge to quickly get started using Neo4j and Cypher.

Just in case you get to pick the video for this weekend. 😉

This is work friendly so you might better save it for a lunch break next week.

Neo4j 1.9.M05 released – wrapping up by Peter Neubauer.

From the post:

We are very proud to announce the next milestone of the Neo4j 1.9 release cycle. This time, we have been trying to introduce as few big changes as possible and instead concentrate on things that make the production environment a more pleasant experience. That means Monitoring, Cypher profiling, Java7 and High Availability were the targets for this work.

Everyone likes improvements, new features, etc.

I am leaning towards profiling cypher statements as my favorite in this release.

What’s yours?

Neo4j 1.8.1 – Stability and (Cypher) Performance by Michael Hunger.

A maintenance release for the Neo4j 1.8.* line.

Michael writes:

In particular, Cypher has been extended with support for the new Bidirectional Traverser Framework, meaning query times are in some cases cut down to a third of what they used to be. Also, Andres spent time optimizing memory consumption, so you can run more and larger Cypher queries faster than ever before!

We got started on extending JVM and Java version support by eliminating compilation issues for Java 7 on both Oracle JVM and OpenJDK – a good first step. We still have some way to go, notably rigorous testing as part of our continuous integration pipeline, and community feedback – this is where you come in. We have had some confusion over this, so we have now inserted checks and warnings that state clearly: we currently only support JDK 6.

For our enterprise customers we have added a new consistency checker that both runs faster and catches more problems, to ensure your backups are always in a good state. And we straightened out some behaviours in our HA protocol around cluster formation that were confusing.

Neo4j 1.8.1 (download)

Neo4j 1.9.M01 – Self-managed HA by Peter Neubauer.

Welcome everyone to the first Milestone of the Neo4j 1.9 releases! In this release we’re presenting our new HA solution and a set of excellent improvements to our query language, Cypher.

Peter hits the highlights of the first milestone release for Neo4j 1.9.

I suggest you grab the software first and read Peter’s summary while you “play along.” 😉

Cheat Sheet: Cypher Query Language for Graph Databases

Cypher is the declarative query language for the Neo4j graph database. Download this cheat sheet to get quickly up to speed on querying graphs and to learn how Cypher:

• Matches patterns of nodes and relationship in the graph, to extract information or modify the data.
• Has the concept of identifiers which denote named, bound elements and parameters.
• Can mutate graph data by creating, updating, and removing nodes, relationships, and properties.

A very good “cheat sheet.”

Up to you to decide if giving up your phone number is worth it for a free cheat sheet.

People get pissed off over passive tracking.

How will they react to overreaching marketing departments collecting phone numbers and addresses?

Something to keep in mind when designing your marketing efforts.

Newsfeed feature powered by Neo4j Graph Database

From the post:

Implementation of newsfeed or timeline feature became a must requirement for every social application. Achieving the same result through traditional relational databases would have been cumbersome as well as inefficient due to number of joins in SQL query. Would post an another article on why graph databases especially NEO4J is an apt choice for social application. For now, this post would directly jump into the implementation of simple newsfeed feature using powerful graph database NEO4J. (This article assumes that reader already understands basic concepts of graph databases representation, Neo4j and Cypher query language).

Neo4j Documentation has already given us the data model to represent social network in graph database and queries to retrieve data. Instead of repeating the whole story, this post would compliment the existing doc by giving cypher queries to create and retrieve data for below data model.

Would be Facebook killers will appreciate the example but tying Neo4j to a standard news feed would be more useful.

Neo4j 1.8 Release – Fluent Graph Literacy by Andreas Kollegger.

From the post:

Available immediately, Neo4j 1.8 offers a delightful experience for reading and writing graph data with the simple expressiveness of the Cypher language. Whether you’re just discovering the social power of Facebook’s Open Graph or are building your own Knowledge Graph for Master Data Management, speaking in graph is easy with Cypher. It is the key to making sense of data with Neo4j.

Another major milestone in Neo4j development!

Cypher Query Language and Neo4j (Registration page)

Thursday, Sept 27, 2012
10:00 PDT // 19:00 CEST

From the description:

The Neo4j graph database is all about relationships. It allows to model domains of connected data easily. Querying using a imperative API is cumbersome and bloated. So the Neo Technology team decided to develop a query language more suited to query graph data. Join us to learn the journey of its inception to a being usable tool.

Curious, has anyone compared Cypher to other graph query languages?

Neo4j 1.8.RC1 – Really Careful #ftw

From the post:

As we prepare the Neo4j 1.8 series for General Availability, we’re moving to an RC model of finalizing production ready software. RC of course stands for Really Careful.

Resisting Changes

Every line of code that is committed to github is greeted with exhaustive continuous testing, earning the developer either a deep-fried twinkie or pickled herring – the reward/punishment is flipped depending on the resident country.

For milestone releases, great care is used to QA the packaged artifacts. Download, install, start/stop, go through the motions of normal use, throw sample applications against it, compare benchmarks, try out language bindings. Yet, we haven’t been entirely comfortable going directly from a milestone to general availability, because the milestone often will have introduced new features and possible breaking changes.

Now, we’re adopting a formal Release Candidate strategy: a feature complete release built from a frozen code base which will only accept bug fixes. An RC could be the GA, but introduces a longer public review before getting the final stamp of approval.

Do you have your copy yet?

Neo4j-[:LOVES]->Cypher

Followup to Michael Hunger’s presentation (30 August 2012) on Neo4j and Cypher.

Slides and video have been posted, plus answers to posted questions.

Neo4j 1.8.M07 – Sharing is Caring

Neo4j 1.8.M07 announcement with a couple of the highlights.

Available immediately, Neo4j 1.8 Milestone 7 sets the stage for responsible data sharing. We’re open source. Naturally we’re mindful about supporting…

Open (Meta) Data

Way back when Neo4j 1.2.M01 was released we introduced the Usage Data Collector (UDC), an optional component which would help us understand how running instance of Neo4j were being used, by reporting back anonymous context information: operating system, runtime, region of the Earth, that kind of thing.

Of course, the source code for the UDC is open and available for inspection. Now, we’re taking some steps to make the meta-data itself available, to make that data useful for everyone in the community, and to do so while being uber sensitive to the slightest hint of privacy concerns.

We’re kinda excited about this, actually. Stay tuned to learn more about what we’re doing, how you can be involved, and how it will be awesome for the community.

Create Unique Data

Earlier in the 1.8 branch, we introduced the RELATE clause, a powerful blend of MATCH and CREATE. With it, you could insist that a pattern of data should exist in the graph, and RELATE would perform the least creations required to uniquely satisfy the pattern.

In discussion, we kept saying things like “uniquely creates” to describe it, finally realizing that we should name the thing with the much more obvious CREATE UNIQUE.

Don’t be the last one on your block to have the latest Neo4j release!

Neo4j 1.7.M02 – Cache Cachet, Matching Matchers, and Debian Debs by Peter Neubauer.

Just the highlights to temp you into reading the full post:

Neo4j 1.7 Milestone 2 introduces a trio of interesting advances: a new cache scheme, targeted pattern matching in Cypher, and Debian install packages. Faster, smarter, and more accessible.

Atomic Array Cache – GC resistant, 10x faster, 10x more capacity

Under the hood, Neo4j runs on the JVM (that’s the ‘J’ in ‘Neo4j’). And as every java developer knows: the Garbage Collector is your friend, the Garbage Collector is your enemy. The Garbage Collector (GC) helpfully relieves the developer from worrying about memory management. Unhelpfully, garbage collection introduces unpredictability in an application’s responsiveness. While partial garbage collection can be a nuisance, full garbage collection can be disastrous, pausing an application for uncomfortably long durations (from a few to far too many seconds). Sadly, there are no really good solutions to consistently avoid full GC pauses or to even prevent the GC from kicking in at inconvenient times.

….

Cypher matching matchers

By describing what you want and leaving the how-to-do-it up to someone else, a declarative language like Cypher presents many opportunities for optimizations. Our brilliant Michael Hunger recently joined Cypher master Andres Taylor for a hard look at pattern matching, initiating a classification of common use cases. Then the duo targeted different pattern matcher implementations to fit each type of query. The results are promising.

….

Got Debian? apt-get neo4j

Ops people rejoice, because Neo4j is now a simple `apt-get` away for any Debian-based Linux distro (like the ever popular Ubuntu). The debian installer is now part of the regular build and deploy chain, pushing out to our own debian repository. See http://debian.neo4j.org/ for details, following these steps to install:

….

Download Neo4j 1.7.M02 today!

Cypher Query Language

Slides by Max De Marzi at Chicago Graph Database Meet-up.

Great set of slides.

Illustrates the syntax and its “ascii art” perspective before moving into more complex queries.

Saw this first at Alex Popescu’s myNoSQL.