Token-based authentication is new in Neo4j 2.2, but how does it work?
The first thing to know is that it is enabled by default in conf/neo4j-server.properties by:
# Require (or disable the requirement of) auth to access Neo4j
Posted in How-to
Tagged neo4j, security
In my first job I was working for a company that developed a management information system for UK Police Forces; this system produced the statutory HMIC (Her Majesty’s Inspectorate of Constabulary) reports and allowed OLAP exploration of the datasets loaded into cubes from the data warehouse tables.
One of the areas that I implemented was the key performance indicators for Road Traffic Collisions, so I was intrigued to discover that the fuller, anonymised STATS19 dataset was now available on data.gov.uk. If you’re interested in the STATS19 form you can see it here.
This article provides a practical introduction to graph databases with a focus on the Groovy ecosystem. It explores Grails GORM support for Neo4j as well as query comparisons between the Neo4j Cypher language, SQL and the Gremlin graph DSL.
This article originally appeared in the May 2013 issue of GroovyMag.
Freemind is an Open Source mind mapping tool. Version 0.9 (released Feb 2011) introduced Groovy scripting that can be used for processing the mind map nodes. In this article we’ll look at a couple of use cases and the supporting scripts.
This article originally appeared in the February 2013 issue of GroovyMag
elasticsearch is an open source distributed RESTful search engine built on top of Apache Lucene.
Like any service or component in your architecture, you’ll want to monitor it to ensure that it’s available and gather performance data to help with tuning.
In this brief post, we’ll look at how we can monitor elasticsearch using Opsview, which is built on Nagios and thus has access to a wide range of plugins, yet provides a more approachable user interface for configuring service checks.
This is a quick how-to for Opsview users who need to monitor an OpenStack (Essex) Swift installation. As a starting point we’ll perform a ‘front door’ check as this should work no matter what Swift implementation you are using.
Apache Mahout is a scalable machine learning framework that can be used to create intelligent applications. In this article we’ll see how Mahout can be used to create personalised recommendations within a Grails application.
This article originally appeared in the February 2012 edition of GroovyMag.