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Gremlin · tinkerpop/gremlin Wiki

Gremlin · tinkerpop/gremlin Wiki
Related:  Graph DBsGraph theory, graph practice

Blueprints · tinkerpop/blueprints Wiki Gephi, an open source graph visualization and manipulation software JDBC access with distributed ruby : Ewout blogt. JDBC, java database connectivity, is the standard database driver interface on the java platform. Since java is ubiquitous, most database vendors provide JDBC drivers to access their data. When a ruby application requires using a legacy data source, sometimes the only option is going through JDBC. The database toolkit Sequel can use JDBC data sources, but only when running on JRuby. Fortunately, distributed ruby exists. Both server-side and client-side code is pretty straightforward. # server side require 'drb' require 'java' require 'rubygems' require 'sequel' DRb.start_service ' Sequel # It might be needed to instantiate the driver here, # so it is available when a connection string is given. NativeException Inside the JDBC driver, native java exceptions can be raised. DRb::DRbUnknownError: NativeException To fix this and get a full stack trace of NativeExceptions, the class needs to be defined in the client. class ::NativeException < RuntimeError ; end

TinkerPop Social network analysis software Social network analysis software (SNA software) is software which facilitates quantitative or qualitative analysis of social networks, by describing features of a network either through numerical or visual representation. Overview[edit] Some SNA software can perform predictive analysis.[5] This includes using network phenomena such as a tie to predict individual level outcomes (often called peer influence or contagion modeling), using individual-level phenomena to predict network outcomes such as the formation of a tie/edge (often called homophily models[6]) or particular type of triad, or using network phenomena to predict other network phenomena, such as using a triad formation at time 0 to predict tie formation at time 1. Network analysis software generally consists of either packages based on graphical user interfaces (GUIs), or packages built for scripting/programming languages. Interactive Data Visualization technology often includes social network analysis capabilities. Notes

rubyrep: Home The Apache Cassandra Project Home Building a Twitter Filter With CherryPy, Redis, and tweetstream Background all the code is available at Since reading this post by Simon Willison I've been interested in Redis and have been following its development. After having a quick play around with Redis I've been looking for a project to work on that uses Redis as a data store. Tools tweetstream - provides the interface to the Twitter Streaming APICherryPy - used for handling the web app side, no need for an ORMJinja2 - HTML templatingjQuery - for doing the AJAXy stuff and visual effectsredis-py - Python client for RedisRedis - the "database", look here for the documenation on how to install it Retrieving tweets The first thing we need to is retrieve tweets from the Twitter Streaming API. Here is the code for the, which when executed as a script from the command-line will start streaming tweets from Twitter that contain the words "why", "how", "when", "lol", "feeling" and the tweet must end in a question mark. Web App Thats it.

HBase - Apache HBase™ Home Home - GitHub Pipes is a dataflow framework using process graphs. A process graph is composed of Pipe vertices connected by communication edges. A Pipe implements a simple computational step that can be composed with other Pipe objects to create a larger computation. There are numerous Pipe classes that come with the main Pipes distribution. Please join the Gremlin users group at for all TinkerPop related discussions. Pipes JavaDoc: 2.5.0 – 2.4.0 – 2.3.0 – 2.2.0 – 2.1.0 – 2.0.0 – 1.0 – 0.9 – 0.8 – 0.7 – 0.6 – 0.5 – 0.4 – 0.3 – 0.2 – 0.1 Pipes WikiDocs: 2.5.0 – 2.4.0 – 2.3.0 – 2.2.0 – 2.1.0 – 2.0.0 <dependency><groupId>com.tinkerpop</groupId><artifactId>pipes</artifactId><version>2.5.0</version></dependency> Non-Maven users can get the raw release jars from Apache’s Central Repository. On the Nature of Pipes (Graphical Presentation of the Pipe Mechanics) 1 Pipes documentation is up to date with the current Pipes codebase, not with the latest Pipes release.

Finding your soulmate: autocomplete with Redis in Rails 3.1 Back in February the SeatGeek team open sourced a gem they call Soulmate that implements autocomplete using a Redis back end. “Soulmate finishes your sentences” as they say on their Github readme page. You can see it in action on I’ll get started today by showing you step by step how to setup a new Rails 3.1 app with Soulmate and Redis, using the jQuery UI autocomplete widget. How Soulmate was intended to work Here’s a conceptual diagram showing how you would normally use Soulmate: The Soulmate gem contains two components that you interact with directly: A loader script (“soulmate load”) that reads a data text file containing all of the words or phrases that your end users will search for and saves them into Redis, and: A Sinatra app that will perform searches against these words and return the matching results via HTTP directly to the user’s browser. Calling Soulmate directly from a Rails 3 app This was actually all very easy to do! Step 2: Creating a model and some test data

Berkeley DB Java Edition | Oracle Berkeley DB Oracle Berkeley DB Java Edition is an open source, embeddable, transactional storage engine written entirely in Java. It takes full advantage of the Java environment to simplify development and deployment. The architecture of Oracle Berkeley DB Java Edition supports very high performance and concurrency for both read-intensive and write-intensive workloads. The majority of Java solutions use object-to-relational (ORM) solutions like the Java Persistence API (JPA) to map class and instance data into rows and columns in a RDBMS. Berkeley DB Java Edition is different from all other Java databases available today. Berkeley DB Java Edition fits into the J2EE architecture by implementing three key APIs within J2EE. Berkeley DB Java Edition supports replication over multiple systems, enabling applications to scale massively with low latency and provide fault tolerance for high availability solutions. Data Storage Berkeley DB Java Edition stores data reliably and ensures data integrity.