Group items tagged

"Graph for Scala is intended to provide basic graph functionality that seamlessly fits into the Scala standard collections library. Like the other members of scala.collection, Graph for Scala is an in-memory container that exposes a user-friendly interface without sacrificing functionality or flexibility. Graph for Scala also has ready-to-go implementations of JSON-Import/Export and Dot-Export - more popular graph serialization formats are coming soon. In addition, other powerful tools such as graph databases emulation and distributed graph processing are due to be supported."

What is Graphite? Graphite is a highly scalable real-time graphing system. As a user, you write an application that collects numeric time-series data that you are interested in graphing, and send it to Graphite's processing backend, carbon, which stores the data in Graphite's specialized database. The data can then be visualized through graphite's web interfaces. Who should use Graphite? Graphite is actually a bit of a niche application. Specifically, it is designed to handle numeric time-series data. For example, Graphite would be good at graphing stock prices because they are numbers that change over time. However Graphite is a complex system, and if you only have a few hundred distinct things you want to graph (stocks prices in the S&P 500) then Graphite is probably overkill. But if you need to graph a lot of different things (like dozens of performance metrics from thousands of servers) and you don't necessarily know the names of those things in advance (who wants to maintain such huge configuration?) then Graphite is for you.

"sigma.js is an open-source lightweight JavaScript library to draw graphs, using the HTML canvas element. It has been especially designed to: Display interactively static graphs exported from a graph visualization software - like Gephi Display dynamically graphs that are generated on the fly"

"Titan is a scalable graph database optimized for storing and querying graphs containing hundreds of billions of vertices and edges distributed across a multi-machine cluster. Titan is a transactional database that can support thousands of concurrent users executing complex graph traversals."

"Blueprints is a property graph model interface. It provides implementations, test suites, and supporting extensions. Graph databases and frameworks that implement the Blueprints interfaces automatically support Blueprints-enabled applications. Likewise, Blueprints-enabled applications can plug-and-play different Blueprints-enabled graph backends."

"Apache Giraph is an iterative graph processing system built for high scalability. For example, it is currently used at Facebook to analyze the social graph formed by users and their connections. Giraph originated as the open-source counterpart to Pregel, the graph processing architecture developed at Google and described in a 2010 paper. Both systems are inspired by the Bulk Synchronous Parallel model of distributed computation introduced by Leslie Valiant. Giraph adds several features beyond the basic Pregel model, including master computation, sharded aggregators, edge-oriented input, out-of-core computation, and more. With a steady development cycle and a growing community of users worldwide, Giraph is a natural choice for unleashing the potential of structured datasets at a massive scale."

"Faunus is a property graph analytics engine based on Hadoop. A breadth-first version of the graph traversal language Gremlin operates on a vertex-centric property graph data structure. Faunus can be extended with new operations written using MapReduce and Blueprints."

"Protostuff is the stuff that leverages google's protobuf. A serialization library with built-in support for forward-backward compatibility (schema evolution) and validation. available formats: protostuff (native) graph (protostuff with support for cyclic references. See SerializingObjectGraphs) protobuf json smile (binary json useable from the protostuff-json module) xml yaml (ser only) kvp (binary uwsgi header) support for messages that are generated by the protostuff-compiler (java_bean) cyclic references via graph format see CompilerOptions for more customized compilation of .proto files support for existing pojos (See runtime schemas) cyclic references via graph format polymorphic (a nested message can be an interface/abstract class or even java.lang.Object) support for existing protoc-generated java messages see the io instructions for json, xml, yaml) no support for cyclic references (limitation of the builder pattern) Interoperability across various mobile platforms android kindle j2me (protostuff-me module) Transcoding support converts one encoding to another. See PipeUsage. Source and Sink protostuff, protobuf, json, json-numeric, smile, smile-numeric, xml Sink only yaml "

"Terraform is a tool for building, changing, and versioning infrastructure safely and efficiently. Terraform can manage existing and popular service providers as well as custom in-house solutions. Configuration files describe to Terraform the components needed to run a single application or your entire datacenter. Terraform generates an execution plan describing what it will do to reach the desired state, and then executes it to build the described infrastructure. As the configuration changes, Terraform is able to determine what changed and create incremental execution plans which can be applied. The infrastructure Terraform can manage includes low-level components such as compute instances, storage, and networking, as well as high-level components such as DNS entries, SaaS features, etc. The key features of Terraform are: Infrastructure as Code: Infrastructure is described using a high-level configuration syntax. This allows a blueprint of your datacenter to be versioned and treated as you would any other code. Additionally, infrastructure can be shared and re-used. Execution Plans: Terraform has a "planning" step where it generates an execution plan. The execution plan shows what Terraform will do when you call apply. This lets you avoid any surprises when Terraform manipulates infrastructure. Resource Graph: Terraform builds a graph of all your resources, and parallelizes the creation and modification of any non-dependent resources. Because of this, Terraform builds infrastructure as efficiently as possible, and operators get insight into dependencies in their infrastructure. Change Automation: Complex changesets can be applied to your infrastructure with minimal human interaction. With the previously mentioned execution plan and resource graph, you know exactly what Terraform will change and in what order, avoiding many possible human errors."

big-data graph graph-processing architecture development programming

"The Neo4j Scala wrapper library allows you the Neo4j open source graph database through a domain-specific simplified language."

"Gephi is an interactive visualization and exploration platform for all kinds of networks and complex systems, dynamic and hierarchical graphs."

Data.js is a data representation framework for Javascript. It is being developed in the context of Substance, a web-based document authoring and publishing engine. It took some inspiration from various existing libraries such as the Google Visualization API or Underscore.js.  You can report bugs and discuss features on the GitHub issues page, on Freenode IRC in the #_substance chann el, post questions to the Google Group, or send tweets to @_substance. With Data.js you can: Model your domain data using a simple graph-based object model that can be serialized to JSON. Traverse your graph, including relationships using a simple API. Manipulate and query data on the client (browser) or on the server (Node.js) by using exactly the same API. 

Open source software products in the graph space

...investigadores de la Universidad Carlos III de Madrid (UC3M) han desarrollado el algoritmo SoSACO, que acelera la búsqueda de caminos entre dos nodos pertenecientes al grafo que representa a una red social... Habría que analizar si es aplicable a los datos de navrel este algoritmo.

"Apache Hama is a pure BSP (Bulk Synchronous Parallel) computing framework on top of HDFS (Hadoop Distributed File System) for massive scientific computations such as matrix, graph and network algorithms. Today, many practical data processing applications require a more flexible programming abstraction model that is compatible to run on highly scalable and massive data systems (e.g., HDFS, HBase, etc). A message passing paradigm beyond Map-Reduce framework would increase its flexibility in its communication capability. Bulk Synchronous Parallel (BSP) model fills the bill appropriately. Some of its significant advantages over MapReduce and MPI are: * Supports message passing paradigm style of application development * Provides a flexible, simple, and easy-to-use small APIs * Enables to perform better than MPI for communication-intensive applications * Guarantees impossibility of deadlocks or collisions in the communication mechanisms"

Ostrich is a library for servers that makes it easy to:  * load & reload per-environment configuration  * collect runtime statistics (counters, gauges, metrics, and labels)  * report those statistics through a simple web interface (optionally with graphs) or into log files  * interact with the server over HTTP to check build versions or shut it down