I just realized I never published a list of links of one of my preferred topic. This is the first post:
Storm – a real time Hadoop like system in Clojure
Hadoop Programming Challenge
The Design of Distributed Applications
Thoughts around REST, DDD, and CQRS: Models, Queries, and Commands
Welcome to Apache Pig
Apache Pig is a platform for analyzing large data sets that consists of a high-level language for expressing data analysis programs, coupled with infrastructure for evaluating these programs. The salient property of Pig programs is that their structure is amenable to substantial parallelization, which in turns enables them to handle very large data sets.
Welcome to Hama project
Apache Hama is a distributed computing framework based on BSP (Bulk Synchronous Parallel) computing techniques for massive scientific computations, e.g., matrix, graph and network algorithms. It was inspired by Google’s Pregel, but different in the sense that it’s purely BSP and common model, not just for graph.
InfoQ: Things Break, Riak Bends
HPCC Systems | Open-source. Fast. Scalable. Simple
HPCC (High Performance Computing Cluster) is a massive parallel-processing computing platform that solves Big Data problems. The platform is now Open Source!
SmartFrog is a powerful and flexible Java-based software framework for configuring, deploying and managing distributed software systems.
Mesos: Dynamic Resource Sharing for Clusters
Mesos is a cluster manager that provides efficient resource isolation and sharing across distributed applications, or frameworks. It can run Hadoop, MPI, Hypertable, Spark (a new framework for low-latency interactive and iterative jobs), and other applications. Mesos is open source in the Apache Incubator.
Dryad – Microsoft Research
InfoQ: Secure Distributed Programming on ECMAScript 5 + HTML5
Ceph as a scalable alternative to the Hadoop Distributed File System
Data-driven Apps With Microsoft Velocity Distributed Caching
Spark is an open source cluster computing system that aims to make data analytics fast — both fast to run and fast to write.
Distributed computing fallacies and REST
Presentation Schedule // CS 525: Advanced Distributed Systems // Spring 2011
InfoQ: Francesco Cesarini and Simon Thompson on Erlang
Scala and Akka are deployed in production at some of the largest web properties and financial institutions in the world, and run on the battle-tested Java runtime environment. Deploy with confidence.
Introducing Riak Core
Actors: A Model of Concurrent Computation in Distributed Systems
The Hadoop Distributed File System
InfoQ: Concurrency Control in Data Replication
Build a distributed realtime tweet search system in no time. Part 1/2
Windows Azure futures: Turning the cloud into a supercomputer
Episode 1: Distributed Systems Host Introductions
Frangipani: A Scalable Distributed File System
Systems We Make
Fault tolerance techniques for distributed systems
Swarm: A true distributed programming language
MSDN Magazine: Distributed Apps
Scalable System Design Patterns
Load Balancer, Scatter and Gather, Result Cache, Shared Space, Pipe and Filter, Map Reduce, Bulk Synchronous Parallel, Execution Orchestrator