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![Twitter's Storm, March 29, 2012](https://cdn-ak-scissors.b.st-hatena.com/image/square/c94df6abefe7376e9d119c5cc884d97b79648e6e/height=288;version=1;width=512/https%3A%2F%2Fi.ytimg.com%2Fvi%2FFfIYZdxQ3VM%2Fhqdefault.jpg%3Fsqp%3D-oaymwEWCMQBEG5IWvKriqkDCQgBFQAAiEIYAQ%3D%3D%26rs%3DAOn4CLA2bKyoIEEcRoG85ujifvtk8pfbFA%26days_since_epoch%3D19873)
2. HADOOP VS STORM Batch processing Real-time processing Jobs runs to completion Topologies run forever JobTracker is SPOF* No single point of failure Stateful nodes Stateless nodes Scalable Scalable Guarantees no data loss Guarantees no data loss Open source Open source * Hadoop 0.21 added some checkpointing SPOF: Single Point Of Failure 3. COMPONENTS Nimbus daemon is comparable to Hadoop JobTrac
Past Christmas I found the perfect pet project for that season: Twitter Storm. Basically is a excellent piece of software that will allow you to process real time information in a ‘kind’ of map reduce style. Also it’s based on the concept of topologies (workflows), quite familiar to me after working at Yahoo! with the precursor of Apache Oozie (workflows for Haddop!) With that background, and afte
Retrieving Storm Cluster Statistics from Nimbus This tutorial will show how to obtain basic storm topology statistics from nimbus (similar to the information show in the storm ui dashboard) so you can store that data in a separate location – such as graphite – for monitoring. Since storm topologies are thrift-based, you can use almost any language to connect to nimbus to download your data. Assump
Storm 0.8.0 will introduce a new amazing feature named pluggable scheduler, what scheduler does is schduling the task assignment: which task should run on which supervisor(machine). So it opens up the opportunity to do a lot of things, for example: make sure a particular task run on a particular machine Topology priority: when the resource is limited, always make sure TopologyA is scheduled first.
Building Large-scale Real-world Recommender Systems - Recsys2012 tutorial There is more to recommendation algorithms than rating prediction. And, there is more to recommender systems than algorithms. In this tutorial, given at the 2012 ACM Recommender Systems Conference in Dublin, I review things such as different interaction and user feedback mechanisms, offline experimentation and AB testing, or
by Jordan Zimmerman Open Source at NetflixWe are committed to Open Source Software at Netflix. We’ve blogged about it in the past. Today we are announcing a portal for open source projects from Netflix. The portal is currently hosted on Github. There are several projects in the pipeline (including Curator which we’re announcing today): Curator — The Netflix ZooKeeper LibraryAstyanax — The Netflix
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