Last updated : Jul 08, 2014
Not on the current edition
This blip is not on the current edition of the Radar. If it was on one of the last few editions it is likely that it is still relevant. If the blip is older it might no longer be relevant and our assessment might be different today. Unfortunately, we simply don't have the bandwidth to continuously review blips from previous editions of the Radar
Understand more
Jul 2014
Adopt
We feel strongly that the industry should be adopting these items. We use them when appropriate on our projects.
Hadoop's initial architecture was based on the paradigm of scaling data horizontally and metadata vertically. While data storage and processing were handled by the slave nodes reasonably well, the masters that managed metadata were a single point of failure and limiting for web scale usage. Hadoop 2.0 has significantly re-architected both HDFS and the Map Reduce framework to address these issues. The HDFS namespace can be federated now using multiple name nodes on the same cluster and deployed in a HA mode. MapReduce has been replaced with YARN, which decouples cluster resource management from job state management and eliminates the scale/performance issues with the JobTracker. Most importantly, this change encourages deploying new distributed programming paradigms in addition to MapReduce on Hadoop clusters.
Jan 2014
Trial
Worth pursuing. It is important to understand how to build up this capability. Enterprises should try this technology on a project that can handle the risk.
May 2013
Trial
Worth pursuing. It is important to understand how to build up this capability. Enterprises should try this technology on a project that can handle the risk.
Veröffentlicht : May 22, 2013
