Enable javascript in your browser for better experience. Need to know to enable it? Go here.
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
采纳 ? 我们强烈建议业界采用这些技术,我们将会在任何合适的项目中使用它们。
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
试验 ? 值得一试。了解为何要构建这一能力是很重要的。企业应当在风险可控的前提下在项目中尝试应用此项技术。
May 2013
试验 ? 值得一试。了解为何要构建这一能力是很重要的。企业应当在风险可控的前提下在项目中尝试应用此项技术。
已发布 : May 22, 2013


English | Español | Português | 中文