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The following page has been changed by HyunsikChoi: http://wiki.apache.org/hadoop/Hamburg ------------------------------------------------------------------------------ == Goal == * Support graph traverse - * Support a simple programming interface dealing graph data + * Support a simple programming interface familiar with graph features. * Follow the scalability concept of shared-nothing architecture * Fault-Tolerant Implementation == Hamburg == - Hambrug is an alternative to MR programming model. It consists of two parts, each of which is related to locality-preserving storage method for graph in terms of connectivity and computations with traverse interface on graphs respectively. + Hambrug is an alternative to MR programming model. It consists of two parts, each of which is related to locality-preserving storing method for graph in terms of connectivity and computations with traverse interface on graphs respectively. - The main purpose of Locality-preserving storage methods for graph is to store vertices close to one another into the same HDFS block. The computation part with this may reduce considerable communication cost and the number of bulk sync step. It will be a kind of preprocessed step and be implemented in MR. + The main purpose of the locality-preserving storing method for graph is to store vertices close to one another into the same HDFS block. The computation part with this storing method may reduce considerable communication cost and the number of bulk sync step. It will be a kind of pre-process step and be implemented in MR. The computation part is based on bulk synchronization parallel (BSP) model. Like MR, Hamburg will take advantages from shared-nothing architecture (SN), so I expect that it will also show scalability without almost degradation of performance as the number of participant nodes increases. In addition, we will provide a set of easy APIs familiar with graph features and similar to MR.
