Partition Aware Graph Computing System

Graph partition quality affects the overall performance of distributed graph computing systems. The quality of a graph partition is measured by the balance factor and edge cut ratio. A balanced graph partition with small edge cut ratio is generally preferred since it reduces the high network communication cost. However, through an empirical study on Giraph, we find that the performance over well partitioned graph might be even two times worse than simple random partitions. The reason is that the systems only optimize for the simple partition strategies and cannot efficiently handle the increasing workload of local message processing when a high-quality graph partition is used. In this chapter, we introduce a novel partition-aware graph computing system named PAGE, which equips a new message processor and a dynamic concurrency control model. The new message processor concurrently processes local and …