Chameleon Speeds Development of Portable Hadoop Reader for Parallel File Systems
Some scientists dream about big data. The dream bridges two divided realms. One realm holds lofty peaks of number-crunching scientific computation. Endless waves of big data analysis line the other realm. A deep chasm separates the two. Discoveries await those who cross these estranged lands. Unfortunately, data cannot move seamlessly between #Hadoop (HDFS) and #parallelfilesystems (PFS). Scientists who want to take advantage of the big data analytics available on Hadoop must copy data from parallel file systems. That can slow workflows to a crawl, especially those with terabytes of data.