I'm looking to run a job that involves a zillion files in a format called CDF, a nasa standard. There are a number of libraries out there that can read CDFs but most of them are not high quality compared to the official NASA one, which has java bindings (via JNI). It's a little clumsy but I have it working fairly well in Scala.
The way I was planning on distributing work was with SparkContext.binaryFIles("hdfs://somepath/*) but that's really sending in an RDD of byte[] and unfortunately the CDF library doesn't support any kind of array or stream as input. The reason is that CDF is really looking for a random-access file, for performance reasons. Whats worse, all this code is implemented down at the native layer, in C. I think my best choice here is to distribute the job using .binaryFiles() but then have the first task of the worker be to write all those bytes to a ramdisk file (or maybe a real file, we'll see)... then have the CDF library open it as if it were a local file. This seems clumsy and awful but I haven't come up with any other good ideas. Has anybody else worked with these files and have a better idea? Some info on the library that parses all this: https://cdf.gsfc.nasa.gov/html/cdf_docs.html --Chris