Have your record reader seek (and discard data) until it finds the beginning of your frame, and always keep reading until the end/length of the current frame/record. This will assure you that if your PB record is split between blocks that you will read them all.
For example, suppose you end up with 2 mappers, and 3 PB records across 2 HDFS splits, then mapper 1 will read one record immediately (it sees the frame market right away), and continue reading a second record up until its end / length -- even into the next block. Mapper 2 will begin reading its block, and begin looking for a frame marker, discarding data up until the marker; effectively reading in one block once it finds the frame marker. Between both mappers you've now read all 3 blocks. HTH, -Michael On Feb 10, 2013, at 10:36 AM, Christopher Piggott <[email protected]> wrote: I'm a little confused about splitting and readers. The data in my application is stored in files of google protocol buffers. There are multiple protocol buffers per file. There have been a number of simple ways to put multiple protobufs in a single file, usually involving writing some kind of length field before. We did something a little more complicated by defining a frame similar to HDLC: frames are enveloped by a flag, escapes provided so the flag can't occur within the frame; and there is a 32-bit CRC-like checksum just before the closing flag. The protobufs are all a type named RitRecord, and we have our own reader that's something like this: public interface RitRecordReader { RitRecord getNext(); } The data collection appication stores these things in ordinary flat files (the whole thing is run through a GzipOutputFilter first, so the files are compressed). I'm having trouble understanding how to best apply this to HDFS for map function consumption. Our data collector writes 1 megabyte files, but I can combine them for map/reduce performance. To avoid TOO much wasted space I was thinking about 16, 32, or 64 MB HDFS blocks (tbd). What I don't get is this: suppose we have a long file that spans multiple HDFS blocks. I think I end up with problems similar to this guy: http://blog.rguha.net/?p=293 where one of my RitRecord objects is half in one HDFS block and half in another HDFS block. If the mapper is assigning tasks to nodes along HDFS blocks then I'm going to end up with a problem. It's not yet clear to me how to solve this. I could make the problem LESS likely with bigger blocks (like the default 128MB) but even then, the problem doesn't completely go away (for me, a >128MB file is unlikely but not impossible). --Chris
