Framework that makes processing arbitrary binary data in Hadoop easier
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I recently needed a quick way to analyze millions of small binary files (from 100K-19MB each) and I wanted a scalable way to repeatedly do this sort of analysis. I chose Hadoop as the platform, and I built this little framework (really, a single MapReduce job) to do it. This is very much a work in progress, and feedback and pull requests are welcome.

The main MapReduce job in this framework accepts a Sequence file of <Text, BytesWritable> where the Text is a name and the BytesWritable is the contents of a file. The framework unpacks the bytes of the BytesWritable to the local filesystem of the mapper it is running on, allowing the mapper to run arbitrary analysis tools that require local filesystem access. The framework then captures stdout and stderr from the analysis tool/script and stores it (how it stores it is pluggable, see io.covert.binary.analysis.OutputParser).


mvn package assembly:assembly



# a local directory with files in it (directories are ignored for now)

# convert a bunch of relatively small files into one sequence file (Text, BytesWritable)
hadoop jar $JAR io.covert.binary.analysis.BuildSequenceFile $LOCAL_FILES $INPUT

# Use the config properties in example.xml to basically run the script on each file using Hadoop
# as the platform for computation
hadoop jar $JAR io.covert.binary.analysis.BinaryAnalysisJob -files -conf example.xml $INPUT $OUTPUT

From example.xml:




This block of example instructs the framework to run using the args of ${file} (where ${file} is replaced by the unpacked filename from the Sequence File. If multiple command line args are required, they can be specified by appending a delimiter and then each arg to the value of the binary.analysis.program.args property


Useful for performing distributed file computation, mainly tailored for converting large binary files to a different format. Example, converting a weird compressed file format to a normal one that can use standard Hadoop tools.

hadoop fs -ls files | awk '{print $8}' > /tmp/all   
# OR hadoop fs -lsr | grep -v '^d' | awk '{print $8}' > /tmp/all

mkdir file-lists
cd file-lists
split -l 10 /tmp/all
cd ..
hadoop fs -put file-lists file-lists

hadoop jar $JAR io.covert.util.FileFormatToConverterJob -Dstream.process.command="/opt/" file-lists