How to use "typedbytes" or "rawbytes" in Hadoop Streaming?

Question

I have a problem that would be solved by Hadoop Streaming in "typedbytes" or "rawbytes" mode, which allow one to analyze binary data in a language other than Java. (Without this, Streaming interprets some characters, usually \t and \n, as delimiters and complains about non-utf-8 characters. Converting all my binary data to Base64 would slow down the workflow, defeating the purpose.)

These binary modes were added by HADOOP-1722. On the command line that invokes a Hadoop Streaming job, "-io rawbytes" lets you define your data as a 32-bit integer size followed by raw data of that size, and "-io typedbytes" lets you define your data as a 1-bit zero (which means raw bytes), followed by a 32-bit integer size, followed by raw data of that size. I have created files with these formats (with one or many records) and verified that they are in the right format by checking them with/against the output of typedbytes.py. I've also tried all conceivable variations (big-endian, little-endian, different byte offsets, etc.). I'm using Hadoop 0.20 from CDH4, which has the classes that implement the typedbytes handling, and it is entering those classes when the "-io" switch is set.

I copied the binary file to HDFS with "hadoop fs -copyFromLocal". When I try to use it as input to a map-reduce job, it fails with an OutOfMemoryError on the line where it tries to make a byte array of the length I specify (e.g. 3 bytes). It must be reading the number incorrectly and trying to allocate a huge block instead. Despite this, it does manage to get a record to the mapper (the previous record? not sure), which writes it to standard error so that I can see it. There are always too many bytes at the beginning of the record: for instance, if the file is "\x00\x00\x00\x00\x03hey", the mapper would see "\x04\x00\x00\x00\x00\x00\x00\x00\x00\x07\x00\x00\x00\x08\x00\x00\x00\x00\x03hey" (reproducible bits, though no pattern that I can see).

From page 5 of this talk, I learned that there are "loadtb" and "dumptb" subcommands of streaming, which copy to/from HDFS and wrap/unwrap the typed bytes in a SequenceFile, in one step. When used with "-inputformat org.apache.hadoop.mapred.SequenceFileAsBinaryInputFormat", Hadoop correctly unpacks the SequenceFile, but then misinterprets the typedbytes contained within, in exactly the same way.

Moreover, I can find no documentation of this feature. On Feb 7 (I e-mailed it to myself), it was briefly mentioned in the streaming.html page on Apache, but this r0.21.0 webpage has since been taken down and the equivalent page for r1.1.1 has no mention of rawbytes or typedbytes.

So my question is: what is the correct way to use rawbytes or typedbytes in Hadoop Streaming? Has anyone ever gotten it to work? If so, could someone post a recipe? It seems like this would be a problem for anyone who wants to use binary data in Hadoop Streaming, which ought to be a fairly broad group.

P.S. I noticed that Dumbo, Hadoopy, and rmr all use this feature, but there ought to be a way to use it directly, without being mediated by a Python-based or R-based framework.

Answer 1

Okay, I've found a combination that works, but it's weird.

1. Prepare a valid typedbytes file in your local filesystem, following the documentation or by imitating typedbytes.py.

2. Use

   hadoop jar path/to/streaming.jar loadtb path/on/HDFS.sequencefile < local/typedbytes.tb
   

   to wrap the typedbytes in a SequenceFile and put it in HDFS, in one step.

3. Use

   hadoop jar path/to/streaming.jar -inputformat org.apache.hadoop.mapred.SequenceFileAsBinaryInputFormat ...
   

   to run a map-reduce job in which the mapper gets input from the SequenceFile. Note that -io typedbytes or -D stream.map.input=typedbytes should not be used--- explicitly asking for typedbytes leads to the misinterpretation I described in my question. But fear not: Hadoop Streaming splits the input on its binary record boundaries and not on its '\n' characters. The data arrive in the mapper as "rawdata" separated by '\t' and '\n', like this:

   1. 32-bit signed integer, representing length (note: no type character)
   2. block of raw binary with that length: this is the key
   3. '\t' (tab character... why?)
   4. 32-bit signed integer, representing length
   5. block of raw binary with that length: this is the value
   6. '\n' (newline character... ?)

4. If you want to additionally send raw data from mapper to reducer, add

   -D stream.map.output=typedbytes -D stream.reduce.input=typedbytes
   

   to your Hadoop command line and format the mapper's output and reducer's expected input as valid typedbytes. They also alternate for key-value pairs, but this time with type characters and without '\t' and '\n'. Hadoop Streaming correctly splits these pairs on their binary record boundaries and groups by keys.

The only documentation on stream.map.output and stream.reduce.input that I could find was in the HADOOP-1722 exchange, starting 6 Feb 09. (Earlier discussion considered a different way to parameterize the formats.)

This recipe does not provide strong typing for the input: the type characters are lost somewhere in the process of creating a SequenceFile and interpreting it with the -inputformat. It does, however, provide splitting at the binary record boundaries, rather than '\n', which is the really important thing, and strong typing between the mapper and the reducer.

Answer 2

We solved the binary data issue using hexaencoding the data at split level when streaming down data to the Mapper. This would utilize and increase the Parallel efficiency of your operation instead of first tranforming your data before processing on a node.