# Capture Directory Context in Hadoop Mapper

I have been using hadoop for data processing and datawarehousing for a while. One of the problem we encountered was map-reduce framework abstracts the input from files to lines, and thus it’s really difficult to apply logic based on different file or directories. Things got worse when we need to aggregate data across various versions of input sources. After digging in Hadoop source code, here is my solution.

## Meets InputSplit in Mapper

Here is the first solution, it’s a bit ugly but works. In Hadoop Mapper class, you can override the setup method to initiate mapper with corresponding context. The context contains inputSplit, which can be cast to FileInputSplit, and contains the file and directory information in it. This is how I did it:

If the input directory looks like this:

And the path argument you passed to FileInputFormat is /input. The resulting paths in the snippet would be one of these:

Each Mapper would get different file path instead of getting the directory /input. If you want to handle the logic better, you can do this:

## TaggedInputSplit

This works for most of the time; however, if you set the input to be /input/*/part*. The InputSplit would be an internal type called TaggedInputSplit instead of FileInputSplit. Although TaggedInputSplit has a method called getInputSplit to get the wrapped class, it is a private class and you can only use java reflection to hack it.

## More general solutions

The solutions above is working on production environment. However, it is a bit too hacky and not general enough. On the next post, I’ll show you how to implement InputFomrat, RecordReader, and Writable classes to solve this problem with lower level APIs.