How does MapReduce read from multiple input files?

问题

I am developing a code to read data and write it into HDFS using mapreduce. However when I have multiple files I don't understand how it is processed . The input path to the mapper is the name of the directory as evident from the output of

String filename = conf1.get("map.input.file");

So how does it process the files in the directory ?

回答1:

In order to get the input file path you can use the context object, like this:

FileSplit fileSplit = (FileSplit) context.getInputSplit();
String inputFilePath = fileSplit.getPath().toString();

And as for how it multiple files are processed:

Several instances of the mapper function are created on the different machines in the cluster. Each instance receives a different input file. If files are bigger than the default dfs block size(128 MB) then files are further split into smaller parts and are then distributed to mappers.

So you can configure the input size being received by each mapper by following 2 ways:

• change the HDFS block size (eg dfs.block.size=1048576)
• set the paramaeter mapred.min.split.size (this can be only set to larger than HDFS block size)

Note: These parameters will only be effective if your input format supports splitting the input files. Common compression codecs (such as gzip) don't support splitting the files, so these will be ignored.

回答2:

In continuation to @Amar 's answer , I used FileStatus object in the following code as my customised inoput format would not split the input file.

FileSystem fs = file.getFileSystem(conf);
                FileStatus status= fs.getFileStatus(file);
                String fileName=status.getPath().toString();

来源：https://stackoverflow.com/questions/14067129/how-does-mapreduce-read-from-multiple-input-files