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courses:mapreduce-tutorial:step-29 [2012/01/29 17:26]
straka 		courses:mapreduce-tutorial:step-29 [2012/01/30 00:44]
straka
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 Every custom format reading keys of type ''K'' and values of type ''V'' must subclass [[http://hadoop.apache.org/common/docs/r1.0.0/api/org/apache/hadoop/mapreduce/InputFormat.html|InputFormat<K, V>]]. Usually it is easier to subclass [[http://hadoop.apache.org/common/docs/r1.0.0/api/org/apache/hadoop/mapreduce/lib/input/FileInputFormat.html|FileInputFormat<K, V>]] -- the file listing and splitting is then solved by the ''FileInputFormat'' itself. Every custom format reading keys of type ''K'' and values of type ''V'' must subclass [[http://hadoop.apache.org/common/docs/r1.0.0/api/org/apache/hadoop/mapreduce/InputFormat.html|InputFormat<K, V>]]. Usually it is easier to subclass [[http://hadoop.apache.org/common/docs/r1.0.0/api/org/apache/hadoop/mapreduce/lib/input/FileInputFormat.html|FileInputFormat<K, V>]] -- the file listing and splitting is then solved by the ''FileInputFormat'' itself.
  
-===== WholeFileInputFormat =====+===== FileAsPathInputFormat =====
  
-We start by creating ''WholeFileInputFormat'', which reads any file and return exactly one input pair (input_path, file_content) with types (''Text'', ''BytesWritable''). The format does not allow file splitting -- each file will be processed by exactly one mapper.+We start by creating ''FileAsPathInputFormat'', which reads any file, splits it and for each split return exactly one input pair (file_path, start-length) with types (''Text'', ''Text''), where ''file_path'' is path to the file and ''start-length'' is a string containing two dash-separated numbers: start offset of the split and length of the split. 
 + 
 +When implementing new input format, we must 
 +  * decide whether the input files are splittable. Usually uncompressed files are splittable and compressed files are not splittable, with the exception of ''SequenceFile'', which is always splittable. 
 +  * implement [[http://hadoop.apache.org/common/docs/r1.0.0/api/org/apache/hadoop/mapreduce/RecordReader.html|RecordReader<K, V>]]. The ''RecordReader'' is the one doing the real work -- it is given a file split and it reads (key, value) pairs of types (K, V), until there are any. 
 + 
 +Our ''FileAsPathInputFormat'' is simple -- we allow splitting of uncompressed file and the ''RecordReader'' reads exactly one input pair. 
 +<code java> 
 +public class FileAsPathInputFormat extends FileInputFormat<Text, Text> { 
 +  // Helper class, which does the actual work -- produce the (path, offset-length) input pair. 
 +  public static class FileAsPathRecordReader extends RecordReader<Text, Text> { 
 +    private Path file; 
 +    long start, length; 
 +    private Text key, value; 
 +     
 +    public void initialize(InputSplit genericSplit, TaskAttemptContext context) throws IOException { 
 +      FileSplit split = (FileSplit) genericSplit; 
 +      file = split.getPath(); 
 +      start = split.getStart(); 
 +      length = split.getLength(); 
 +      key = null;    
 +      value = null;  
 +    }                
 +    public boolean nextKeyValue() throws IOException { 
 +      if (key != null) return false; 
 +                     
 +      key = new Text(file.toString()); 
 +      value = new Text(String.format("%d-%d", start, length)); 
 +                     
 +      return true;   
 +    }                
 +                     
 +    public Text getCurrentKey() { return key; } 
 +    public Text getCurrentValue() { return value; } 
 +    public float getProgress() { return (key == null) ? 0 : 1; } 
 +    public synchronized void close() throws IOException {} 
 +  } 
 +       
 +  // Use the helper class as a RecordReader in out file format. 
 +  public RecordReader<Text, Text> createRecordReader(InputSplit split, TaskAttemptContext context) { 
 +    return new FileAsPathRecordReader(); 
 +  }    
 +       
 +  // Allow splitting uncompressed files. 
 +  protected boolean isSplittable(JobContext context, Path filename) { 
 +    CompressionCodec codec = new CompressionCodecFactory(context.getConfiguration()).getCodec(filename); 
 +    return codec == null; 
 +  } 
 +} 
 +</code> 
 + 
 +===== WholeFileInputFormat =====
  
-The main functionality lays in ''WholeFileRecordReader'', a subclass of [[http://hadoop.apache.org/common/docs/r1.0.0/api/org/apache/hadoop/mapreduce/RecordReader.html|RecordReader<Text, BytesWritable]].+Next we create ''WhileFileInputFormat'', which for each file return exactly one input pair (input_path, file_content) with types (''Text'', ''BytesWritable''). The format does not allow file splitting -- each file will be processed by exactly one mapper.
  
 <code java> <code java>
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     private Path file;     private Path file;
     int length;     int length;
-    private boolean value_read; 
     private Text key;     private Text key;
     private BytesWritable value;     private BytesWritable value;
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       key = null;       key = null;
       value = null;       value = null;
-      value_read = false; 
  
       FileSystem fs = file.getFileSystem(context.getConfiguration());       FileSystem fs = file.getFileSystem(context.getConfiguration());
Line 38: Line 87:
  
     public boolean nextKeyValue() throws IOException {     public boolean nextKeyValue() throws IOException {
-      if (value_read) return false;+      if (key != null) return false;
  
       byte[] data = new byte[length];       byte[] data = new byte[length];
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       key = new Text(file.toString());       key = new Text(file.toString());
       value = new BytesWritable(data);       value = new BytesWritable(data);
-      value_read = true; 
  
       return true;       return true;
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     public Text getCurrentKey() { return key; }     public Text getCurrentKey() { return key; }
     public BytesWritable getCurrentValue() { return value; }     public BytesWritable getCurrentValue() { return value; }
-    public float getProgress() { return value_read ? 0 : 1; }+    public float getProgress() { return key == null ? 0 : 1; }
     public synchronized void close() throws IOException { if (in != null) { in.close(); in = null; } }     public synchronized void close() throws IOException { if (in != null) { in.close(); in = null; } }
   }   }
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   }   }
 } }
- 
 </code> </code>
  
 +===== Exercise: ParagraphTextInputFormat =====

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