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https://issues.apache.org/jira/browse/HADOOP-3149?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12584411#action_12584411
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Runping Qi commented on HADOOP-3149:
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The key to use MultipleOutputFormat class is to define a subclass that
implements
{code}
abstract protected RecordWriter<K, V> getBaseRecordWriter(FileSystem fs,
JobConf job, String name, Progressable arg3) throws IOException;
{code}
MultipleSequenceFileOutputFormat and MultipleTextOutputFormat are two simple
but commonly used sub classes.
If you need to use different type of record writer classes (TextRecordWriter
and SequenceFileRecordWriter) for different output files,
you need to have a subclass implementing that logic in getBaseRecordWriter.
You can use the name argument and/or any info in the JobConf argument to decide
whether to create a TextRecordReader or SequenceFileRecordWriter. Since
signatures for TextRecordWriter and SequenceFileRecordWriter are not quite
compatible,
you may beed to fiddle with the types a bit by type casting.
> supporting multiple outputs for M/R jobs
> ----------------------------------------
>
> Key: HADOOP-3149
> URL: https://issues.apache.org/jira/browse/HADOOP-3149
> Project: Hadoop Core
> Issue Type: New Feature
> Components: mapred
> Environment: all
> Reporter: Alejandro Abdelnur
> Assignee: Alejandro Abdelnur
> Fix For: 0.17.0
>
> Attachments: patch3149.txt
>
>
> The outputcollector supports writing data to a single output, the 'part'
> files in the output path.
> We found quite common that our M/R jobs have to write data to different
> output. For example when classifying data as NEW, UPDATE, DELETE, NO-CHANGE
> to later do different processing on it.
> Handling the initialization of additional outputs from within the M/R code
> complicates the code and is counter intuitive with the notion of job
> configuration.
> It would be desirable to:
> # Configure the additional outputs in the jobconf, potentially specifying
> different outputformats, key and value classes for each one.
> # Write to the additional outputs in a similar way as data is written to the
> outputcollector.
> # Support the speculative execution semantics for the output files, only
> visible in the final output for promoted tasks.
> To support multiple outputs the following classes would be added to
> mapred/lib:
> * {{MOJobConf}} : extends {{JobConf}} adding methods to define named outputs
> (name, outputformat, key class, value class)
> * {{MOOutputCollector}} : extends {{OutputCollector}} adding a
> {{collect(String outputName, WritableComparable key, Writable value)}} method.
> * {{MOMapper}} and {{MOReducer}}: implement {{Mapper}} and {{Reducer}} adding
> a new {{configure}}, {{map}} and {{reduce}} signature that take the
> corresponding {{MO}} classes and performs the proper initialization.
> The data flow behavior would be: key/values written to the default (unnamed)
> output (using the original OutputCollector {{collect}} signature) take part
> of the shuffle/sort/reduce processing phases. key/values written to a named
> output from within a map don't.
> The named output files would be named using the task type and task ID to
> avoid collision among tasks (i.e. 'new-m-00002' and 'new-r-00001').
> Together with the setInputPathFilter feature introduced by HADOOP-2055 it
> would become very easy to chain jobs working on particular named outputs
> within a single directory.
> We are using heavily this pattern and it greatly simplified our M/R code as
> well as chaining different M/R.
> We wanted to contribute this back to Hadoop as we think is a generic feature
> many could benefit from.
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