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From "Alejandro Abdelnur (JIRA)" <j...@apache.org>
Subject [jira] Commented: (HADOOP-3149) supporting multiple outputs for M/R jobs
Date Wed, 02 Apr 2008 04:27:24 GMT

    [ https://issues.apache.org/jira/browse/HADOOP-3149?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12584401#action_12584401

Alejandro Abdelnur commented on HADOOP-3149:

Owen, let me try filling the gaps in your suggestion.

# {{MultipleOutputFormats}} extends {{MultipleOutputFormat}} providing a static method to
define named outputs in the job conf including outputformat, key and value classes.
# {{MultipleOutputFormats}} will also implement the logic to create the per task file names
based on the given named output.
# A {{MultipleOutputCollector}} will provide a {{collect(String namedOutput, WritableComparable
key, Writable value)}} method.
# {{MultipleOutputMapper}} and {{MultipleOutputReducer}} classes will have {{map}} and  {{reduce}}
method receiving a {{MultipleOutputCollector}}.
# There will not be a {{MOJobConf}}, #1 takes care of seeding the named output data into the
vanilla {{JobConf}}.

Follow up comments/questions:

* I don't see the point of the KeyValue class as it will not be possible to leverage the generic
type checking at compile time (that is why #3 signature differs from your suggestion).
* It seems to me that {{MultipleOutputFormats}} would have to have its own subclasses for
Text and SequenceFile to create the right {{RecordWriter}} within the {{getRecordWriter}}
method as I could have named outputs that are {{TextOutputFormat}} or {{SequenceFileOutputFormat}}.
And the {{MultipleOutputFormats}} would be restricted to handle those 2 output format types.


> 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
> 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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