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From Nick Dimiduk <ndimi...@gmail.com>
Subject Re: Using Hadoop Input/Output formats
Date Fri, 04 Dec 2015 17:52:52 GMT
Thanks for the comments everyone. For my part, i'm interested most in using
Hadoop's OutputFormats for writing out data at the end of a streaming job.

I also agree that while these "convenience methods" make for good example
code in slide decks, they're often not helpful for "real" applications. The
additional maintenance burden of a bloated API tends to be
counter-productive.

-n

On Wed, Nov 25, 2015 at 8:41 AM, Robert Metzger <rmetzger@apache.org> wrote:

> I agree with Stephan.
>
> Reading static files is quite uncommon with the DataStream API. Before We
> add such a method, we should add a convenience method for Kafka ;)
> But in general, I'm not a big fan of adding too many of these methods
> because they pull in so many external classes, which lead to breaking API
> changes, dependency issues etc.
>
> I think such issues can be addressed easily with a good documentation
> (maybe in the "Best practices" guide), good answers on Stack Overflow and
> so on.
>
> On Wed, Nov 25, 2015 at 12:12 PM, Stephan Ewen <sewen@apache.org> wrote:
>
>> For streaming, I am a bit torn whether reading a file will should have so
>> many such prominent functions. Most streaming programs work on message
>> queues, or on monitored directories.
>>
>> Not saying no, but not sure DataSet/DataStream parity is the main goal -
>> they are for different use cases after all...
>>
>> On Wed, Nov 25, 2015 at 8:22 AM, Chiwan Park <chiwanpark@apache.org>
>> wrote:
>>
>>> Thanks for correction @Fabian. :)
>>>
>>> > On Nov 25, 2015, at 4:40 AM, Suneel Marthi <smarthi@apache.org> wrote:
>>> >
>>> > Guess, it makes sense to add readHadoopXXX() methods to
>>> StreamExecutionEnvironment (for feature parity with what's existing
>>> presently in ExecutionEnvironment).
>>> >
>>> > Also Flink-2949 addresses the need to add relevant syntactic sugar
>>> wrappers in DataSet api for the code snippet in Fabian's previous email.
>>> Its not cool, having to instantiate a JobConf in client code and having to
>>> pass that around.
>>> >
>>> >
>>> >
>>> > On Tue, Nov 24, 2015 at 2:26 PM, Fabian Hueske <fhueske@gmail.com>
>>> wrote:
>>> > Hi Nick,
>>> >
>>> > you can use Flink's HadoopInputFormat wrappers also for the DataStream
>>> API. However, DataStream does not offer as much "sugar" as DataSet because
>>> StreamEnvironment does not offer dedicated createHadoopInput or
>>> readHadoopFile methods.
>>> >
>>> > In DataStream Scala you can read from a Hadoop InputFormat
>>> (TextInputFormat in this case) as follows:
>>> >
>>> > val textData: DataStream[(LongWritable, Text)] = env.createInput(
>>> >   new HadoopInputFormat[LongWritable, Text](
>>> >     new TextInputFormat,
>>> >     classOf[LongWritable],
>>> >     classOf[Text],
>>> >     new JobConf()
>>> > ))
>>> >
>>> > The Java version is very similar.
>>> >
>>> > Note: Flink has wrappers for both MR APIs: mapred and mapreduce.
>>> >
>>> > Cheers,
>>> > Fabian
>>> >
>>> > 2015-11-24 19:36 GMT+01:00 Chiwan Park <chiwanpark@apache.org>:
>>> > I’m not streaming expert. AFAIK, the layer can be used with only
>>> DataSet. There are some streaming-specific features such as distributed
>>> snapshot in Flink. These need some supports of source and sink. So you have
>>> to implement I/O.
>>> >
>>> > > On Nov 25, 2015, at 3:22 AM, Nick Dimiduk <ndimiduk@gmail.com>
>>> wrote:
>>> > >
>>> > > I completely missed this, thanks Chiwan. Can these be used with
>>> DataStreams as well as DataSets?
>>> > >
>>> > > On Tue, Nov 24, 2015 at 10:06 AM, Chiwan Park <chiwanpark@apache.org>
>>> wrote:
>>> > > Hi Nick,
>>> > >
>>> > > You can use Hadoop Input/Output Format without modification! Please
>>> check the documentation[1] in Flink homepage.
>>> > >
>>> > > [1]
>>> https://ci.apache.org/projects/flink/flink-docs-release-0.10/apis/hadoop_compatibility.html
>>> > >
>>> > > > On Nov 25, 2015, at 3:04 AM, Nick Dimiduk <ndimiduk@apache.org>
>>> wrote:
>>> > > >
>>> > > > Hello,
>>> > > >
>>> > > > Is it possible to use existing Hadoop Input and OutputFormats
with
>>> Flink? There's a lot of existing code that conforms to these interfaces,
>>> seems a shame to have to re-implement it all. Perhaps some adapter shim..?
>>> > > >
>>> > > > Thanks,
>>> > > > Nick
>>> > >
>>> > > Regards,
>>> > > Chiwan Park
>>> > >
>>> > >
>>> >
>>> > Regards,
>>> > Chiwan Park
>>> >
>>>
>>> Regards,
>>> Chiwan Park
>>>
>>>
>>>
>>>
>>
>

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