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Avro >> mail # user >> Avro new mapreduce API


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Re: Avro new mapreduce API
Hi Johannes,

Thanks for you remind. It's solved after adding mapper key/value schema settings.

New mapreduce API is more convenient than mapred's. I love this way.
Best Regards,

Jamin
在 2013-10-6,上午5:30,Johannes Schulte <[EMAIL PROTECTED]> 写道:

> Hi,
>
> you should try using the static methods of AvroJob  to configure your map output key and value schemas. This takes care of configuring the right KeyComparators for you. SO instead of writing
>
> job.setMapOutputKeyClass(AvroKey.class);
>         job.setMapOutputValueClass(AvroValue.class);
>
> write
>
> AvroJob.setMapOutputKEySchema(Schema.create(Type.String));
> AvroJob.setMapOutputValueSchema(NetflowRecord.getClassSchema())
>
> and same for output values
>
> AvroJob.setOutputKeySchema.
>
>
> Cheers,
> Johannes
>
>
>
> On Wed, Oct 2, 2013 at 3:28 PM, Xiaming Chen <[EMAIL PROTECTED]> wrote:
> Hi there,
>
> Can u give me some examples or explaination about programming with
> pure org.apache.avro.mapreduce interfaces??
>
> -------- Save your time, continue if you know how --------
>
> All of my programs are writing with hadoop's new MR1 interfaces
> (org.apache.hadoop.mapreduce), so I want to use new
> org.apache.avro.mapreduce of avro too. But it doesn't work for me.
>
> The program takes input of avro data and output the same.
> The main idea behind my program is subclassing hadoop's Mapper
> and Reducer against avro wrapped key/value.
>
> Here is a block of my job driver :
>
>         AvroJob.setInputKeySchema(job, NetflowRecord.getClassSchema());
>         AvroJob.setOutputKeySchema(job, NetflowRecord.getClassSchema());
>
>         job.setMapperClass(MyAvroMap.class);
>         job.setReducerClass(MyAvroReduce.class);
>        
>         job.setInputFormatClass(AvroKeyInputFormat.class);
>         job.setOutputFormatClass(AvroKeyOutputFormat.class);
>
>         job.setMapOutputKeyClass(AvroKey.class);
>         job.setMapOutputValueClass(AvroValue.class);
>        
>         job.setOutputKeyClass(AvroKey.class);
>         job.setOutputValueClass(NullWritable.class);
>
> The definitions of MyAvroMap and MyAvroReduce subclasses respectivly are
>
>     public static class MyAvroMap extends Mapper<AvroKey<NetflowRecord>, NullWritable,
>     AvroKey<CharSequence>, AvroValue<NetflowRecord>>{ ... }
>
>     public static class MyAvroReduce extends Reducer<AvroKey<CharSequence>, AvroValue<NetflowRecord>,
>            AvroKey<NetflowRecord>, NullWritable>{ ... }
>
> The methioned NetflowRecord is my avro record class. And I got running exception
>
>     java.lang.ClassCastException: class org.apache.avro.hadoop.io.AvroKey
>
> By reading hadoop's and avro's source code,
> I found that the exception was thrown by JobConf to make sure
> the map key is a subclass of WritableComparable, like this (hadoop1.2.1, line759)
>
>     WritableComparator.get(getMapOutputKeyClass().asSubclass(WritableComparable.class));
>
> But the avro shows that AvroKey and AvroValue are just a simple wrapper
> **without** subclassing Writable* interfaces of hadoop.
> I believe that, even without testing, I can get through that using old mapred interfaces,
> but its not what I want.
>
>
> Sincerely,
>
> Jamin
>
>
>

NEW: Monitor These Apps!
elasticsearch, apache solr, apache hbase, hadoop, redis, casssandra, amazon cloudwatch, mysql, memcached, apache kafka, apache zookeeper, apache storm, ubuntu, centOS, red hat, debian, puppet labs, java, senseiDB