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From "Buttler, David" <buttl...@llnl.gov>
Subject RE: Best Way to Insert data into Hbase using Map Reduce
Date Fri, 05 Nov 2010 15:28:07 GMT
Have you tried turning off auto flush, and managing the flush in your own code (say every 1000
puts?)
Dave


-----Original Message-----
From: Shuja Rehman [mailto:shujamughal@gmail.com] 
Sent: Friday, November 05, 2010 8:04 AM
To: user@hbase.apache.org
Subject: Re: Best Way to Insert data into Hbase using Map Reduce

Michael

hum....so u are storing xml record in the hbase and in second job, u r
parsing. but in my case i am parsing it also in first phase. what i do, i
get xml file and i parse it using jdom and then putting data in hbase. so
parsing+putting both operations are in 1 phase and in mapper code.

My actual problem is that after parsing file, i need to use put statement
millions of times and i think for each statement it connects to hbase and
then insert it and this might be the reason of slow processing. So i am
trying to figure out some way we i can first buffer data and then insert in
batch fashion. it means in one put statement, i can insert many records and
i think if i do in this way then the process will be very fast.

secondly what does it means? "we write the raw record in via a single put()
so the map() method is a null writable."

can u explain it more?

Thanks


On Fri, Nov 5, 2010 at 5:05 PM, Michael Segel <michael_segel@hotmail.com>wrote:

>
> Suja,
>
> Just did a quick glance.
>
> What is it that you want to do exactly?
>
> Here's how we do it... (at a high level.)
>
> Input is an XML file where we want to store the raw XML records in hbase,
> one record per row.
>
> Instead of using the output of the map() method, we write the raw record in
> via a single put() so the map() method is a null writable.
>
> Its pretty fast. However fast is relative.
>
> Another thing... we store the xml record as a string (converted to
> bytecode) rather than a serialized object.
>
> Then you can break it down in to individual fields in a second batch job.
> (You can start with a DOM parser, and later move to a Stax parser.
> Depending on which DOM parser you have and the size of the record, it should
> be 'fast enough'. A good implementation of Stax tends to be
> recursive/re-entrant code which is harder to maintain.)
>
> HTH
>
> -Mike
>
>
> > Date: Fri, 5 Nov 2010 16:13:02 +0500
> > Subject: Best Way to Insert data into Hbase using Map Reduce
> > From: shujamughal@gmail.com
> > To: user@hbase.apache.org
> >
> > Hi
> >
> > I am reading data from raw xml files and inserting data into hbase using
> > TableOutputFormat in a map reduce job. but due to heavy put statements,
> it
> > takes many hours to process the data. here is my sample code.
> >
> > conf.set(TableOutputFormat.OUTPUT_TABLE, "mytable");
> >     conf.set("xmlinput.start", "<adc>");
> >     conf.set("xmlinput.end", "</adc>");
> >     conf
> >         .set(
> >           "io.serializations",
> >
> >
> "org.apache.hadoop.io.serializer.JavaSerialization,org.apache.hadoop.io.serializer.WritableSerialization");
> >
> >       Job job = new Job(conf, "Populate Table with Data");
> >
> >     FileInputFormat.setInputPaths(job, input);
> >     job.setJarByClass(ParserDriver.class);
> >     job.setMapperClass(MyParserMapper.class);
> >     job.setNumReduceTasks(0);
> >     job.setInputFormatClass(XmlInputFormat.class);
> >     job.setOutputFormatClass(TableOutputFormat.class);
> >
> >
> > *and mapper code*
> >
> > public class MyParserMapper   extends
> >     Mapper<LongWritable, Text, NullWritable, Writable> {
> >
> >     @Override
> >     public void map(LongWritable key, Text value1,Context context)
> >
> > throws IOException, InterruptedException {
> > *//doing some processing*
> >  while(rItr.hasNext())
> >                     {
> > *                   //and this put statement runs for 132,622,560 times
> to
> > insert the data.*
> >                     context.write(NullWritable.get(), new
> > Put(rowId).add(Bytes.toBytes("CounterValues"),
> > Bytes.toBytes(counter.toString()),
> Bytes.toBytes(rElement.getTextTrim())));
> >
> >                     }
> >
> > }}
> >
> > Is there any other way of doing this task so i can improve the
> performance?
> >
> >
> > --
> > Regards
> > Shuja-ur-Rehman Baig
> > <http://BLOCKEDpk.linkedin.com/in/shujamughal>
>




-- 
Regards
Shuja-ur-Rehman Baig
<http://BLOCKEDpk.linkedin.com/in/shujamughal>

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