HDFS is a double-edged sword . Being a raw file system - you can feed it
to a Map Reduce program although it might be necessary to define
InputSplit-s as appropriate to chop down the input size.
OTOH, HBase is structured data ( well - sort of ! ) using a file format
on top of HDFS to store the schema and hence comes with predefined
InputSplit-s that make it easy to get started on a MapReduce program.
From an API simplicity point of view - HBase can get you started
relatively faster because of it ( assuming you have your data in hbase).
Refer to -
http://wiki.apache.org/hadoop/Hbase/MapReduce .
Although the wiki says deprecated - in reality - it is suggested to
stick with *.mapred.* packages for some time since the underlying
.mapreduce.* packages are not mature enough at this point.
The decision is to entirely do with - the kind of the data you have and
identifying the data by a primary key amenable to your application,
which is all hbase in its rudimentary form needs.
On the other hand - if having a schema and defining a primary key for
your data seems non-orthogonal for your app - you can stick with HDFS
and a custom InputSplit depending on your data. Especially since HBase
provides a lot more than HDFS in terms of scanning / row id ordering and
if these features are not necessary for what you do - then storing data
in HDFS should be just about ok.
On 1/28/10 6:20 PM, Otis Gospodnetic wrote:
I asked a similar question recently:
http://search-hadoop.com/[email protected]||hbase%20mapreduce%20otis%20TableInputFormat
Otis
----- Original Message ----
From: "[email protected]"<[email protected]>
To: [email protected]
Sent: Thu, January 28, 2010 8:02:39 PM
Subject: Hbase as Map/Reduce source
Hi,
I want to understand clearly about Hbase as Map/Reduce source.
Basicly, if a table with 100 regions, it means 100 map will be started,
right?
What's the difference between hdfs and hbase as a Map/Reduce source?
Thanks
Fleming Chiu(邱宏明)
707-6128
[email protected]
週一無肉日吃素救地球(Meat Free Monday Taiwan)
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