On Tue, Jul 31, 2012 at 10:43 PM, Abhishek Shivkumar <
[EMAIL PROTECTED]> wrote:
> Hi Manoj,
> Pig is basically a data-flow language used to perform high-level simple
> operations such as summarizations and basic analysis on top of the data
> residing on HDFS. It uses a language called Pig-Latin. It gives your HDFS a
> datawarehouse kind of perspective, and lets you do a data analysis job by
> writing simple scripts.
> Pig Latin is easy to learn and one necessarily doesn't need to know
> mapreduce to write and run Pig Latin. It is important to note that once you
> write the Pig scripts, when they are run, internally they generate
> mapreduce jobs to run the scripts. So, eventually, you are using mapreduce
> On the other hand, you use mapreduce to perform a job that is not as
> simple to be written using a script in pig Latin. for this, you will need
> to design the mapreduce job by deciding how many reducers do you need,
> designing the combiner, partitioner and grouping class for various
> performance issues.
> Of course it is easy to run jobs using pig scripts, but it may not be
> possible to write everything in Pig.
> Hope it is fine.
> Thank you!
> With Regards,
> Abhishek S
> On Tue, Jul 31, 2012 at 10:37 PM, Manoj Babu <[EMAIL PROTECTED]> wrote:
>> It would be great if any of you compare Pig and Hadoop map reduce. When
>> we should go for Hadoop or Pig?
>> I love to program using java but peoples were arguing that can be
>> easily achieved in ping with very few lines of code even my boss too...
>> I am a fresh developer for Hadoop. Could kindly provide the pros and