Hi,

I'd instead like you to explain why you think someone's proposed
answer (who?) is wrong and why yours is correct. You learn more that
way than us head nodding/shaking to things you ask.

On Wed, Nov 7, 2012 at 10:51 PM, Ramasubramanian Narayanan
<[EMAIL PROTECTED]> wrote:
> Hi,
>
>    I came across the following question in some sites and the answer that
> they provided seems to be wrong according to me... I might be wrong... Can
> some one help on confirming the right answers for these 11 questions pls..
> appreciate the explanation if you could able to provide...
>
> *******************************************************************************
> You are running a job that will process a single InputSplit on a cluster
> which has no other jobs
> currently running. Each node has an equal number of open Map slots. On which
> node will Hadoop
> first attempt to run the Map task?
> A. The node with the most memory
> B. The node with the lowest system load
> C. The node on which this InputSplit is stored
> D. The node with the most free local disk space
>
> My Answer            : C
> Answer Given in site : A
>
> *******************************************************************************
> What is a Writable?
> A. Writable is an interface that all keys and values in MapReduce must
> implement. Classes implementing this interface must implement methods
> forserializingand deserializing themselves.
> B. Writable is an abstract class that all keys and values in MapReduce must
> extend. Classes extending this abstract base class must implementmethods for
> serializing and deserializingthemselves
> C. Writable is an interface that all keys, but not values, in MapReduce must
> implement. Classes implementing this interface mustimplementmethods for
> serializing and deserializing themselves.
> D. Writable is an abstract class that all keys, but not values, in MapReduce
> must extend. Classes extending this abstract base class must
> implementmethods for serializing and deserializing themselves.
>
> My Answer            : A
> Answer Given in site : B
>
> *******************************************************************************
>
> You write a MapReduce job to process 100 files in HDFS. Your MapReducc
> algorithm uses
> TextInputFormat and the IdentityReducer: the mapper applies a regular
> expression over input
> values and emits key-value pairs with the key consisting of the matching
> text, and the value
> containing the filename and byte offset. Determine the difference between
> setting the number of
> reducers to zero.
> A. There is no differenceinoutput between the two settings.
> B. With zero reducers, no reducer runs and the job throws an exception. With
> one reducer,
> instances of matching patterns are stored in a single file on HDFS.
> C. With zero reducers, all instances of matching patterns are gathered
> together in one file on
> HDFS. With one reducer, instances ofmatching patternsstored in multiple
> files on HDFS.
> D. With zero reducers, instances of matching patterns are stored in multiple
> files on HDFS. With
> one reducer, all instances of matching patterns aregathered together in one
> file on HDFS.
>
> My Answer            : D
> Answer Given in site : C
>
> *******************************************************************************
>
> During the standard sort and shuffle phase of MapReduce, keys and values are
> passed to
> reducers. Which of the following is true?
> A. Keys are presented to a reducerin sorted order; values foragiven key are
> not sorted.
> B. Keys are presented to a reducer in soiled order; values for a given key
> are sorted in ascending
> order.
> C. Keys are presented to a reducer in random order; values for a given key
> are not sorted.
> D. Keys are presented to a reducer in random order; values for a given key
> are sorted in
> ascending order.
>
> My Answer            : A
> Answer Given in site : D
>
> *******************************************************************************

Harsh J