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HDFS >> mail # user >> Re: Please help on providing correct answers


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Re: Please help on providing correct answers
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
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