hadoop-user mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From Harsh J <ha...@cloudera.com>
Subject Re: Please help on providing correct answers
Date Wed, 07 Nov 2012 18:22:12 GMT
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
<ramasubramanian.narayanan@gmail.com> 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
>
> *******************************************************************************
>
> Which statement best describes the data path of intermediate key-value pairs
> (i.e., output of the
> mappers)?
> A. Intermediate key-value pairs are written to HDFS. Reducers read the
> intermediate data from
> HDFS.
> B. Intermediate key-value pairs are written to HDFS. Reducers copy the
> intermediate data to the
> local disks of the machines runningthe reduce tasks.
> C. Intermediate key-value pairs are written to the local disks of the
> machines running the map
> tasks, and then copied to the machinerunning thereduce tasks.
> D. Intermediate key-value pairs are written to the local disks of the
> machines running the map
> tasks, and are then copied to HDFS. Reducers read theintermediate data from
> HDFS.
>
> My Answer            : C
> Answer Given in site : B
>
> *******************************************************************************
>
> You are developing a combiner that takes as input Text keys, IntWritable
> values, and emits Text
> keys, Intwritable values. Which interface should your class implement?
> A. Mapper <Text, IntWritable, Text, IntWritable>
> B. Reducer <Text, Text, IntWritable, IntWritable>
> C. Reducer <Text, IntWritable, Text, IntWritable>
> D. Combiner <Text, IntWritable, Text, IntWritable>
> E. Combiner <Text, Text, IntWritable, IntWritable>
>
> My Answer            : D
> Answer Given in site : C
>
> *******************************************************************************
>
> What happens in a MapReduce job when you set the number of reducers to one?
> A. A single reducer gathers and processes all the output from all the
> mappers. The output is
> written in as many separate files as there are mappers.
> B. A single reducer gathers and processes all the output from all the
> mappers. The output is
> written to a single file in HDFS.
> C. Setting the number of reducers to one creates a processing bottleneck,
> and since the number
> of reducers as specified by the programmer is used as areference value only,
> the MapReduce
> runtime provides a default setting for the number of reducers.
> D. Setting the number of reducers to one is invalid, and an exception is
> thrown
>
> My Answer            : B
> Answer Given in site : C
>
> *******************************************************************************
>
> In the standard word count MapReduce algorithm, why might using a combiner
> reduce the overall
> Job running time?
> A. Because combiners perform local aggregation of word counts, thereby
> allowing the mappers to
> process input data faster.
> B. Because combiners perform local aggregation of word counts, thereby
> reducing the number of
> mappers that need to run.
> C. Because combiners perform local aggregation of word counts, and then
> transfer that data to
> reducers without writing the intermediatedata to disk.
> D. Because combiners perform local aggregation of word counts, thereby
> reducing the number of
> key-value pairs that need to be snuff letacross thenetwork to the reducers.
>
> My Answer            : C
> Answer Given in site : A
>
> *******************************************************************************
>
> You need to create a GUI application to help your company's sales people add
> and edit customer
> information. Would HDFS be appropriate for this customer information file?
> A. Yes, because HDFS isoptimized forrandom access writes.
> B. Yes, because HDFS is optimized for fast retrieval of relatively small
> amounts of data.
> C. No, becauseHDFS can only be accessed by MapReduce applications.
> D. No, because HDFS is optimized for write-once, streaming access for
> relatively large files.
>
> My Answer            : D
> Answer Given in site : A
>
> *******************************************************************************
>
> You need to create a job that does frequency analysis on input data. You
> will do this by writing a
> Mapper that uses TextInputForma and splits each value (a line of text from
> an input file) into
> individual characters. For each one of these characters, you will emit the
> character as a key and
> as IntWritable as the value. Since this will produce proportionally more
> intermediate data than
> input data, which resources could you expect to be likely bottlenecks?
> A. Processor and RAM
> B. Processor and disk I/O
> C. Disk I/O and network I/O
> D. Processor and network I/O
>
> My Answer            : D
> Answer Given in site : B
>
> *******************************************************************************
>
> Which of the following statements best describes how a large (100 GB) file
> is stored in HDFS?
> A. The file is divided into variable size blocks, which are stored on
> multiple data nodes. Each block
> is replicated three timesby default.
> B. The file is replicated three times by default. Each ropy of the file is
> stored on a separate
> datanodes.
> C. The master copy of the file is stored on a single datanode. The replica
> copies are divided into
> fixed-size blocks, which are stored on multiple datanodes.
> D. The file is divided into fixed-size blocks, which are stored on multiple
> datanodes.Eachblock is
> replicated three times by default. Multiple blocks from the same file
> mightreside on the same
> datanode.
> E. The tile is divided into fixed-sizeblocks, which are stored on multiple
> datanodes.Eachblock is
> replicated three times by default.HDES guarantees that different blocks from
> the same file are
> never on the same datanode.
>
> My Answer            : D
> Answer Given in site : B
>
> *******************************************************************************
>
> regards,
> Rams



-- 
Harsh J

Mime
View raw message