Latest Hadoop MapReduce Interview Questions and answers:
What is MapReduce?
It is a framework or a programming model that
is used for processing large data sets over clusters of computers using
distributed programming.
What are 'maps' and
'reduces'?
'Maps' and
'Reduces' are two phases of solving a query in HDFS. 'Map' is
responsible to read data from input location, and based on the input type, it
will generate a key value pair,that is, an intermediate output in
local machine.'Reducer' is responsible to process the intermediate
output received from the mapper and generate the final output.
What are the four
basic parameters of a mapper?
The four basic
parameters of a mapper are LongWritable, text, text and IntWritable.
The first two represent input parameters and the second two represent
intermediate output parameters.
What are the four
basic parameters of a reducer?
The four basic
parameters of a reducer are Text, IntWritable, Text, IntWritable.The
first two represent intermediate output parameters and the second two represent
final output parameters.
What do the master
class and the output class do?
Master is defined to update the Master or the
job tracker and the output class is defined to write data onto the output
location.
What is the input
type/format in MapReduce by default?
By default the type input type in MapReduce is
'text'.
Is it mandatory to set
input and output type/format in MapReduce?
No, it is not mandatory to set the input and
output type/format in MapReduce. By default, the cluster takes the input and
the output type as 'text'.
What does the text
input format do?
In text input format,
each line will create a line object, that is an hexa-decimal number. Key is
considered as a line object and value is considered as a whole line text. This
is how the data gets processed by a mapper. The mapper will receive the 'key'
as a 'LongWritable' parameter and value as a 'Text' parameter.
What does job conf
class do?
MapReduce needs to
logically separate different jobs running on the same cluster. 'Job conf
class' helps to do job level settings such as declaring a job in real
environment. It is recommended that Job name should be descriptive and
represent the type of job that is being executed.
What does
conf.setMapper Class do?
Conf.setMapperclass sets the mapper class and all the stuff
related to map job such as reading a data and generating a key-value
pair out of the mapper.
What do sorting and
shuffling do?
Sorting and shuffling
are responsible for creating a unique key and a list of values.Making similar
keys at one location is known as Sorting. And the process by which
the intermediate output of the mapper is sorted and sent across to the reducers
is known as Shuffling.
What does a split do?
Before transferring
the data from hard disk location to map method, there is a phase or method
called the 'Split Method'. Split method pulls a block of data from HDFS
to the framework. The Split class does not write anything, but
reads data from the block and pass it to the mapper.Be default, Split is taken
care by the framework. Split method is equal to the block size and is used to
divide block into bunch of splits.
How can we change the
split size if our commodity hardware has less storage space?
If our commodity
hardware has less storage space, we can change the split size by writing the 'custom
splitter'. There is a feature of customization in Hadoop which can be
called from the main method.
What does a MapReduce
partitioner do?
A MapReduce partitioner makes sure that all the value of a single key
goes to the same reducer, thus allows evenly distribution of the map output
over the reducers. It redirects the mapper output to the reducer by determining
which reducer is responsible for a particular key.
How is Hadoop
different from other data processing tools?
In Hadoop, based upon your requirements, you
can increase or decrease the number of mappers without bothering about the
volume of data to be processed. this is the beauty of parallel processing in
contrast to the other data processing tools available.
Can we rename the
output file?
Yes we can rename the
output file by implementing multiple format output class.
Why we cannot do
aggregation (addition) in a mapper? Why we require reducer for that?
We cannot do aggregation (addition) in a
mapper because, sorting is not done in a mapper. Sorting happens only on the
reducer side. Mapper method initialization depends upon each input split. While
doing aggregation, we will lose the value of the previous instance. For each
row, a new mapper will get initialized. For each row, inputsplit again gets
divided into mapper, thus we do not have a track of the previous row value.
What is Streaming?
Streaming is a feature with Hadoop framework
that allows us to do programming using MapReduce in any programming language
which can accept standard input and can produce standard output. It could be
Perl, Python, Ruby and not necessarily be Java. However, customization in
MapReduce can only be done using Java and not any other programming language.
What is a Combiner?
A 'Combiner' is a mini reducer that performs
the local reduce task. It receives the input from the mapper on a particular
node and sends the output to the reducer. Combiners help in enhancing the
efficiency of MapReduce by reducing the quantum of data that is required to be
sent to the reducers.
What is the difference
between an HDFS Block and Input Split?
HDFS Block is the physical division of the data and Input
Split is the logical division of the data.
What happens in a
TextInputFormat?
In TextInputFormat,
each line in the text file is a record. Key is the byte offset
of the line and value is the content of the line.
For instance,Key: LongWritable, value: Text.
For instance,Key: LongWritable, value: Text.
What do you know about
KeyValueTextInputFormat?
In KeyValueTextInputFormat,
each line in the text file is a 'record'. The first separator character
divides each line. Everything before the separator is the key and
everything after the separator is the value.
For instance,Key: Text, value: Text.
For instance,Key: Text, value: Text.
What do you know about
SequenceFileInputFormat?
SequenceFileInputFormat is an input format for reading in sequence
files. Key and value are user defined. It is
a specific compressed binary file format which is optimized for passing the
data between the output of one MapReduce job to the input of some other
MapReduce job.
What do you know about
NLineOutputFormat?
NLineOutputFormat splits 'n' lines of input as one split.
