In This article, you will get some common Interview Question
about Big data hadoop. Every Interviewer expected that Hadoop developer must
have deep understanding of Basic Concepts.
1) What is Big data
2) Why need to analysis Big data
3) What are the big data characteristics
4) What is Hadoop Map Reduce
5) How Hadoop MapReduce work
6) What is Hadoop Namenode
7) How JobTracker works
8) What is The Heartbeats
9) What is basic parameter of Mapper
What is Big data
Big
data is term that means a huge amount of Digital Data. This data is unorganized
and unstructured because it is capture from different sources. So it is
difficulty to analysis.
Read More - What is Big data and Hadoop
Why need to analysis Big data
Big
data helps to make strategy for future and understand user behaviors.
Let’s
take an Example:
When you
created Facebook an account, Facebook stored your all information such as your
location, your education, your work profile, your interest etc. this information
help full for marketing agency to target relevant audience.
What are the big data characteristics
Volume,
velocity and variety are main characteristics of big data. Let us know about
it.
Volume: Volume means amount of data.
Velocity: velocity means Speed of data
processing.
Variety: variety means Types of Information
or data.
What is Hadoop Map Reduce
To
analysis Big data, hadoop framework distribute data in datasets as hadoop clusters.
Data start in two steps first data mapping and then reduce data.
How Hadoop MapReduce work
Let's Understand With This Image How Hadoop Mapreduce Works
What is Hadoop Namenode
NameNode
is the location where Hadoop stored address of files location. In other words
Hadoop Distributed File System (HDFS) used NameNode to store files location.
what is JobTracker in Hadoop
Hadoop
send the mapreduceing Task to JobTracker for futher processing, JobTracker
takes input form Hadoop distribute file system(HDFS) and assign Task to Task Manager.
How
JobTracker works ?
Lets See Steps by Steps Processing of JobTracker.
- Copy All input files to DFS(Distributed File System)
- Submit a Query to Client Application
- Client Application store Input in HDFS NameNodes
- Client Splits job into Small Jobs
- These Small Job Information send to HDFS
- Client submit the job to job Tracker
- Job Tracker Initialize Job to Job Queue
- Job Tracker Read Job Files From HDFS
- Job Tracker Start to create Maps and Reduces
- Task Tracker send Heartbeat to Job Tracker
- Job Tracker Pick up the Task to Job Queue
- Send Task to Task Tracker
What is The Heartbeats
Task
Tracker send a Message to Job Tracker that I am alive and assign me some task
then Job Tracker Pick up the Task from Job Queue and Assign to Task Tracker.
What is basic parameter of Mapper
LongWritable
and Text
Text
and IntWritable
20 comments
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ReplyThe MapReduce has two phases. The first phase being the map phase and the second phase being the reduce phase. Map phase includes the counting of words or sorting out data. The second phase that is reduced as the name suggests includes reducing the data and aggregating them. Hence, the data first gets divided for analysis. The Best MapReduce Certification
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