NPTEL Big Data Computing Assignment 4 Answer

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NPTEL Big Data Computing Assignment

ABOUT THE COURSE :
In today’s fast-paced digital world , the incredible amount of data being generated every minute has grown tremendously from sensors used to gather climate information, posts to social media sites, digital pictures and videos, purchase transaction records, and GPS signals from cell phone to name a few. This amount of large data with different velocities and varieties is termed as big data and its analytics enables professionals to convert extensive data through statistical and quantitative analysis into powerful insights that can drive efficient decisions. This course provides an in-depth understanding of terminologies and the core concepts behind big data problems, applications, systems and the techniques, that underlie today’s big data computing technologies. It provides an introduction to some of the most common frameworks such as Apache Spark, Hadoop, MapReduce, Large scale data storage technologies such as in-memory key/value storage systems, NoSQL distributed databases, Apache Cassandra, HBase and Big Data Streaming Platforms such as Apache Spark Streaming, Apache Kafka Streams that has made big data analysis easier and more accessible. And while discussing the concepts and techniques, we will also look at various applications of Big Data Analytics using Machine Learning, Deep Learning, Graph Processing and many others. The course is suitable for all UG/PG students and practicing engineers/ scientists from the diverse fields and interested in learning about the novel cutting edge techniques and applications of Big Data Computing.

PREREQUISITES : Data Structure & Algorithms, Computer Architecture, Operating System, Database Management Systems

INDUSTRY SUPPORT : Companies like Amazon, Microsoft, Google, IBM, Facebook

Next Week Assignment Answers

This course can have Associate in Nursing unproctored programming communication conjointly excluding the Proctored communication, please check announcement section for date and time. The programming communication can have a weightage of twenty fifth towards the ultimate score.

Final score = Assignment score + Unproctored programming exam score + Proctored Exam score

Assignment score = 25% of average of best 8 assignments out of the total 12 assignments given in the course.
( All assignments in a particular week will be counted towards final scoring – quizzes and programming assignments).
Unproctored programming exam score = 25% of the average scores obtained as part of Unproctored programming exam – out of 100
Proctored Exam score =50% of the proctored certification exam score out of 100

YOU WILL BE ELIGIBLE FOR A CERTIFICATE ONLY IF ASSIGNMENT SCORE >=10/25 AND
UNPROCTORED PROGRAMMING EXAM SCORE >=10/25 AND PROCTORED EXAM SCORE >= 20/50.

If any one of the 3 criteria is not met, you will not be eligible for the certificate even if the Final score >= 40/100.

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1 point

In Cassandra, ________________ replication strategy treats the entire cluster as a single data center. It is suitable for a single data center and one rack. This is also called as Rack-Unaware Strategy.

Simple strategy

Network topology strategy

Quorum strategy

None of the mentioned

1 point

In Cassandra, ____________________ is used to specify data centers and the number of replicas to place within each data center. It attempts to place replicas on distinct racks to avoid the node failure and to ensure data availability.

Simple strategy

Network topology strategy

Quorum strategy

None of the mentioned

1 point

True or False ?

A Snitch determines which data centers and racks nodes belong to. Snitches inform Cassandra about the network topology so that requests are routed efficiently and allows Cassandra to distribute replicas by grouping machines into data centers and racks.

True

False

1 point

Identify the correct choices for the given scenarios:

P: All nodes see same data at any time, or reads return latest written value by any client

Q: The system allows operations all the time, and operations return quickly

R: The system continues to work in spite of network partitions

P: Consistency, Q: Availability, R: Partition tolerance

P: Availability, Q: Consistency, R: Partition tolerance

P: Partition tolerance, Q: Consistency, R: Availability

P: Consistency, Q: Partition tolerance, R: Availability

1 point

Consider the following statements:

Statement 1: In Cassandra, during a write operation, when hinted handoff is enabled and If any replica is down, the coordinator writes to all other replicas, and keeps the write locally until down replica comes back up.

Statement 2: In Cassandra, Ec2Snitch is important snitch for deployments and it is a simple snitch for Amazon EC2 deployments where all nodes are in a single region. In Ec2Snitch region name refers to data center and availability zone refers to rack in a cluster.

Only Statement 1 is true

Only Statement 2 is true

Both Statements are true

Both Statements are false

1 point

Cassandra uses a protocol called __________________to discover location and state information about the other nodes participating in a Cassandra cluster.

Key-value

Memtable

Gossip

Heartbeat

1 point

What is Eventual Consistency ?

At any time, the system is linearizable

At any time, concurrent reads from any node return the same values

If writes stop, a distributed system will become consistent

If writes stop, all reads will return the same value after a while

1 point

Consider the following statements:

Statement 1: When two processes are competing with each other causing data corruption, it is called deadlock

Statement 2: When two processes are waiting for each other directly or indirectly, it is called race condition

Only Statement 1 is true

Only Statement 2 is true

Both Statements are false

Both Statements are true

1 point

Which of the following is incorrect statement ?

ZooKeeper is a distributed co-ordination service to manage large set of hosts.

ZooKeeper allows developers to focus on core application logic without worrying about the distributed nature of the application.

ZooKeeper solves this issue with its simple architecture and API.

The ZooKeeper framework was originally built at “Google” for accessing their applications in an easy and robust manner.

1 point

In Zookeeper, when a _______ is triggered the client receives a packet saying that the znode has changed.

Event

Row

Watch

Value

1 point

ZooKeeper itself is intended to be replicated over a sets of hosts called ____________

Chunks

Ensemble

Subdomains

None of the mentioned

1 point

Consider the Table temperature_details in Keyspace “day3” with schema as follows:

temperature_details(daynum, year,month,date,max_temp)
with primary key(daynum,year,month,date)

There exists same maximum temperature at different hours of the same day. Choose the correct CQL query to:

Alter table temperature_details to add a new column called “seasons” using map of type <varint, text> represented as <month, season>. Season can have the following values season={spring, summer, autumn, winter}.

Update table temperature_details where columns daynum, year, month, date contain the following values- 4317,1955,7,26 respectively.

Use the select statement to output the row after updation.

Note: A map relates one item to another with a key-value pair. For each key, only one value may exist, and duplicates cannot be stored. Both the key and the value are designated with a data type.

cqlsh:day3> alter table temperature_details add hours1 set<varint>;
cqlsh:day3> update temperature_details set hours1={1,5,9,13,5,9} where daynum=4317; cqlsh:day3> select * from temperature_details where daynum=4317;

cqlsh:day3> alter table temperature_details add seasons map<varint,text>;
cqlsh:day3> update temperature_details set seasons = seasons + {7:’spring’} where daynum=4317 and year =1955 and month = 7 and date=26;
cqlsh:day3> select * from temperature_details where daynum=4317 and year=1955 and month=7 and date=26;

cqlsh:day3>alter table temperature_details add hours1 list<varint>;
cqlsh:day3> update temperature_details set hours1=[1,5,9,13,5,9] where daynum=4317 and year = 1955 and month = 7 and date=26;
cqlsh:day3> select * from temperature_details where daynum=4317 and year=1955 and month=7 and date=26;

cqlsh:day3> alter table temperature_details add seasons map<month, season>;
cqlsh:day3> update temperature_details set seasons = seasons + {7:’spring’} where daynum=4317;
cqlsh:day3> select * from temperature_details where daynum=4317;

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