CS-702-D Big Data - Nov 2023 Question Paper

Under each question, How to answer lists the points an answer should cover, outlined by CampusPrep from the syllabus. Check the details against your textbook.

1. 7 Marks
   aDescribe any five characteristics of Big Data.
   How to answer

   • Define Big Data and Vs model
   • Explain any five: Volume, Velocity, Variety, Veracity, Value / Variability etc.
   • Give example for each characteristic
   • Conclude with need for Big Data technologies
2. 7 Marks
   bDescribe the structure of HDFS in a Hadoop ecosystem using a diagram.
   How to answer

   • Define HDFS and its role in Hadoop ecosystem
   • Explain NameNode, DataNode, Secondary NameNode, blocks, replication
   • Provide labelled schematic diagram of HDFS architecture
   • Explain read/write flow briefly
3. 7 Marks
   aExplain the technologies available for big data.
   How to answer

   • Define Big Data technology stack
   • Explain storage: HDFS, NoSQL, etc.
   • Explain processing: MapReduce, Spark, Hive, Pig
   • Explain ingestion / management tools: Sqoop, Flume, YARN
4. 7 Marks
   bEnlist and explain the various challenges with big data.
   How to answer

   • List major challenges: storage, velocity, variety, veracity, privacy, security, skilled manpower
   • Explain each challenge briefly
   • Relate to Volume/Velocity/Variety issues
   • Conclude with impact on processing
5. 7 Marks
   aExplain in detail Hadoop distributed file system.
   How to answer

   • Define HDFS and design goals
   • Explain architecture: NameNode, DataNode, blocks, replication
   • Explain features: fault tolerance, scalability, read/write operations
   • Add labelled diagram of HDFS
6. 7 Marks
   bDiscuss the following:

   1. i)Mapper
   2. ii)Reducer
   3. iii)Combiner
   How to answer

   • Define MapReduce phase roles
   • Explain Mapper: input splits to key-value pairs
   • Explain Reducer: shuffle, sort, aggregate
   • Explain Combiner: mini-reducer, optimization
7. 7 Marks
   aExplain how big data processing differs from distributed processing.
   How to answer

   • Define big data processing vs traditional distributed processing
   • Compare on data size, type, scalability, fault tolerance
   • Explain Hadoop / MapReduce paradigm difference
   • Give examples
8. 7 Marks
   bWhat is Hive meta store? Which classes are used by the Hive to Read and write HDFS files? Explain.
   How to answer

   • Define Hive metastore and its need
   • Explain embedded, local, remote metastore modes
   • Identify SerDe / InputFormat / OutputFormat classes for HDFS read-write
   • Explain read-write flow with example
9. 7 Marks
   aWrite example Hive Queries for Natural Join and Outer-Join.
   How to answer

   • Define Hive JOIN syntax
   • Write example NATURAL JOIN query with tables
   • Write example OUTER JOIN (LEFT/RIGHT/FULL) query
   • Explain output briefly
10. 7 Marks
    bList and explain the relational operators in Pig.
    How to answer

    • Define Pig Latin relational operators
    • List FOREACH, FILTER, GROUP, JOIN, ORDER, DISTINCT etc.
    • Explain function of each with syntax
    • Give small example
11. 7 Marks
    aWrite a short note on NoSQL databases.
    How to answer

    • Define NoSQL and need over RDBMS
    • Explain types: key-value, document, column, graph
    • Give examples: MongoDB, Cassandra, etc.
    • Summarize features
12. 7 Marks
    bDifferentiate between NoSQL and relational database.
    How to answer

    • Define NoSQL vs relational model
    • Compare on schema, scalability, ACID vs BASE, query language
    • Present comparison in table
    • Give use-case suitability
13. 7 Marks
    aDescribe applications of NoSQL databases in Industry.
    How to answer

    • Define industrial need for NoSQL
    • Explain applications: e-commerce, social media, IoT, banking
    • Give examples: MongoDB, Cassandra use cases
    • Conclude with benefits
14. 7 Marks
    bWhat is NoSQL database? Discuss key characteristics and advantages of NoSQL database.
    How to answer

    • Define NoSQL database
    • Explain key characteristics: schema-less, horizontal scaling, distributed
    • Explain advantages: high availability, performance, flexibility
    • Give examples
15. 14 Marks
    Explain the following:

    1. i)Applications of social network mining
    2. ii)Recommender system
    How to answer

    • Define social network mining and recommender system
    • Explain applications of social network mining: community detection, influence analysis
    • Explain recommender system types: collaborative, content-based
    • Give industry examples