BIG DATA ANALYTICS (Department Elective-II) — Winter 2023

Explain five P’s of Big Data in brief.

Explain job scheduling of fair scheduler in Map Reduce.

1) Define the following terms:

Name Node b) Data Node c) Heartbeat 2) Explain HDFS operations in detail.

Explain Big Data in terms of Volume, Velocity and Veracity.

Enlist various applications of Big Data. How it can be used to improve the productivity in agriculture.

Explain Hadoop components with diagram.

1) Define data serialization. 2) With proper examples discuss and differentiate structured, unstructured and semi-structured data. 3) Make a note on how type of data affects data serialization.

Explain storage mechanism in HBase.

Differentiate: Apache pig Vs Map Reduce.

Justify “Spark is faster than MapReduce”.

Define Zookeeper. Enlist and discuss the benefits of it.

Explain the architecture of HIVE. List out the features of HIVE.

What is RDD? Explain about transformations and actions in the context of RDDs. State and explain RDD operations in brief.

Discuss Machine Learning with MLlib in SPARK.

Explain SPARK unified stack.

Differentiate SQL and NoSQL. Enlist the industry applications of NoSQL.

Explain sharding process of MongoDB.

Explain job scheduling of capacity scheduler in Map Reduce.

What is NoSQL? List out the features of NoSQL. Explain types of NoSQL databases in brief.

Define: Term Frequency and Inverse Document Frequency.

Explain metastore in Hive.

Explain following for MongoDB. 1) Indexing 2) Aggregation1

Explain scaling feature of MongoDB.

Explain following in brief with respect to Mongo DB : 1) Collections and documents 2) Indexing and retrieval

Explain CRUD operations with suitable example in MongoDB.