BIG DATA ANALYTICS (Department Elective-II) — Winter 2022

1) Define the following terms:

Big Data b) Machine Learning c) Heartbeat

Explain 4Vs property of Big Data.

a) Explain five P’s of Big Data in brief.

Explain job scheduling of fair scheduler in Map Reduce.

Explain HDFS operations in detail.

Enlist various applications of Big Data. How it can be used in weather forecasting.

Define Distributed file system. Enlist and explain features of DFS.

a) Define Schema.

Explain the importance of Big Data.

Make a note on “how type of data affects data serialization.”

Explain storage mechanism in HBase.

Differentiate: Apache pig Vs Map Reduce.

Explain Hadoop components with diagram.

Define Zookeeper. Enlist and discuss the benefits of it.

Explain SPARK unified stack.

Justify “Spark is faster than MapReduce”.

Define: Term Frequency and Inverse Document Frequency.

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

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

Explain sharding process of MongoDB.

Explain job scheduling of capacity scheduler in Map Reduce.

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

Discuss Machine Learning with MLlib in SPARK.

Explain scaling feature of MongoDB.

Explain following for MongoDB. 1) Indexing 2) Aggregation1

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

Explain metastore in Hive.

Explain CRUD operations with suitable example in MongoDB.