Hadoop Ecosystem Fundamentals: MapReduce, Pig, Hive Basics

MapReduce focuses on ________, while Hive focuses on ________.

• Real-time processing; Batch analytics

• Batch processing; Data warehousing and querying

• Data visualization; ETL operations

• Data streaming; File storage

Which Hadoop component provides a high-level abstraction over MapReduce jobs?

• Pig and Hive

• YARN and HDFS

• HBase and Sqoop

• Oozie and Flume

Pig Latin scripts are internally converted into:

• HiveQL queries

• MapReduce jobs

• SQL queries

• NoSQL tables

MapReduce handles data at the ______ level, while Hive manages it at the ______ level.

• Record; Table

• File; Block

• Job; Cluster

• Node; Directory

Which one is declarative in nature?

• MapReduce

• Pig Latin

• HiveQL

• Both B and C

Pig is mainly designed for _______, whereas MapReduce is for _______.

• Simple queries; complex operations

• ETL operations; custom logic

• OLTP systems; OLAP systems

• Data transfer; resource management

In Hive, every query is internally executed as:

• SQL job

• MapReduce job

• Spark job

• Shell command

Which of the following allows schema-on-read processing?

• MapReduce only

• Hive and Pig

• HBase

• YARN

The shuffle and sort process in MapReduce is conceptually similar to which phase in Hive?

• Query optimization

• Data grouping and aggregation

• File loading

• Schema definition

MapReduce’s Combiner function is similar to which operation in Hive?

• GROUP BY

• ORDER BY

• DISTINCT

• JOIN