AWS Certified Data Analytics Specialty 2021 - Hands-On! - Apache Pig on Amazon Elastic MapReduce (EMR)

The video tutorial introduces Pig Latin, a scripting language in the Hadoop ecosystem, as an alternative to writing MapReduce code. It highlights Pig Latin's SQL-like syntax, making it easier to define map and reduce steps without Java. The tutorial covers Pig Latin's extensibility with user-defined functions and its integration with Hive. A code example demonstrates its high-level syntax. The video also explains Pig's integration with AWS, allowing data queries on Amazon S3 and EMR. Despite being older technology, Pig Latin remains relevant for distributed data analysis.

What is Pig Latin primarily used for in the Hadoop ecosystem?

• To optimize Tez performance

• To manage HDFS storage

• To provide a high-level scripting alternative to MapReduce

• To replace SQL databases

Which of the following is a feature of Pig that enhances its functionality?

• Built-in machine learning algorithms

• Automatic data encryption

• User-defined functions

• Real-time data processing

In the architecture of Pig, which component does it directly sit on top of?

• Amazon S3

• MapReduce or Tez

• HDFS

• YARN

How does Pig integrate with Amazon EMR?

• By providing a GUI for AWS services

• By directly managing EC2 instances

• By querying data on Amazon S3 through EMRFS

• By using built-in AWS machine learning models

What is a key characteristic of Pig's scripting language?

• It is used for real-time analytics

• It is identical to SQL

• It is highly distributed and SQL-like

• It is a low-level programming language