AWS Certified Data Analytics Specialty 2021 - Hands-On! - [Exercise] Elastic MapReduce - Part 2

The video tutorial guides viewers through configuring Apache Spark to suppress info messages, running a script to generate recommendations, and accessing data from an S3 bucket. It covers data cleaning, debugging, and executing the script on an EMR cluster. The tutorial concludes with a demonstration of the recommender system's results and emphasizes the importance of cleaning up resources to avoid costs.

What is the purpose of setting the log level to 'error' in Spark?

• To display all log messages

• To show debug messages

• To suppress all log messages

• To only show error messages

Why is data cleaning important in machine learning?

• It reduces the size of the dataset

• It ensures the data is accurate and relevant

• It increases the complexity of the model

• It improves the speed of the algorithm

What change was made to the script to accommodate the new data source?

• Increased the number of nodes

• Added more data columns

• Updated the S3 bucket path

• Changed the delimiter to a semicolon

What was the error encountered during the script execution?

• Insufficient memory

• Missing data file

• Network timeout

• Incorrect column names

How was the error related to column names resolved?

• By updating the script with correct column names

• By changing the data format

• By increasing the cluster size

• By renaming the data file

What does a low root mean square error indicate in the context of the recommender system?

• The data is insufficient

• The model is performing well

• The algorithm is too complex

• The model is overfitting

Why is it important to terminate the EMR cluster after use?

• To free up storage space

• To prevent data loss

• To avoid incurring additional costs

• To improve system performance

What AWS service was used to populate the S3 data lake?

• Amazon EC2

• Amazon RDS

• Amazon Kinesis Firehose

• Amazon DynamoDB

What is the main function of the recommender system built in this tutorial?

• To classify images

• To predict user preferences

• To analyze text data

• To perform sentiment analysis

Which Apache Spark library was used to build the recommender system?

• GraphX

• MLlib

• Spark Streaming

• Spark SQL