A company has an on-premise data store in Oracle. They need to import the data into an Amazon EMR Cluster which uses HDFS. Which of the following can be used to fulfil this requirement?

Answer options:

A.Apache Hive
B.Apache Sqoop
C.Apache Hue
D.Jupyter Notebook

Answer – B
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Migrate RDBMS or On-Premise data to EMR Hive, S3, and Amazon Redshift using EMR – Sqoop
This blog post shows how our customers can benefit by using the Apache Sqoop tool. This tool is designed to transfer and import data from a Relational Database Management System (RDBMS) into AWS – EMR Hadoop Distributed File System (HDFS), transform the data in Hadoop, and then export the data into a Data Warehouse (e.g. in Hive or Amazon Redshift).
To demonstrate the Sqoop tool, this post uses Amazon RDS for MySQL as a source and imports data in the following three scenarios:
Scenario 1 — AWS EMR (HDFS -> Hive and HDFS)
Scenario 2 — Amazon S3 (EMFRS), and then to EMR-Hive
Scenario 3 — S3 (EMFRS), and then to Redshift
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Option A is incorrect since this is an open-source, data warehouse, and analytic package that runs on top of a Hadoop cluster
Option C is incorrect since this is an open-source, web-based, graphical user interface for use with Amazon EMR and Apache Hadoop
Option D is incorrect since this is an open-source web application that you can use to create and share documents that contain live code, equations, visualizations, and narrative text
For more information on a use case that uses Apache Sqoop, please refer to the below URL
https://aws.amazon.com/blogs/big-data/migrate-rdbms-or-on-premise-data-to-emr-hive-s3-and-amazon-redshift-using-emr-sqoop/