Top Amazon EMR (Amazon Elastic MapReduce) Interview Questions (2021) | CodeUsingJava
















Most frequently Asked Amazon EMR (Amazon Elastic MapReduce) Interview Questions


  1. What is Amazon EMR?
  2. What are the benefits of Amazon EMR?
  3. How can we deploy Amazon EMR?
  4. What is EMR Studio?
  5. What is a Workspace in EMR Studio?
  6. How does Apache Spark work on Amazon EMR?
  7. What are the difference between Amazon EMR And EC2?
  8. Does Amazon EMR use HDFS?
  9. What are the Open Source Applications in Amazon EMR?
  10. What is MapReduce Key Value Pair?
  11. How does Amazon EMR Perform?
  12. How can we install Python modules on Amazon EMR?
  13. How to configure an EMR cluster by using boto?
  14. What are Amazon EMR Web Interfaces?

What is Amazon EMR?

Amazon EMR(Elastic MapReduce) is used in Data Analysis, Web Indexing, Data Warehousing, Financial Analysis, and Scientific Simulation. It also provides a managed framework in running data processing frameworks like Apache Hadoop, Apache Presto, and Apache Spark in securing manner and cost-effective.

What are the benefits of Amazon EMR?

Benefits of Amazon EMR are as follows:
  • Reliable in Nature - Amazon EMR helps in sensing if it retries fails tasks and also replaces its performing instances.
  • Elasticity - Amazon EMR helps in computing large amounts of instances in processing data at any scale.
  • Flexibility - Amazon EMR helps by completing control over the clusters and rooting access to all instances.
  • Securing - Amazon EMR helps in configuring AWS EC2 Firewall settings, controlling network access to the instances, launching clusters in AWS VPC, and many more.

How can we deploy Amazon EMR?

We can deploy Amazon EMR workloads by using AWS EKS(Elastic Kubernetes Service), AWS EC2, and premises of AWS Outposts. We can also run and manage our workloads within EMR Console, API, CLI, or SDK by using AWS Managed Workflow for Apache Airflow or AWS Step Functions.

What is EMR Studio?

EMR Studio helps in making data scientists and engineers in developing, visualizing, and debugging data engineering and data science applications all written in Scala, Python, and PySpark.It is also a fully managed application that also consists of Single-On, Automated Infrastructure Provisioning and has the Ability to Debugging Jobs without logging in to AWS Console or Cluster.

What is a Workspace in EMR Studio?

Workspace is used in organizing Jupyter Notebooks, those notebooks are then saved to the same AWS S3 location and can run on the same cluster. We can also link code repositories such as GitHub Repository to all the notebooks.

How does Apache Spark work on Amazon EMR?

Apache Spark is a programming model which helps us to do machine learning, stream processing by using Amazon EMR Clusters.

Amazon EMR


What are the difference between Amazon EMR And EC2?

AWS EC2(Elastic Compute Cloud) helps in providing computational resources in the cloud, it also reduces the time which is required in obtaining and booting new server instances to minutes by allowing us to quickly scale capacity up and down as our computing requirement changes.
Amazon EMR(Elastic MapReduce) is a cloud service that focuses on analytics and can run on top of the EC2 Instances. It has Hadoop Stack already installed. All users can decide and add services such as Presto, Hive, Spark, and many more as needed and based on the analytics desired.

Does Amazon EMR use HDFS?

Yes, Amazon EMR Cluster has Hadoop installed already. Hadoop contains an HDFS Storage system. All users can use HDFS in storing data, they can also use AWS S3 or the local disks which come with instances in the clusters.

What are the Open Source Applications in Amazon EMR?


Amazon EMR

  • Apache Hadoop used in processing large datasets.
  • Apache Spark used in big data workloads and optimizes execution for supporting general batch processing.
  • Apache HBase used as a Big Data Store that is present in the Hadoop Ecosystem.
  • Presto used in processing data data form various data stores which also includes HDFS(Hadoop Distributed File System).

What is MapReduce Key Value Pair?

MapReduce Key-Value helps in recording entities that Hadoop MapReduce accepts for execution. It can be operated on key-value pairs and also views the input to the job as a set of key-value pairs and helps in producing a set of key-value pairs as the output of the job.

How does Amazon EMR Perform?


Amazon EMR

Activities performed bt Amazon EMR are as follows:
Real-time Analytics
Log Analysis
Clickstream analysis
Extract Transform Load
Predictive Analytics
Genomics

How can we install Python modules on Amazon EMR?

We can install Python modules on Amazon EMR by using the following command:
#!/bin/bash -xe

# Non-Standard, Non-Amazon Machine Image Python modules:
sudo pip install -U
awscli            
boto              
ciso8601                      
workalendar

sudo yum install -y python-modules


How to configure an EMR cluster by using boto?

For configuring EMR Cluster by boto, we can use the following cammond:
#!/usr/bin/wnv python

import boto
import boto. emr
from the boot. emr.instance_group import InstanceGroup

conn = boto.emr.connect_to_region('us-west-1')


What are Amazon EMR Web Interfaces?


Amazon EMR

Amazon EMR Web Interfaces are as follows:
Amazon EMR
CloudWatch Event
AWS CloudWatch
AWS Lambda Target
AWS Route S3