lec4

Question 2

What is parallel computing?

Answer 2

The foundation of modern cloud computing, enabling the execution of multiple computations simultaneously to improve performance and scalability.

Question 3

What are the main models of parallelism?

Answer 3

• Task Parallelism
• Data Parallelism
• Pipeline Parallelism

Question 4

Define Task Parallelism.

Answer 4

Different tasks are executed simultaneously across different computing units.

Question 5

Define Data Parallelism.

Answer 5

The same operation is performed concurrently on subsets of a large dataset.

Question 6

Define Pipeline Parallelism.

Answer 6

A sequence of processing stages where the output of one stage serves as input to the next.

Question 7

How does parallel computing in the cloud work?

Answer 7

It is facilitated by distributed architectures that dynamically allocate resources as needed.

Question 8

What is MapReduce?

Answer 8

A programming model designed for processing large datasets in parallel across a distributed cluster.

Question 9

What are the two main phases of MapReduce?

Answer 9

• Map Phase
• Reduce Phase

Question 10

What occurs in the Map Phase of MapReduce?

Answer 10

Input data is split into smaller chunks and processed in parallel.

Question 11

What occurs in the Reduce Phase of MapReduce?

Answer 11

The processed data is aggregated and combined to generate the final output.

Question 12

What does Hadoop provide?

Answer 12

• HDFS (Hadoop Distributed File System)
• YARN (Yet Another Resource Negotiator)
• MapReduce API

Question 13

What is HDFS?

Answer 13

A scalable and fault-tolerant storage system.

Question 14

What is YARN?

Answer 14

A resource management layer that schedules and allocates resources efficiently.

Question 15

What is the limitation of Hadoop?

Answer 15

Its batch-processing nature makes it less suitable for real-time applications.

Question 16

What is Apache Spark?

Answer 16

An in-memory distributed computing engine that processes data much faster than Hadoop.

Question 17

What is the RDD abstraction in Spark?

Answer 17

Resilient Distributed Dataset, allowing data to be processed in-memory with fault tolerance.

Question 18

List key features of Apache Spark.

Answer 18

• RDDs
• DAG (Directed Acyclic Graph) Execution
• Streaming Capabilities
• Integration with Machine Learning
• Graph Processing

Question 19

What is serverless computing?

Answer 19

Allows developers to deploy code without managing underlying infrastructure.

Question 20

What is Function-as-a-Service (FaaS)?

Answer 20

A cloud execution model where individual functions are executed in response to events.

Question 21

What are the benefits of serverless computing?

Answer 21

• Automatic Scaling
• Cost Efficiency
• Reduced Operational Overhead

Question 22

Name popular FaaS providers.

Answer 22

• AWS Lambda
• Google Cloud Functions
• Azure Functions

Question 23

What are cloud-native applications?

Answer 23

Applications designed specifically for cloud environments.

Question 24

What architecture do cloud-native applications leverage?

Answer 24

• Microservices Architecture
• Containerization
• Orchestration
• CI/CD Pipelines

Question 25

Define Microservices Architecture.

Answer 25

Divides applications into modular, loosely coupled services, each responsible for a specific function.

Question 26

What is Docker?

Answer 26

A containerization platform that packages applications and dependencies into lightweight, portable containers.

Question 27

What is Kubernetes?

Answer 27

An orchestration system that manages containerized applications at scale.

Question 28

What is a service mesh?

Answer 28

A tool for adding security, reliability, and observability features to cloud native applications.

Question 29

How is a service mesh implemented?

Answer 29

As a scalable set of network proxies deployed alongside application code.

Question 30

What does the service mesh's data plane consist of?

Answer 30

Proxies that handle communication between microservices.

Question 31

What is event-driven computing?

Answer 31

A paradigm where applications respond to events, crucial for building real-time, scalable cloud applications.

Question 32

List key technologies in event-driven computing.

Answer 32

* Message Queues * Event-Driven FaaS * Stream Processing

Question 33

What is the conclusion about parallel programming in the cloud?

Answer 33

It has revolutionized modern computing, enabling efficient data processing, scalable applications, and resilient architectures.