Big Data Systems Overview
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Questions and Answers

What is the main purpose of scheduling in data center operations?

  • To track software versioning for development projects
  • To enhance data security protocols in cloud environments
  • To improve user interface design for applications
  • To optimize resource allocation and task execution timing (correct)

Which statement about virtualization is true?

  • Virtualization prevents resource sharing among applications
  • Virtualization increases hardware costs by requiring more physical machines
  • Virtualization allows multiple operating systems to run on a single physical machine (correct)
  • Virtualization eliminates the need for physical servers entirely

How does Docker relate to virtualization?

  • Docker is a type of hypervisor that manages virtual machines
  • Docker provides application containerization without the overhead of full virtual machines (correct)
  • Docker eliminates the use of operating systems altogether
  • Docker is primarily concerned with network management rather than resource allocation

Why is scheduling considered important in cloud computing?

<p>It ensures efficient use of cloud resources and minimizes latency (C)</p> Signup and view all the answers

Which of the following is a common misconception about virtualization?

<p>Virtualization only benefits large enterprises (B)</p> Signup and view all the answers

What is primarily managed by the Docker Engine?

<p>Docker containers (D)</p> Signup and view all the answers

Which of the following best describes a Docker image?

<p>A read-only template for creating containers (D)</p> Signup and view all the answers

Which of these is NOT a function of cluster schedulers?

<p>Creating Docker images (D)</p> Signup and view all the answers

What is the main function of Docker Hub?

<p>To host public images for Docker (B)</p> Signup and view all the answers

Which of the following tools is NOT an example of a cluster scheduler?

<p>Apache (D)</p> Signup and view all the answers

In terms of resource negotiation with clients, what are cluster schedulers managing?

<p>Resource bundles such as CPU and memory (B)</p> Signup and view all the answers

How does Docker primarily ease deployment compared to virtual machines?

<p>By simplifying the application lifecycle (C)</p> Signup and view all the answers

What structure do Docker images utilize?

<p>Layered structure based on Union File Systems (C)</p> Signup and view all the answers

What is the average completion time using Shortest Task First (STF) scheduling?

<p>9.66 (C)</p> Signup and view all the answers

Which of the following statements about First-In First-Out (FIFO) scheduling is true?

<p>It maintains jobs in order of arrival. (A)</p> Signup and view all the answers

What is a characteristic of Round-Robin scheduling?

<p>It uses a time quantum to segment job execution. (A)</p> Signup and view all the answers

In Hadoop's Fair Scheduler, what happens when one pool has a minimum share?

<p>It guarantees a minimum percentage of the cluster. (D)</p> Signup and view all the answers

What is the primary requirement for cloud scheduling mentioned in the content?

<p>Ensuring every user makes progress. (C)</p> Signup and view all the answers

What does the Hadoop Capacity Scheduler use to manage tenant resources?

<p>Multiple queues for each tenant. (A)</p> Signup and view all the answers

Which of the following is NOT a feature of Shortest Task First scheduling?

<p>Decreasing starvation of longer jobs. (D)</p> Signup and view all the answers

In which type of scheduling is preemption commonly used?

<p>Round-Robin Scheduling. (C)</p> Signup and view all the answers

How does the priority scheduling model affect Shortest Task First scheduling?

<p>It can lead to starvation of lower priority jobs. (A)</p> Signup and view all the answers

What limitation does the Hadoop Capacity Scheduler impose on job management?

<p>Changes to queue limits only after job completion. (D)</p> Signup and view all the answers

Which scheduling technique is designed to minimize the wait time for interactive responses?

<p>Round-Robin Scheduling. (D)</p> Signup and view all the answers

What is the main design of the Hadoop Fair Scheduler regarding job execution?

<p>Each job has an equal chance to utilize the full cluster. (B)</p> Signup and view all the answers

What happens to jobs in the queue during Round-Robin Scheduling once they are preempted?

<p>They are added to the end of the queue. (D)</p> Signup and view all the answers

Flashcards

Docker

A platform that provides tools for creating, distributing, and deploying applications using containers.

Docker Hub

A public repository where users can store, share, and download Docker images.

Docker Engine

The core tool for managing Docker containers. It acts as a client-server application that allows users to control and execute Docker objects.

Docker Image

A read-only template that contains instructions for creating a Docker container.

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Dockerfile

A file that contains all the instructions for building a Docker image. It defines the image's layers and dependencies.

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Container Orchestration Systems

Software systems that help manage a cluster of computers by automating tasks such as container scheduling, deploying, and managing.

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Cluster Scheduling

The process of distributing tasks and resources to different computers in a cluster.

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Container Scheduling Tools

A collection of software tools that help organizations manage their containers at scale.

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Data Center

A physical facility that houses computer systems and associated equipment, providing the infrastructure for large-scale data processing and storage.

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Virtualization

The process of running multiple virtual machines (VMs) on a single physical server, enabling resource sharing and efficient utilization of hardware.

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Scheduling

A mechanism to allocate computational resources (e.g., CPU, memory) to different tasks or applications running on a system.

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Cloud Computing

A model of delivering computing services - like servers, storage, databases - over the internet, enabling on-demand access and pay-as-you-go pricing.

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First-In First-Out (FIFO) Scheduling

A scheduling algorithm where jobs are executed in the order they arrive in the queue. The job at the head of the queue is processed first, and the process continues until the queue is empty.

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Average Completion Time (FIFO)

The average time taken for all jobs to complete in a FIFO scheduling system.

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Shortest Task First (STF) Scheduling

A scheduling algorithm where jobs are prioritized based on their execution time. The shortest job is executed first, followed by the next shortest, and so on.

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Average Completion Time (STF)

The average completion time for all jobs in an STF scheduling system.

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Priority Scheduling

A type of scheduling where jobs are given priority based on their importance. The most important jobs are executed first, followed by the next most important, and so on.

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Round-Robin Scheduling

A scheduling algorithm that divides a process into smaller time units, called quanta, and runs a portion of the task at the head of the queue for each quanta.

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Quantum

The time allocated to a process in a Round-Robin scheduling system.

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Cloud Scheduling

A scheduling system that allows multiple users to share computing resources. Each user or group of users can access the resources and run their jobs independently.

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Tenant

A user or group of users that access resources in a cloud scheduling system.

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Hadoop Capacity Scheduler

A scheduler in Hadoop that manages resources based on fixed capacities for each queue or tenant.

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Queue

A dedicated space for a user or group of users in a Hadoop Capacity Scheduler. Each queue represents a 'reservation' of cluster resources.

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Hadoop Fair Scheduler

A scheduling algorithm that ensures all users have equal access to cluster resources, regardless of the number of jobs they submit.

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Pool

A virtualized environment where multiple jobs are grouped together on a single server.

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Minimum Shares

A feature in the Hadoop Fair Scheduler that allows a user or pool to receive a minimum percentage of cluster resources

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Limits on Max Jobs

A feature in the Hadoop Fair Scheduler where a user or pool can be limited in the number of jobs they can submit.

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Study Notes

Big Data Systems

  • The presentation covers Big Data Systems, Data Centers, and Cloud Computing.
  • The presenter, Martin Boissier, from the Hasso-Plattner-Institut, is the source of much of the information
  • The course material involves a timeline of topics and lectures, and there is a diagram showing the relationships between the various system components/levels
  • A fundamental concept of Data Centers is discussed, including an anatomy of a datacenter

Timeline of Topics

  • Topics covered include Introduction and Organizational Overview, Performance Management, Map Reduce I, Map Reduce II, Data Centers, File Systems, Key Value Stores I & II, Key Value Stores III, Stream Processing I & II, and Machine Learning Systems I.

Data Centers

  • Large-scale facilities housing a considerable number of servers.
  • Contains multiple rack systems, and a high number of servers.
  • Includes various hardware components, including servers, RAM, and hard drives.
  • Numbering greater than 100,000 servers are common, e.g. Google Data Centers
  • Commodity CPUs are a key component, such as the Xeon E5-2440 or Xeon Gold 6148.

Virtualization

  • Abstracting the operating system from the hardware, enabling multiple operating systems and applications on a single server.
  • This reduces costs, improves efficiency, and allows for easier management and scaling of resources.

Scheduling

  • Managing the allocation of resources, like CPU, memory, and disk space, to optimize performance and resource utilization.
  • Different scheduling algorithms, like First-In-First-Out (FIFO), Shortest Task First (STF), and Round Robin, are used to schedule concurrent jobs in a cluster.
  • Various schedulers such as Kubernetes, Mesos, YARN, Amazon ECS, Microsoft ACS, and Docker Swarm.

Cloud Computing

  • On-demand access to a shared pool of computing resources, including storage, servers, and networking.
  • Service models: IaaS, PaaS, SaaS.
  • Public, private and hybrid clouds.
  • Transformation of the IT industry

Fault Tolerance (Google)

  • Frequent issues within data centers include overheating, Power Distribution Unit (PDU) failures, rack moves, and network problems.
  • There are numerous types of failures, including outages, bandwidth/connectivity issues, and hard drive failures.

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Big Data Systems: Data Center and Cloud Computing PDF

Description

Explore the essential concepts of Big Data Systems, including Data Centers and Cloud Computing. This quiz covers the components and relationships within data management systems, along with a detailed timeline of relevant topics. Understand the anatomy of a data center and gain insights into performance management and key value stores.

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