YARN

Duration: 5 min

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Inside: a video lesson and guided study material.

Module outline

  1. Quantitative Aptitude: Number System, Divisibility Rules, HCF LCM, Percentage, Ratio and Proportion (Ratios), Average, Profit and Loss, Simple Interest and Compound Interest, Mixture and Alligation, Partnership, Age Problems, Time and Work, Pipe and Cistern, Speed Time and Distance, Algebra, Arithmetic, Data Interpretation, Sequence and Series (Series), Logarithm, Powers and Exponents (Surds and Indices), Permutation and Combination, Probability, Speed Mathematics and Basic Mathematics, Trigonometry
  2. Logical Reasoning: Coding Decoding, Blood Relations, Directions (Direction Test), Ranking, Order and Sequence, Seating Arrangements, Puzzle Solving (Puzzles), Data Arrangement, Syllogisms, Inequality, Data Sufficiency, Deductive and Inductive Reasoning (Logical Deduction and Induction) (Prepositional Reasoning), Series (Number and Letter Series) (Numerical Relations and Reasoning), Venn Diagram, Logical Sequence Of Words, Calendar, Clock, Cubes & Dices, Non Verbal Reasoning (Spatial Aptitude) (Spatial Reasoning) (Visual Reasoning)
  3. Verbal Ability: Noun, Pronoun, Adjectives, Verb, Adverb, Tenses, Subject Verb Agreement (Verb Noun Agreement), Articles, Preposition, Conjunction, Modals, Determiner, Vocabulary, Comprehension / Reading Comprehension / Unseen Passages (Critical Reasoning) (Paragraph Questions), Cloze Test (Cloze Passage), Sentence Correction (Error Correction), Sentence Completion (Fill in the blanks), Sentence Re-arrangements (Para Jumbles) (Narrative Sequencing), Active Passive Voice (Voice), Direct and Indirect Speech, Sentence Construction
  4. Data Structures (Domain Test): Introduction to DS, Array, Stack, Queue, Linked List, Tree, Graphs, Hashing
  5. Algorithms (Domain Test): Algorithm Analysis, Sorting Algorithms, Time Complexity Analysis, Greedy Algorithms
  6. OOPs (Domain Test): Object Oriented Programming (OOPS)
  7. DBMS (Domain Test): Basics of DBMS, ER Diagram, Relational Model & Functional Dependencies, Keys & Integrity Constraints, Normalization (1NF - BCNF), Decomposition Properties & 4NF, File Organization & Indexing, Relational Algebra, Relational Calculus, Transaction Management, Concurrency Control, Database Recovery, ORDBMS, Database Security & Authorization, Query Processing & Optimization, Enhanced Data Models, Data Warehousing & Mining, Big Data Systems, NoSQL
  8. SQL (Domain Test): SQL
  9. Operating Systems (Domain Test): Introduction to OS, Process Management, CPU Scheduling, Process Synchronization, Deadlock, Threads & Process Creation, Memory Management, Virtual Memory, Disc Scheduling, File Management, Windows OS, Linux OS, Security, Distributed Systems, Virtual Machines
  10. Computer Networks (Domain Test): Introduction to CN, Data Communication, DLL: Access Control, DLL: Flow Control, DLL: Error Control, DLL: Framing, Data Link Layer - Ethernet, Net Layer: IPv4 & Proto, Net Layer: IP Addressing, Net Layer:Routing Protocol, Transport Layer Services, TL: Congestion & UDP, Application Layer, Hardware basics, Network Security, Mobile Technology, Cloud Computing and IoT, Cyber and Info Security
  11. Coding: Coding Questions by Yash Sir, C Programming by Yash Sir, Programming in C++, Java, Python for Placements by Yash Sir
  12. Written English Test: English Writing Ability
  13. Psychometric Test: Behavioral Assessment (Behavioral Competency Profiling) (Psychometric Test)
AI summary & chapters

AI Summary

An AI-generated summary of this video lecture.

The video is a lecture on the YARN (Yet Another Resource Negotiator) architecture, focusing on its two main components: the ResourceManager and the NodeManager. The instructor begins by explaining the ResourceManager, which operates at the cluster level and runs on the master machine. It is responsible for managing resources and scheduling applications, and it has two key components: the Scheduler, which allocates resources, and the ApplicationMaster, which negotiates the first container for job execution. The instructor then transitions to the NodeManager, which runs on each slave machine and is responsible for managing containers, monitoring resource utilization, and communicating with the ResourceManager. The lecture uses a PDF document as a visual aid, with the instructor adding handwritten annotations to highlight key concepts and relationships, such as the connection between YARN, Hadoop, and HDFS.

Chapters

  1. 0:00 – 2:00 00:00-02:00

    The video starts with a lecture on the YARN architecture, focusing on the ResourceManager. The instructor explains that the ResourceManager is a cluster-level component that runs on the master machine and manages resources and schedules applications. It has two components: the Scheduler, which allocates resources, and the ApplicationManager, which accepts job submissions and negotiates the first container for execution. The instructor also notes that the ResourceManager keeps track of heartbeats from the NodeManager. On-screen text from the PDF includes the heading "Resource Manager and Node Manager" and bullet points detailing the ResourceManager's functions. The instructor adds handwritten annotations like "YARN" and "Hadoop" to the document, visually linking the concepts.

  2. 2:00 – 4:40 02:00-04:40

    The lecture transitions to the NodeManager. The instructor explains that the NodeManager is a node-level component that runs on each slave machine. Its responsibilities include managing containers, monitoring resource utilization, and handling log management. It also continuously communicates with the ResourceManager to stay up-to-date. The instructor highlights the text "NodeManager" and adds handwritten notes like "Name Node" and "Data Node" to the document, connecting the NodeManager to the broader HDFS architecture. The on-screen text describes the NodeManager's role in managing containers and monitoring resource utilization, and the instructor emphasizes its communication with the ResourceManager.

The video provides a structured overview of the YARN architecture by first detailing the central role of the ResourceManager, which acts as the cluster's master, and then explaining the distributed role of the NodeManager on each slave node. The lecture effectively uses a combination of the provided PDF text and handwritten annotations to illustrate the hierarchical relationship between these components and their interaction within the Hadoop ecosystem, emphasizing the division of labor between cluster-level and node-level management.

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