Basics of Hashing

Duration: 9 min

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Module outline

  1. About the Course: About the Course
  2. Paper-1 & 2 | Basic Numeracy: Ratio and Proportion (Ratios), Divisibility Rules, Mixture and Alligation, Permutation and Combination, Logarithm, Number System, HCF LCM, Sequence and Series (Series), Speed Time and Distance, Percentage, Average, Mensuration and Geometry, Age Problems, Arithmetic, Statistics, Probability, Profit and Loss, Simple Interest and Compound Interest, Partnership, Speed Mathematics and Basic Mathematics, Algebra, Powers and Exponents (Surds and Indices), Time and Work, Pipe and Cistern, RSSB Specific Videos - Basic Numeracy
  3. Paper-1 & 2 | Data Interpretation: Data Interpretation
  4. Paper-1 & 2 | General Mental Ability: Mental Ability, RSSB Specific Videos - Mental Ability
  5. Paper-1 & 2 | Logical Reasoning and Analytical Ability: Series (Number and Letter Series) (Numerical Relations and Reasoning), Coding Decoding, Data Sufficiency, Non Verbal Reasoning (Spatial Aptitude) (Spatial Reasoning) (Visual Reasoning), Syllogisms, Seating Arrangements, Blood Relations, Directions (Direction Test), Analytical Reasoning (Counting Figures Reasoning), Puzzle Solving (Puzzles), Calendar, Clock, Cubes & Dices, Venn Diagram, Analogy, Ranking, Order and Sequence, Deductive and Inductive Reasoning (Logical Deduction and Induction) (Prepositional Reasoning), Data Arrangement, Logical Sequence Of Words, Crypt Arithmetic
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  7. Paper-1 | General Science: Physics, Biology, Chemistry, RSSB Specific Videos
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  9. Paper - 2 | Digital Logic Systems: Digital Systems & Boolean Basics, Logic Gates & Hardware, Combinational Circuit, Sequential Circuits
  10. Paper-2 | Database Management System: Basics of DBMS, ER Diagram, Relational Model & Functional Dependencies, Keys & Integrity Constraints, Normalization (1NF - BCNF), Decomposition Properties & 4NF, Relational Calculus, Relational Algebra, SQL, NoSQL
  11. Paper-2 | Data Structures & Algorithms: Introduction to DS, Array, Stack, Queue, Linked List, Tree, Graphs, Algorithm Analysis, Sorting Algorithms, Intro to Compilers, Hashing
  12. Paper 2 | Data Communication and Network Security: Introduction to CN, Data Communication, Data Link Layer - Ethernet, DLL: Error Control, Net Layer: IPv4 & Proto, Net Layer: IP Addressing, Application Layer, Hardware basics, Network Security, Ethical Hacking
  13. Paper-2 | Operating Systems: Introduction to OS, Process Management, Memory Management, File Management, Deadlock
  14. Paper-2 | Computer Organization and Architecture: Basics of COA, Floating Point Rep, Cache Memory Organization, Input Output Organisation, Instr Formats & Modes, Control Unit Design, Register Transfer and Microoperations, Programming the Basic Computer, Number System, Number Representation
  15. Paper 2 | System Analysis and Design: Fundamentals of Systems and Information Systems, Fundamentals of Software Engineering, SDLC and Development Approaches, Software Documentation and Software Requirements Specification (SRS), SDD and Quality Assurance, Security, Risk Management & Maintenance, Software Testing
  16. Paper-2 | C Programming: C Fundamentals, Control Flow, Functions, Arrays & Pointers, Storage Classes, Structures & Enums, DMA, Macros, Scoping & File Handling
  17. Paper 2 | OOPS , C++ , JAVA: Language Design, OOPS with C++, Java, .Net Programming, Java Fundamentals
  18. Paper 2 | Python: Introduction to Python, Tokens, Variables, Data Types, I/O, Operators & Expressions, Control Flow & Looping, Collections & Strings, Functions & Modules, File Handling & Data Analysis
  19. Emerging Trends and AI: Emerging Tech Trends, Artificial Intelligence
  20. Paper-2 | Data Processing (Ms-Office): MS Office Applications
  21. Paper-2 | Internet and Web Technologies: HTML Basics, CSS, XML, JavaScript-Basics, Internet Fundamentals, Protocols & Services, Web Publishing & Hosting, Server Side & Security, Emerging Technologies, Terms & Abbreviations, Cyber Threats and Malware Attacks, Role of Internet and Web Services, Security in Mobile and Wireless Computing
  22. Paper 2 | Pedagogy: Child Development, Theories, Concept of Pedagogy, Inclusive Education, Experiential Pedagogy, Assessment & Evaluation, Psychology, Curriculum Framework & Reforms, National Education Policy (NEP) 2020
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  24. Paper 1 - Full Mock Tests:
  25. Paper 2 - Full Mock Tests:
  26. BCI Previous Year Papers:
AI summary & chapters

AI Summary

An AI-generated summary of this video lecture.

This lecture provides an introduction to hashing, a data structure technique designed to optimize search operations. The instructor begins by contextualizing hashing within the broader scope of data structures, noting that while storage is the primary goal, search is the most frequent operation. He reviews the search complexities of various structures, such as O(n) for unsorted arrays and O(logn) for sorted arrays and AVL trees. The core of the lecture defines hashing as a method to achieve constant time O(1) search by mapping keys directly to memory addresses. It concludes by defining hash functions and introducing the concept of collisions, where distinct keys map to the same location, necessitating collision resolution strategies. The lecture sets the foundation for understanding how hashing improves efficiency over traditional linear or tree-based searches.

Chapters

  1. 0:00 – 2:00 00:00-02:00

    The instructor starts by emphasizing that the most common operation in data structures is search, not insertion or deletion. He presents a slide listing search complexities for different structures: Unsorted array O(n), sorted array O(logn), linked list O(n), BT O(n), BST O(n), and AVL O(logn). To illustrate why these take time, he draws red diagrams next to the list. He sketches rectangular blocks for arrays and linked nodes for linked lists, showing arrows indicating a sequential traversal to find an element. He specifically crosses out 'Unsorted array' and 'BT' and 'BST' while keeping 'sorted array' and 'AVL' to contrast complexities. He underlines that search time depends on the number of elements and the structure type.

  2. 2:00 – 5:00 02:00-05:00

    The topic shifts to hashing, defined on the slide as a technique where search time is independent of the number of items. The instructor explains the basic idea: using the key itself to find the memory address. He gives examples like phone numbers, roll numbers, or Aadhar cards. A diagram shows a list of keys on the left mapping to a table of buckets in the middle. He explains that a hash function converts a key into a smaller practical number to use as an index. He highlights the text 'access the element in O(1) time' with a red circle. He also points out 'overflow entries' in the diagram, showing how extra data is handled when a bucket is full. He draws a red arrow from a key to a bucket index, illustrating the direct mapping process. He mentions that the hash function must be modified so a great deal of space is not wasted.

  3. 5:00 – 8:50 05:00-08:50

    The instructor formally defines the hash function as a conversion from a set of keys K to a set of memory locations L, written as H: K -> L. He explains that it maps a big number or string to a small integer. He then introduces 'Collision', explaining that two different keys K1 and K2 might yield the same hash address. He writes H(K1) and H(K2) on the board with arrows pointing to the same location L. He states that the technique to resolve this is called collision resolution. He draws a diagram showing n < m (keys less than locations) but notes collisions can still happen. He underlines the definition of collision on the slide. He explains that even if the number of keys is less than the number of locations, collisions are possible.

The lecture effectively bridges the gap between traditional data structures and hashing. It starts by establishing the problem: search operations in structures like arrays and trees are not constant time. It then proposes hashing as the solution, offering O(1) access. The instructor details the mechanism of hash functions and the inevitable issue of collisions, setting the stage for learning how to handle them. This progression moves from problem identification to solution definition and finally to the specific challenges of the solution, providing a comprehensive overview of the hashing concept.

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