Basics of Hashing

Duration: 9 min

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Module outline

  1. About the Course: About the Course
  2. Section 1 | Language (Hindi): भाषा, लिपि, ध्वनि, वर्ण, अक्षर, स्वर, व्यंजन, मात्रा और संयुक्ताक्षर, वर्तनी, वर्ण-विन्यास, अनुस्वार, अनुनासिक, चंद्रबिंदु और ‘र’ के रूप, शब्द, पद और शब्द-भेद, संज्ञा और सर्वनाम, विशेषण और क्रिया, लिंग, वचन, पुरुष और कारक, काल, वाच्य, वाक्य और वाक्य-भेद, संधि, समास, विलोम शब्द, पर्यायवाची शब्द, सामान्य अशुद्धियाँ, अनेक शब्दों के लिए एक शब्द, मुहावरे और लोकोक्तियाँ, अपठित गद्यांश और अपठित पद्यांश, Multi-Topic Content (Cross-Concept Material), वर्णमाला
  3. Section 1 | Language (उर्दू भाषा — 22 प्रश्न (निश्चित)): Spelling & Diacritics, Grammar (اسم, فعل, صفت, ضمیر), Vocabulary, Idioms & Proverbs, Comprehension
  4. Section 1 | Language (বাংলা / बांग्ला भाषा — 22 प्रश्न (निश्चित)): Bangla Script and Sounds, Bangla Grammar and Usage, Bangla Word Formation and Vocabulary, Reading and Text Interpretation
  5. Section 1 | Language (English): Vocabulary, Noun, Subject Verb Agreement (Verb Noun Agreement), Adjectives, Tenses, Pronoun, Verb, Adverb, Preposition, Articles, Determiner, Conjunction, Modals, Active Passive Voice (Voice), Direct and Indirect Speech, Sentence Correction (Error Correction), Sentence Completion (Fill in the blanks), Sentence Construction, Sentence Re-arrangements (Para Jumbles) (Narrative Sequencing), Comprehension / Reading Comprehension / Unseen Passages (Critical Reasoning) (Paragraph Questions), Cloze Test (Cloze Passage), Verbal Analogy (Word Based Analogy), Facts, Inference and Judgements
  6. Section 2 | Primary Maths & Reasoning: Ratio and Proportion (Ratios), Divisibility Rules, Mixture and Alligation, Permutation and Combination, Number System, HCF LCM, Sequence and Series (Series), Speed Time and Distance, Series (Number and Letter Series) (Numerical Relations and Reasoning), Coding Decoding, Non Verbal Reasoning (Spatial Aptitude) (Spatial Reasoning) (Visual Reasoning), Percentage, Average, Profit and Loss, Simple Interest and Compound Interest, Time and Work, Mensuration and Geometry, Age Problems, Arithmetic, Powers and Exponents (Surds and Indices), Algebra, Probability, Trigonometry, Syllogisms, Seating Arrangements, Blood Relations, Directions (Direction Test), Analytical Reasoning (Counting Figures Reasoning), Puzzle Solving (Puzzles), Calendar, Clock, Cubes & Dices, Venn Diagram, Data Arrangement, Inequality, Analogy, Ranking, Order and Sequence
  7. Section 2 | General Awareness (GK + Current Affairs): Polity, Physics, Biology, State Wise GK, Chemistry, History, Geography, Indian Economy, Environment, GK- Current Affairs, Static General Knowledge
  8. Section 3 | Computer System and Org. (CSO): Basics of COA, Floating Point Rep, Cache Memory Organization, Instr Formats & Modes, Programming the Basic Computer, Input Output Organisation, Register Transfer and Microoperations, Control Unit Design
  9. Section 3 | Database Management System: Basics of DBMS, ER Diagram, Relational Model & Functional Dependencies, Keys & Integrity Constraints, Normalization (1NF - BCNF), Decomposition Properties & 4NF, SQL, File Organization & Indexing, Relational Algebra, Relational Calculus, Transaction Management, Concurrency Control
  10. Section 3 | Operating System: Introduction to OS, Process Management, CPU Scheduling, Threads & Process Creation, Memory Management, Virtual Memory, Disc Scheduling, File Management, Process Synchronization
  11. Section 3 | Computer Networks: Introduction to CN, Data Communication, DLL: Access Control, DLL: Flow Control, DLL: Error Control, Data Link Layer - Ethernet, Net Layer: IPv4 & Proto, Net Layer: IP Addressing, Transport Layer Services, TL: Congestion & UDP, Application Layer, Hardware basics
  12. Section 3 | Data Structures: Introduction to DS, Array, Stack, Queue, Linked List, Tree, Graphs, Hashing, Algorithm Analysis, Time Complexity Analysis, Sorting Algorithms, Greedy Algorithms, Minimum Spanning Trees, Shortest Path Algos
  13. Section 3 | Theory Of Computation & Compiler Design: Introduction to TOC, Deterministic FA (DFA), Non-Deterministic FA, Regular Expressions, Grammar, Regular Language Properties, Moore & Mealy Machines, Pushdown Automata & CFG, Turing Machines, Intro to Compilers, Lexical Analysis, Grammar & CFG, Syntax Analysis: Top-Down, Syntax Analysis: Bottom-Up, Semantic Analysis & SDT, Intermediate Code Gen, Code Optimization
  14. Section 3 | Emerging Trends (AI, Societal Ethics & MS Office): Artificial Intelligence, Emerging Tech Trends, Society, Law & Ethics, MS Office Applications
  15. Section 3 | Software Engineering: Fundamentals of Software Engineering, Software Requirements and Quality Assurance, Software Design, Estimation and Metrics, Software Maintenance and Configuration Management, Software Testing
  16. Section 3 | C Programming: C Fundamentals, Control Flow, Functions, Arrays & Pointers, Storage Classes, Structures & Enums, DMA, Macros, Scoping & File Handling
  17. Section 3 | OOPS, C++, JAVA, HTML: OOPS with C++, Java, HTML Basics, CSS
  18. Section 3 | Java: Java Fundamentals, Array, String, IO & References
  19. Section 3 | Python: Introduction to Python, Tokens, Variables, Data Types, I/O, Operators & Expressions, Control Flow & Looping, Collections & Strings, Functions & Modules, File Handling & Data Analysis
  20. Section 3 | Digital Electronics: Digital Systems & Boolean Basics, Logic Gates & Hardware, Boolean Expression, Boolean Minimization, Combinational Circuit, Sequential Circuits, Number System, Number Representation
  21. Section 3 | Multimedia: Multimedia
  22. BPSC Previous Year Papers:
  23. BPSC Full Mock Tests:
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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