Double Hashing

Duration: 2 min

This video lesson is available to enrolled students.

Return to /learn/COGNIZANT-PREPARATION/data-structures/hashing/open-addressing-probing/asset-double-hashing after enrolling

Inside: a video lesson and guided study material.

Module outline

  1. Communication Round: Vocabulary, Subject Verb Agreement (Verb Noun Agreement), Tenses, 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), Direct and Indirect Speech, Active Passive Voice (Voice), Verbal Analogy (Word Based Analogy), Articles, Preposition, Conjunction, Sentence Construction, English Writing Ability, Communication Assessment
  2. Quantitative Aptitude: Ratio and Proportion (Ratios), Divisibility Rules, Data Interpretation, Mixture and Alligation, Permutation and Combination, Logarithm, Number System, HCF LCM, Speed Time and Distance, Percentage, Average, Powers and Exponents (Surds and Indices), Time and Work, Mensuration and Geometry, Age Problems, Pipe and Cistern, Probability, Profit and Loss, Simple Interest and Compound Interest, Algebra
  3. Analytical and Logical Reasoning: Series (Number and Letter Series) (Numerical Relations and Reasoning), Coding Decoding, Data Sufficiency, Non Verbal Reasoning (Spatial Aptitude) (Spatial Reasoning) (Visual Reasoning), Directions (Direction Test), Ranking, Order and Sequence, Deductive and Inductive Reasoning (Logical Deduction and Induction) (Prepositional Reasoning), Selection Decision Table (Decision Making), Logical Sequence Of Words, Puzzle Solving (Puzzles), Syllogisms, Seating Arrangements, Calendar, Clock, Blood Relations, Cubes & Dices, Venn Diagram, Analytical Reasoning (Counting Figures Reasoning)
  4. Cognizant Gaming Aptitude: Gamified / Game Based Aptitude
  5. Java (Cluster 1): Java
  6. ANSI SQL MySQL (Cluster 1,2,3): SQL
  7. HTML, CSS, JavaScript (Cluster 1,3): HTML, CSS, JavaScript
  8. Python (Cluster 2): Python for Placements by Yash Sir
  9. Cloud Fundamentals (Cluster 2): Emerging Tech Trends
  10. C# (Cluster 3): C#
  11. OOPs: Object Oriented Programming (OOPS)
  12. Technical Assessment (Coding): Coding Questions by Yash Sir, C Programming by Yash Sir, Programming in C++, Pseudo Codes
  13. Data Structures: Introduction to DS, Array, Stack, Queue, Linked List, Tree, Graphs, Hashing
  14. DBMS: 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
  15. Operating Systems: 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
  16. Computer Networks: 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
AI summary & chapters

AI Summary

An AI-generated summary of this video lecture.

The video lecture provides a comprehensive introduction to Double Hashing, a collision resolution technique used in hash tables with open-addressing. The instructor, Sanchit Jain Sir, explains that double hashing uses a secondary hash of the key as an offset when a collision occurs. He contrasts this with linear and quadratic probing, noting that in double hashing, the interval depends on the data, which minimizes repeated collisions and clustering. The instructor writes the probe sequence formula $h_i(k) = (h_1(k) + i \cdot h_2(k)) \pmod m$ on the screen. He defines $h_1(k)$ as the primary hash function and $h_2(k)$ as the secondary hash function. He specifies that $h_1$ maps to $[0, |T|-1]$ and $h_2$ maps to $[1, |T|-1]$. The variable $i$ represents the probe number, starting from 0. The lecture emphasizes that $h_1$ and $h_2$ should be independent and uniform to approximate a random distribution. The slide text further explains that pair-wise independent hash functions yield a probability of $(h_1/|T|)^2$ that any pair of keys will follow the same bucket sequence.

Chapters

  1. 0:00 – 2:00 00:00-02:00

    The instructor introduces Double Hashing, writing the formula $h_i(k) = (h_1(k) + i \cdot h_2(k)) \pmod m$ on the screen. He explains that unlike linear probing, the step size is determined by a second hash function $h_2(k)$. He writes $i=0, 1, 2$ to demonstrate the iteration. The slide text defines the technique and mentions minimizing repeated collisions. He details the ranges for $h_1$ and $h_2$ as $[0, |T|-1]$ and $[1, |T|-1]$ respectively. He also mentions that $h_1$ and $h_2$ are selected from a set of universal hash functions.

  2. 2:00 – 2:10 02:00-02:10

    The instructor concludes the explanation of the formula's components. He highlights the independence of the hash functions to ensure a random distribution. He mentions that pair-wise independent hash functions yield a probability of $(h_1/|T|)^2$ that any pair of keys will follow the same bucket sequence, ensuring minimal clustering. He reiterates that this method approximates a random distribution effectively.

The lesson progresses from a high-level definition of double hashing to a detailed breakdown of its probe sequence formula. By writing the equation $h_i(k) = (h_1(k) + i \cdot h_2(k)) \pmod m$, the instructor clarifies how the secondary hash function determines the step size, effectively solving the primary clustering issues found in linear probing. The constraints on the ranges of $h_1$ and $h_2$ are crucial for ensuring that the entire table is probed.

Loading lesson…