Hashing Techniques in Data Structures
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Hashing Techniques in Data Structures

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Questions and Answers

What is the primary purpose of hashing in data structures?

  • To perform complex calculations quickly
  • To minimize data storage requirements
  • To organize data in a linear sequence
  • To optimize search operations with minimal comparisons (correct)

    • What characteristic of hashing allows for fast data access?

  • It relies on updating data sequentially
  • It uses linear search algorithms
  • It generates unique hash values from keys (correct)
  • It sorts data before insertion

    • In ideal scenarios, what is the time complexity for search, insert, and delete operations in hashing?

  • O(log n)
  • O(n)
  • O(n log n)
  • O(1) (correct)

    • What does the hash function do in the hashing process?

    <p>It transforms keys into numeric indexes within a defined range</p> Signup and view all the answers

    What is the result of applying a hash function to a key in hashing?

    <p>A unique integer that serves as an index in the hash table</p> Signup and view all the answers

    What is the purpose of a hash function in a hash table?

    <p>To compute an index from the data for fast retrieval</p> Signup and view all the answers

    Which collision resolution technique involves checking the next available slot sequentially until an empty one is found?

    <p>Linear Probing</p> Signup and view all the answers

    In the context of a hash table, what do you call the small integer value returned by a hash function?

    <p>Hash Value</p> Signup and view all the answers

    What happens in a hash table when two keys produce the same hash value?

    <p>A collision occurs</p> Signup and view all the answers

    What is the main characteristic of a hash table regarding the items it stores?

    <p>It only contains unique elements</p> Signup and view all the answers

    Study Notes

    Hashing Technique

    • Hashing in data structures maps data items to specific locations (buckets) in a hash table.
    • This enables efficient data storage and retrieval.
    • Hashing is a well-known technique for searching elements within a set of data.
    • It's highly efficient for storing, retrieving, and handling data by converting keys into specific locations.

    Hash Tables

    • A hash table uses an array data structure for storing data items.
    • The hash function calculates a unique integer value (hash value) from a data item or key.
    • This hash value corresponds to an index in the hash table where the data is stored..
    • Data items are inserted into the hash table based on their hash values.

    Hash Value

    • A hash key value is a special value used as an index for a data item.
    • It determines where a data item should be stored in the hash table.
    • The hash key value is generated using a hash function.

    Hash Function

    • The hash function converts a range of key values into a range of indexes.
    • It's crucial for the efficiency of hashing by distributing data evenly throughout the hash table.
    • A good hash function minimizes collisions (when two keys produce the same hash value).
    • It's essential that hash function's mathematical or bitwise operations are efficient to compute.

    Hash Table

    • A hash table (or hash map) is a data structure that holds key-value pairs for easy access later.
    • It's a collection of items enabling fast retrieval of data stored based on keys.

    Collision Resolution Techniques

    • Collisions occur when two keys produce the same hash value.
    • Techniques handle collisions:
      • Linear Probing: Finds the next available slot sequentially.
      • Quadratic Probing: Uses a quadratic function to find slots reduce clustering.
      • Double Hashing: Uses a second hash function to calculate the next probing step.
      • Chaining: Stores elements that hash to the same index in a linked list.

    Open Addressing

    • In open addressing, if a collision occurs, the hash table tries alternative slots until an empty slot is found.

    Quadratic Probing

    • If a slot calculated by a hash function is full, quadratic probing tries the next slot based on a quadratic equation until a free slot is found.

    Separate Chaining

    • Separate chaining manages collisions by storing elements with the same hash index in a linked list at that index.

    Load Factor

    • The load factor (á) represents the utilization of the hash table.
    • It's calculated by dividing the number of occupied table elements by the table size.
    • Ideally, the load factor should be below a certain threshold (e.g., 0.75) to maintain good performance and avoid severe collisions, especially in open addressing methods.

    Rehashing

    • Rehashing involves increasing the table size when it becomes too full.
    • This improves efficiency by distributing data more evenly to minimize collisions and improve search and insertion times in the hash table.

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    Hashing Technique PDF

    Description

    This quiz explores hashing techniques used in data structures, specifically focusing on hash tables and their functions. Understand how hash functions and hash values contribute to efficient data storage and retrieval. Test your knowledge on the fundamental concepts of hashing and its applications in computer science.

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