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If you read up on hashing, why hashing is done, what are its uses. Then you will be able to answer your own question. More to the point you will have studied the material that your homework question is intended to make you study. It is educational.

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What is double hashing in data structure?

if collision is occurred in hash function then we can solve this problem by using double hash function


Define hashing and describe briefly including types of hashing and where it is used and advantages and disadvantages of hashing?

Hashing is performed on arbitrary data by a hash function. A hash function is any function that can convert data to either a number or an alphanumeric code. There are possibly as many types of hashing as there are data. How precisely the hash function works depends on what data it is meant to generate a hash code from. Hashing is used for a variety of things. For example, a hash table is a data structure used for storing data in memory. Instead of iterating through the structure to find a specific item, we associate a key (hash code) to a particular item (data). A hash code can be generated from a file or disk image. If the data does not match the code, then the data is assumed to be corrupted. Hashing has the advantage of taking a larger amount of data and representing it as a smaller amount of data (hash code). The code generated is unique to the data it came from. Generating a hash code can take time however, depending on the function and the data. Some hash functions include Bernstein hash, Fowler-Noll-Vo hash, Jenkins hash, MurmurHash, Pearson hashing and Zobrist hashing.


How does bucket hashing work to efficiently distribute data into different buckets based on a specific hashing function?

Bucket hashing works by using a hashing function to assign each data item to a specific bucket. The hashing function calculates a unique hash value for each item, which determines the bucket it belongs to. This helps distribute the data evenly across different buckets, making it easier to retrieve and manage the data efficiently.


What are hashing techniques that allow dynamic file expansion in dbms?

Dynamic hashing techniques, such as Extendible Hashing and Linear Hashing, allow for efficient file expansion in database management systems (DBMS). Extendible Hashing uses a directory structure that can grow as needed, allowing new buckets to be created without reorganizing existing data. Linear Hashing incrementally splits buckets based on a predetermined growth factor, enabling dynamic adjustment of the hash structure while maintaining efficient access. These techniques help manage variable data sizes and maintain performance as data volume changes.


Which hashing function includes 128-bit hash value and is often used to verify the intergrity of data?

MD5


What is Homomorphic Hashing?

Homomorphic Hashing is a algorithm technique used for verifying data.


Hashing in DBMS?

Hashing is the technique of to retrieving the datas in the database. for example,we created one index for one main table,so how we can retrieve the index from that main table? ans- to using one function we can retrieve the data,that function is called hash function. hash function format is h(search key)=pointer or bucket identifier.


Why do you use hashing and not array?

Hashing provides a method to search for data.Hashing provides a method to search for data.Hashing provides a method to search for data.Hashing provides a method to search for data.


In dbms what is indexes and hashing techniques?

Indexes in DBMS are data structures used to quickly retrieve data based on specific columns in a table. They allow for faster query processing by reducing the number of records that need to be scanned. Hashing techniques in DBMS involve converting data into a hashed value using a hash function, which is then used to index or organize the data for faster retrieval. Hashing provides quick access to data by generating a unique location for each record based on its hash value.


Explain the distinction between closed an open hashing Discuss the relative merits of each technique in database application?

A hash table is where data storage for a key-value pair is done by generating an index using a hash function. Open Hashing (aka Separate chaining) is simpler to implement, and more efficient for large records or sparse tables. Closed Hashing (aka Open Addressing) is more complex but can be more efficient, especially for small data records.


How does hashing work in computer science and what are its applications in data security and encryption?

Hashing in computer science involves taking input data and generating a fixed-size string of characters, known as a hash value, using a specific algorithm. This hash value is unique to the input data and is used for various purposes, including data security and encryption. In data security, hashing is used to verify the integrity of data by comparing hash values before and after transmission or storage. If the hash values match, it indicates that the data has not been tampered with. Hashing is also used in password storage, where passwords are hashed before being stored in a database to protect them from unauthorized access. In encryption, hashing is used to securely store sensitive information, such as credit card numbers or personal data. Hashing algorithms are also used in digital signatures to verify the authenticity of a message or document. Overall, hashing plays a crucial role in data security and encryption by providing a way to securely store and verify data integrity.


What does hashing mean and how is it used in computer science and cryptography?

Hashing is a process in computer science and cryptography where data is converted into a fixed-size string of characters, known as a hash value. This hash value is unique to the input data and is used for various purposes such as data retrieval, data integrity verification, and password storage. In cryptography, hashing is used to securely store passwords and verify data integrity by comparing hash values.