A Hash Index is a data structure used in databases to facilitate fast data retrieval. It’s based on the concept of hash functions.
#How it works
- Hash Indexes use a hash function to map keys (eg column values) to specific locations in memory.
- Each unique key generates a hash value, which is used as an index to access the associated data. https://visualgo.net/en/hashtable
#Pros and Cons of Hash Indexes
#Benefits
- Fast Retrieval
- Hash indexes offer constant-time (O(1)) retrieval, making them exceptionally fast for exact-mach queries.
- No Sorting
- Data is stored in an unordered fashion, eliminating the need for sorting.
- Ideal for scenarios where sorting is not a requirement.
#Challenges
- Collisions
- Hash collisions occur when two different keys produce the same hash value.
- Collision resolution techniques (eg chaining, open addressing) are used to handle this issue.
#Use Cases and Limitations
#Use Cases
- Hash indexes are highly effective for primary key and exact-match lookups.
- Commonly used in in-memory databases and scenarios where retrieval speed is paramount.
#Limitations
- Inflexible for range queries or partial matches.
- Not suitable for scenarios requiring ordered data retrieval.
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