Hash indexes in DBMS Theory - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is a hash index in a database?

A hash index is a type of database index that uses a hash function to map search keys to specific locations, allowing fast data retrieval based on exact matches.

beginner

How does a hash function help in hash indexing?

A hash function converts a search key into a fixed-size value (hash code) that points to the location where the data is stored, enabling quick access without scanning the entire dataset.

beginner

What type of queries are hash indexes best suited for?

Hash indexes are best for queries that look for exact matches, such as finding a record with a specific key value, but they are not efficient for range queries.

intermediate

What is a limitation of hash indexes compared to B-tree indexes?

Hash indexes do not support range queries or ordered traversal of data, while B-tree indexes allow both exact match and range queries efficiently.

intermediate

What happens if two keys produce the same hash value in a hash index?

This is called a collision. Hash indexes handle collisions using methods like chaining (linking entries) or open addressing (finding another slot), ensuring data can still be retrieved correctly.

What is the main advantage of using a hash index?

A Supports full-text search

B Efficient range queries

C Ordered data traversal

D Fast exact match lookups

Hash indexes provide very fast lookups for exact key matches but do not support range queries or ordered traversal.

Which of the following is a common problem in hash indexes?

A Slow insertions

B Data duplication

C Collisions

D Lack of indexing

Collisions occur when two keys hash to the same location; hash indexes use special methods to handle collisions.

Hash indexes are NOT suitable for which type of query?

A Exact match queries

B Range queries

C Single record retrieval

D Equality searches

Hash indexes do not support range queries efficiently because they do not maintain order.

Which data structure is commonly used as an alternative to hash indexes for range queries?

A B-tree

B Stack

C Linked list

D Queue

B-tree indexes maintain sorted order and support efficient range queries.

What does a hash function do in a hash index?

A Maps keys to storage locations

B Sorts the data

C Compresses data

D Encrypts data

A hash function converts keys into hash codes that point to where data is stored for quick access.

Explain how a hash index works and when it is most useful.

Think about how a key is transformed and used to find data quickly.

Compare hash indexes with B-tree indexes in terms of query types they support.

Consider what kinds of searches each index type handles best.

Practice

1. What is the primary purpose of a hash index in a database?

easy

A. To store data in sorted order

B. To speed up range queries

C. To compress data for storage

D. To speed up exact key lookups

Solution

1. Step 1: Understand the function of hash indexes

   Hash indexes convert keys into hash values to quickly find exact matches.

2. Step 2: Compare with other index types

   Unlike B-tree indexes, hash indexes do not support range queries or sorting.

3. Final Answer:

   To speed up exact key lookups -> Option D

4. Quick Check:

   Hash index = exact key lookup speed [OK]

Hint: Hash indexes are for exact matches, not ranges [OK]

Common Mistakes:

• Thinking hash indexes support range queries
• Confusing hash indexes with sorted indexes
• Assuming hash indexes compress data

2. Which of the following is the correct syntax to create a hash index on a column named user_id in SQL (assuming the database supports hash indexes)?

easy

A. CREATE INDEX idx_user ON users USING HASH (user_id);

B. CREATE HASH INDEX idx_user ON users (user_id);

C. CREATE INDEX idx_user ON users (user_id) HASH;

D. CREATE INDEX idx_user HASH ON users (user_id);

Solution

1. Step 1: Recall standard SQL syntax for hash indexes

   The correct syntax uses CREATE INDEX with USING HASH to specify the index type.

2. Step 2: Analyze each option

   CREATE INDEX idx_user ON users USING HASH (user_id); correctly places USING HASH after the index name and before the column list.

3. Final Answer:

   CREATE INDEX idx_user ON users USING HASH (user_id); -> Option A

4. Quick Check:

   Syntax for hash index = CREATE INDEX ... USING HASH ... [OK]

Hint: Use 'USING HASH' after index name to specify hash index [OK]

Common Mistakes:

• Placing HASH keyword incorrectly
• Omitting USING keyword
• Using non-standard syntax unsupported by SQL

3. Consider the following SQL query on a table with a hash index on email column:

SELECT * FROM users WHERE email = '[e-mail]';

What is the expected behavior of the database when using the hash index?

medium

A. It performs a range scan on the email column

B. It scans the entire table because hash indexes do not support equality

C. It performs a fast exact match lookup using the hash index

D. It returns an error because hash indexes cannot be used in WHERE clauses

Solution

1. Step 1: Understand hash index usage in equality queries

   Hash indexes are designed to quickly find rows matching an exact key value.

2. Step 2: Analyze the query condition

   The WHERE clause uses equality on the indexed column, so the hash index is used efficiently.

3. Final Answer:

   It performs a fast exact match lookup using the hash index -> Option C

4. Quick Check:

   Equality query + hash index = fast lookup [OK]

Hint: Hash indexes speed up exact equality queries [OK]

Common Mistakes:

• Thinking hash indexes do full table scans
• Confusing hash index with range scan
• Assuming hash indexes cause errors in queries

4. A developer created a hash index on the phone_number column but notices that queries with LIKE '%1234' are slow. What is the most likely reason?

medium

A. The hash index is corrupted and needs rebuilding

B. Hash indexes do not support pattern matching or partial searches

C. The database does not support hash indexes on numeric columns

D. The query optimizer ignores all indexes for LIKE queries

Solution

1. Step 1: Understand hash index limitations

   Hash indexes only support exact key lookups, not pattern matching or partial searches.

2. Step 2: Analyze the query pattern

   The LIKE '%1234' pattern searches for suffix matches, which hash indexes cannot optimize.

3. Final Answer:

   Hash indexes do not support pattern matching or partial searches -> Option B

4. Quick Check:

   Hash index ≠ pattern matching support [OK]

Hint: Hash indexes only speed exact matches, not LIKE patterns [OK]

Common Mistakes:

• Assuming hash indexes speed up all LIKE queries
• Blaming index corruption without evidence
• Thinking numeric columns can't have hash indexes

5. You want to optimize a database table for fast lookups on a customer_id column, but also need to efficiently query ranges of order_date. Which indexing strategy is best?

hard

A. Create a hash index on customer_id and a B-tree index on order_date

B. Create hash indexes on both customer_id and order_date

C. Create a B-tree index on customer_id and no index on order_date

D. Create no indexes and rely on full table scans

Solution

1. Step 1: Match index types to query needs

   Hash indexes are best for exact key lookups like on customer_id.

2. Step 2: Use B-tree indexes for range queries

   B-tree indexes efficiently support range queries, so use it on order_date.

3. Final Answer:

   Create a hash index on customer_id and a B-tree index on order_date -> Option A

4. Quick Check:

   Hash for exact, B-tree for range queries [OK]

Hint: Use hash for exact keys, B-tree for ranges [OK]

Common Mistakes:

• Using hash index for range queries
• Not indexing columns needed for fast queries
• Relying on full scans for large tables