Memory-efficient data structures in Redis - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is the main goal of memory-efficient data structures in Redis?

To store data using as little memory as possible while keeping fast access and operations.

intermediate

What is a Redis ziplist and when is it used?

A ziplist is a compact, memory-efficient list structure used for small lists or hashes to save space.

intermediate

How does Redis optimize small hashes to save memory?

Redis uses a special encoding called ziplist or listpack for small hashes to store fields and values compactly.

intermediate

What is a Redis intset and what type of data does it store?

An intset is a memory-efficient structure that stores small sets of integers in a compact sorted array.

advanced

Why does Redis switch from memory-efficient encodings to regular data structures as data grows?

Because memory-efficient encodings are slower for large data, Redis switches to faster but larger structures for better performance.

Which Redis data structure is most memory-efficient for small lists?

A Hash table

B Ziplist

C Intset

D Linked list

Ziplist is a compact structure used for small lists to save memory.

What type of data does a Redis intset store?

A Hashes

B Strings

C Integers

D Sorted sets

Intset stores small sets of integers in a compact way.

When does Redis switch from ziplist encoding to a regular hash table?

A When the hash is empty

B When the server restarts

C When the hash contains only integers

D When the hash grows beyond a size threshold

Redis switches to a regular hash table when the hash grows too large for ziplist efficiency.

Which of these is NOT a memory-efficient Redis data structure?

A Linked list

B Ziplist

C Intset

D Listpack

Linked list uses more memory compared to ziplist or intset.

Why are memory-efficient data structures important in Redis?

A To reduce memory usage and improve performance

B To increase network speed

C To make data permanent

D To encrypt data

Memory-efficient structures reduce memory use and keep Redis fast.

Explain how Redis uses memory-efficient data structures to store small hashes and lists.

Think about how Redis saves space for small collections.

Describe the trade-off Redis makes between memory efficiency and performance when choosing data structures.

Consider why Redis changes data structure types as data grows.

Practice

1. Which Redis data structure is best suited for storing many small key-value pairs efficiently in memory?

easy

A. List

B. Set

C. Hash

D. String

Solution

1. Step 1: Understand Redis data structures

   Hashes store multiple field-value pairs under one key, saving memory compared to many separate keys.

2. Step 2: Compare with other structures

   Lists and sets store collections but are less memory-efficient for many small pairs; strings store single values only.

3. Final Answer:

   Hash -> Option C

4. Quick Check:

   Hashes = memory-efficient key-value pairs [OK]

Hint: Use hashes for many small key-value pairs to save memory [OK]

Common Mistakes:

• Choosing List or Set for key-value pairs
• Thinking String can store multiple pairs
• Ignoring memory efficiency of Hashes

2. Which of the following is the correct Redis command to add a field-value pair to a hash named user:1?

easy

A. HSET user:1 name "Alice"

B. SADD user:1 name "Alice"

C. LPUSH user:1 name "Alice"

D. SET user:1 name "Alice"

Solution

1. Step 1: Identify the command for hashes

   HSET adds or updates a field in a hash key in Redis.

2. Step 2: Check other commands

   SADD is for sets, LPUSH for lists, SET for strings; none add fields to hashes.

3. Final Answer:

   HSET user:1 name "Alice" -> Option A

4. Quick Check:

   HSET = add field to hash [OK]

Hint: Use HSET to add fields to hashes in Redis [OK]

Common Mistakes:

• Using SADD or LPUSH for hashes
• Confusing SET with HSET
• Incorrect command syntax

3. Given the Redis commands:
HSET user:2 age 30
HSET user:2 city "NYC"
What will HGETALL user:2 return?

medium

A. ["age", "30", "city", "NYC"]

B. ["user:2", "age", "30", "city", "NYC"]

C. ["age", 30, "city", "NYC"]

D. ["age", "30", "city"]

Solution

1. Step 1: Understand HSET commands

   Two fields, 'age' and 'city', are set with values '30' and 'NYC' in hash 'user:2'.

2. Step 2: Check HGETALL output format

   HGETALL returns a flat list of field-value pairs as strings.

3. Final Answer:

   ["age", "30", "city", "NYC"] -> Option A

4. Quick Check:

   HGETALL returns field-value pairs list [OK]

Hint: HGETALL returns flat list of fields and values [OK]

Common Mistakes:

• Expecting key name in output
• Mixing data types (string vs integer)
• Missing value for a field

4. You run the command HSET user:3 name "Bob" but get an error. Which is the most likely cause?

medium

A. Redis does not support hashes with string fields

B. The key user:3 already holds a string value

C. HSET requires a numeric field value

D. The field name is reserved and cannot be used

Solution

1. Step 1: Understand Redis type errors

   If the key 'user:3' holds a string, trying to use HSET (hash command) causes a type error.

2. Step 2: Check other options

   Field names are not reserved, HSET accepts strings, and Redis supports string fields in hashes.

3. Final Answer:

   The key user:3 already holds a string value -> Option B

4. Quick Check:

   Type mismatch causes HSET error [OK]

Hint: Check key type before using hash commands [OK]

Common Mistakes:

• Assuming field names are restricted
• Thinking HSET needs numeric values
• Ignoring Redis data type rules

5. You want to store user preferences with many optional fields but minimize memory. Which Redis approach is best?

hard

A. Use a set with all field names as members

B. Use a list with all possible fields and empty strings for missing

C. Use separate string keys for each field

D. Use a hash with only fields that have values

Solution

1. Step 1: Consider memory efficiency

   Hashes store only existing fields, saving memory by omitting empty or missing fields.

2. Step 2: Evaluate other options

   Lists with empty strings waste memory; sets store unique members but not key-value pairs; separate keys increase overhead.

3. Final Answer:

   Use a hash with only fields that have values -> Option D

4. Quick Check:

   Hashes save memory by storing only present fields [OK]

Hint: Store only present fields in hashes to save memory [OK]

Common Mistakes:

• Using lists with empty placeholders
• Using sets for key-value data
• Creating many separate keys