Embedding vs referencing in Redis - Interactive Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to store a user profile with embedded address data in Redis using a hash.

Redis

HSET user:1000 name "Alice" [1] "123 Main St" city "Springfield"

Drag options to blanks, or click blank then click option'

Astreet

Baddress

Clocation

Daddr

Attempts:

3 left

💡 Hint

Common Mistakes

Using a generic term like 'address' which might be confusing in a hash.

Using abbreviations that are unclear.

The key 'street' is used to embed the street address directly in the user hash.

2fill in blank

medium

Complete the code to reference an address stored separately by its ID in Redis.

Redis

HSET user:1001 name "Bob" address_id [1]

Drag options to blanks, or click blank then click option'

Aaddress:200

Baddr200

Caddress_200

Daddr:200

Attempts:

3 left

💡 Hint

Common Mistakes

Using keys without colon separators which is less common in Redis.

Using inconsistent naming conventions.

The field 'address_id' holds a reference key 'address:200' pointing to the separate address hash.

3fill in blank

hard

Fix the error in the code that tries to embed a list of phone numbers directly in a Redis hash.

Redis

HSET user:1002 name "Carol" phones [1]

Drag options to blanks, or click blank then click option'

A"[123-4567, 234-5678]"

B"123-4567;234-5678"

C"123-4567,234-5678"

D"123-4567 234-5678"

Attempts:

3 left

💡 Hint

Common Mistakes

Using JSON-like arrays which Redis hashes do not support.

Using semicolons or spaces which are less standard separators.

Redis hashes store strings, so phone numbers should be stored as a comma-separated string without brackets.

4fill in blank

hard

Fill in the blank to create a Redis command that retrieves the city from the referenced address hash.

Redis

HGET [1] city

Drag options to blanks, or click blank then click option'

Aaddress_300

Baddress:300

Cuser:city

Duser:300

Attempts:

3 left

💡 Hint

Common Mistakes

Using the user key instead of the address key.

Using underscores instead of colons in keys.

The command retrieves the 'city' field from the address hash with key 'address:300'.

5fill in blank

hard

Fill all three blanks to create a Redis Lua script snippet that fetches a user name, then fetches the city from the referenced address hash.

Redis

local userKey = [1]
local addressKey = redis.call('HGET', userKey, [2])
return redis.call('HGET', addressKey, [3])

Drag options to blanks, or click blank then click option'

A'user:400'

B'address_id'

C'city'

D'name'

Attempts:

3 left

💡 Hint

Common Mistakes

Using wrong field names like 'name' instead of 'address_id' for the reference.

Mixing up the order of commands.

The script first sets the user key, then gets the 'address_id' field from the user hash, and finally retrieves the 'city' from the address hash.

Practice

1. Which statement best describes embedding in Redis?

easy

A. Storing related data together in one key.

B. Storing data in separate keys linked by IDs.

C. Using multiple databases for related data.

D. Storing only references without actual data.

Solution

1. Step 1: Understand embedding concept

   Embedding means putting related data inside one Redis key, so all data is together.

2. Step 2: Compare with referencing

   Referencing stores data separately and links them by IDs, which is different from embedding.

3. Final Answer:

   Storing related data together in one key. -> Option A

4. Quick Check:

   Embedding = data together [OK]

Hint: Embedding means one key holds all related data [OK]

Common Mistakes:

• Confusing embedding with referencing
• Thinking embedding uses multiple keys
• Assuming embedding stores only IDs

2. Which Redis data structure is best suited for embedding small related data together?

easy

A. Sorted Set

B. String

C. List

D. Hash

Solution

1. Step 1: Identify data structure for embedding

   Hashes store multiple fields and values inside one key, ideal for embedding related small data.

2. Step 2: Compare other structures

   Strings hold single values, Lists and Sorted Sets are for ordered collections, less suited for embedding small related fields.

3. Final Answer:

   Hash -> Option D

4. Quick Check:

   Embedding small data = Hash [OK]

Hint: Use Hash for embedding small related fields [OK]

Common Mistakes:

• Choosing String for multiple fields
• Confusing List with Hash
• Using Sorted Set without score relevance

3. Given these Redis commands:

HSET user:100 name "Alice" age 30
HSET user:100:address city "NY" zip 10001

Which describes the data design?

medium

A. Referencing address data in a separate key

B. Embedding all user data in one key

C. Using a List to store user info

D. Storing user data as a String

Solution

1. Step 1: Analyze keys and data

   user:100 holds name and age, user:100:address holds address fields separately.

2. Step 2: Identify design pattern

   Address is stored in a separate key linked by user ID, which is referencing.

3. Final Answer:

   Referencing address data in a separate key -> Option A

4. Quick Check:

   Separate keys linked by ID = referencing [OK]

Hint: Separate keys with related IDs mean referencing [OK]

Common Mistakes:

• Thinking all data is embedded in one key
• Confusing List with Hash usage
• Assuming address is embedded inside user key

4. You want to store user profiles with embedded address data in Redis using hashes. Which command has an error?

medium

A. HSET user:200 name "Bob" age 25

B. HSET user:200:address city "LA" zip 90001

C. HSET user:200 name "Bob" city "LA" zip 90001

D. HSET user:200 name "Bob" age 25 city "LA" zip 90001

Solution

1. Step 1: Check embedding address in user hash

   Embedding means all fields in one key, so address fields city and zip should be in user:200 hash.

2. Step 2: Identify error in command C

   Command C uses a separate key user:200:address, storing address separately linked by ID. This is referencing, not embedding.

3. Final Answer:

   HSET user:200:address city "LA" zip 90001 -> Option B

4. Quick Check:

   Separate keys = referencing, not embedding [OK]

Hint: Embedding: all data in ONE key, no sub-keys [OK]

Common Mistakes:

• Missing value for a field
• Using separate keys when embedding
• Mixing field-value pairs incorrectly

5. You have a Redis database storing product info. You want to optimize for fast reads of product details including reviews. Which design is best?

hard

A. Embed product details and all reviews in one hash key per product.

B. Store all reviews in a single list key for all products.

C. Store product details in one hash and each review in separate keys linked by product ID.

D. Store product details as strings and reviews as sorted sets.

Solution

1. Step 1: Consider data size and access pattern

   Reviews can be many and large, embedding all in one key can cause large data and slow updates.

2. Step 2: Choose referencing for scalability

   Storing product details separately and reviews in linked keys allows efficient updates and reads without large keys.

3. Step 3: Evaluate other options

   Embedding all reviews in one hash risks large keys; storing all reviews in a single list key for all products mixes products; storing product details as strings and reviews as sorted sets don't fit review structure well.

4. Final Answer:

   Store product details in one hash and each review in separate keys linked by product ID. -> Option C

5. Quick Check:

   Large related data = referencing for performance [OK]

Hint: Large or many related items? Use referencing [OK]

Common Mistakes:

• Embedding large lists causing slow reads
• Mixing all reviews in one key
• Ignoring update frequency of reviews