Write-through pattern in Redis - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is the Write-through pattern in caching?

The Write-through pattern means that when data is written, it is saved both in the cache and the main database at the same time. This keeps cache and database always in sync.

beginner

Why use the Write-through pattern with Redis?

Using Write-through with Redis ensures data is always consistent between Redis cache and the database. It avoids stale data in cache and reduces cache misses.

intermediate

What happens if the database write fails in Write-through pattern?

If the database write fails, the cache write should also be rolled back or avoided to keep data consistent. Handling errors carefully is important.

intermediate

How does Write-through pattern affect write latency?

Write-through can increase write latency because data must be written to both cache and database before confirming success.

advanced

Compare Write-through and Write-back caching patterns.

Write-through writes data to cache and database immediately, ensuring consistency. Write-back writes only to cache first and updates database later, which can be faster but risks data loss.

In the Write-through pattern, when is data written to the database?

A Never, only cache is updated

B Only after the cache expires

C At the same time as writing to the cache

D Only when the cache is full

Write-through means data is written to both cache and database simultaneously to keep them in sync.

What is a main advantage of Write-through caching?

A Cache and database are always consistent

B Writes are very fast

C Database is updated only once a day

D Cache can have stale data

Write-through ensures cache and database stay consistent by writing to both immediately.

Which is a potential downside of Write-through pattern?

A Increased write latency

B Data loss risk

C Cache is never updated

D Database is not used

Writing to both cache and database can slow down write operations.

If a database write fails during Write-through, what should happen?

A Cache write should proceed anyway

B Cache write should be rolled back or avoided

C Ignore the failure and continue

D Delete the cache entirely

To keep data consistent, cache should not be updated if database write fails.

Which caching pattern writes data to cache first and database later?

A Read-through

B Write-through

C Cache-aside

D Write-back

Write-back caching delays database writes until later, unlike Write-through which writes immediately.

Explain the Write-through pattern and why it is useful in Redis caching.

Think about how data stays the same in both places.

Describe a scenario where Write-through caching might cause slower writes and how to handle failures.

Consider what happens if one write succeeds and the other fails.

Practice

1. What is the main purpose of the write-through pattern in Redis caching?

easy

A. To delete data from the cache when the database is updated

B. To update only the cache and delay database writes

C. To read data only from the cache without updating the database

D. To update both the cache and the database at the same time

Solution

1. Step 1: Understand write-through pattern basics

   The write-through pattern means writing data to the cache and database simultaneously to keep them in sync.

2. Step 2: Identify the correct behavior in Redis context

   In Redis, this pattern ensures cache is updated immediately when the database changes, avoiding stale data.

3. Final Answer:

   To update both the cache and the database at the same time -> Option D

4. Quick Check:

   Write-through = update cache + database [OK]

Hint: Write-through updates cache and DB together [OK]

Common Mistakes:

• Thinking write-through updates only cache
• Confusing write-through with write-back pattern
• Assuming cache is updated after database asynchronously

2. Which Redis command sequence correctly implements a write-through cache update when saving a user profile with key user:123 and value {"name":"Alice"}?

easy

A. DEL user:123 then SET user:123 '{"name":"Alice"}'

B. GET user:123 then SET user:123 '{"name":"Alice"}'

C. SET user:123 '{"name":"Alice"}' followed by DB update

D. SET user:123 '{"name":"Alice"}' only, no DB update

Solution

1. Step 1: Identify write-through steps

   Write-through requires writing to cache (Redis) and database together.

2. Step 2: Match Redis commands to write-through

   Using SET updates Redis cache; followed by DB update ensures both are in sync.

3. Final Answer:

   SET user:123 '{"name":"Alice"}' followed by DB update -> Option C

4. Quick Check:

   SET + DB update = write-through [OK]

Hint: SET cache then update DB for write-through [OK]

Common Mistakes:

• Only updating cache without DB
• Deleting cache before setting without DB update
• Getting cache before setting without DB write

3. Consider this pseudo-code using write-through pattern:

cache.SET('item:1', 'value1')
database.UPDATE('item:1', 'value1')
result = cache.GET('item:1')

What will result contain after execution?

medium

A. null

B. 'value1'

C. Old cached value

D. Error due to missing database read

Solution

1. Step 1: Analyze cache write

   The cache is set to 'value1' for key 'item:1' before database update.

2. Step 2: Analyze cache read

   Reading from cache immediately after setting returns the new value 'value1'.

3. Final Answer:

   'value1' -> Option B

4. Quick Check:

   Cache GET after SET returns new value [OK]

Hint: GET after SET returns updated cache value [OK]

Common Mistakes:

• Assuming cache GET returns null if DB updated
• Thinking old cached value remains after SET
• Expecting error without explicit DB read

4. You implemented write-through caching but notice stale data in Redis after database updates. Which mistake likely causes this?

medium

A. Updating database but forgetting to update Redis cache

B. Updating Redis cache but not the database

C. Using GET instead of SET to update cache

D. Deleting database entries without clearing cache

Solution

1. Step 1: Identify cause of stale cache

   If database updates but cache is not updated, cache holds old data causing staleness.

2. Step 2: Match mistake to write-through pattern

   Write-through requires cache update on every DB write; missing cache update breaks this.

3. Final Answer:

   Updating database but forgetting to update Redis cache -> Option A

4. Quick Check:

   Missing cache update causes stale data [OK]

Hint: Always update cache when DB changes [OK]

Common Mistakes:

• Updating cache only without DB
• Using GET to update cache instead of SET
• Not clearing cache on DB deletes

5. You want to implement a write-through cache in Redis for a product catalog. Which approach best ensures data consistency and minimal stale reads?

hard

A. On product update, update both Redis cache and database synchronously in the same operation

B. On product update, update the database first, then delete the Redis cache entry

C. On product update, update only the database and rely on cache expiration to refresh

D. On product update, write to Redis cache first, then update the database asynchronously

Solution

1. Step 1: Understand write-through consistency needs

   Write-through requires cache and database to be updated together to avoid stale reads.

2. Step 2: Evaluate options for consistency

   Updating both synchronously ensures cache always reflects latest DB state, minimizing stale data.

3. Final Answer:

   On product update, update both Redis cache and database synchronously in the same operation -> Option A

4. Quick Check:

   Synchronous cache + DB update = consistent write-through [OK]

Hint: Update cache and DB together synchronously [OK]

Common Mistakes:

• Updating cache before DB asynchronously causing race conditions
• Deleting cache instead of updating it
• Relying only on cache expiration for freshness