Redis Questions

Vikas Vimal (Vikki)

Score: 🔥 175

Intermediate

Took 2 months

Databases

Redis

53%

Questions Attempted

15 / 15

Correct Answers

Incorrect Answers

Points Earned

🔥 8

Question 1

When a transaction is executed with EXEC, and a watched key has been modified, what is the expected return value?

An empty list ([]).
The string "OK".
The integer 1.
The integer 0.

Explanation:

If a watched key is modified before EXEC, indicating a potential conflict, Redis returns an empty list ([]) to signal that the transaction was not executed.

Question 2

What happens when you execute RENAME key1 key2 and key2 already exists?

An error is returned, and no changes are made
key1 is renamed to key2, overwriting the existing key2
key2 is renamed to a temporary name, and then key1 is renamed to key2
The command blocks until key2 is deleted

Explanation:

RENAME overwrites the destination key if it already exists. This behavior ensures the command remains atomic.

Question 3

What is a potential downside of using Redis as a primary database for your application?

Redis does not support complex queries or joins like traditional SQL databases.
Redis' in-memory nature means data persistence relies on disk or replication, introducing potential data loss risks.
Redis has limited data modeling capabilities compared to document-oriented or relational databases.
All of the above

Explanation:

While versatile, Redis has limitations as a primary database. It lacks robust querying, its in-memory nature poses persistence challenges, and its data modeling is less flexible than dedicated database systems.

Question 4

Which Redis feature allows you to persist data from memory to disk, providing some level of durability?

Virtual Memory
Persistence
Replication
Transactions

Explanation:

Redis offers different persistence options (like RDB and AOF) that write data to disk at intervals. This prevents complete data loss if the server restarts.

Question 5

When integrating Redis as a cache layer with a database, what strategy ensures data consistency between the cache and the database?

Write-through cache
Read-through cache
Cache-aside pattern
All of the above

Explanation:

Write-through, read-through, and cache-aside are all caching strategies that address data consistency between the cache and the primary database, albeit with different trade-offs.

Question 6

What is the key difference between traditional locking and optimistic locking in Redis?

Traditional locking blocks other clients, while optimistic locking allows concurrent access but detects conflicts.
Traditional locking is used for read operations, while optimistic locking is used for write operations.
Traditional locking is implemented with WATCH, while optimistic locking uses MULTI and EXEC.
Traditional locking is only available in Redis Cluster, while optimistic locking can be used in standalone mode.

Explanation:

Optimistic locking in Redis, using WATCH, allows concurrent operations but detects and prevents data corruption if multiple clients attempt to modify the same data. Traditional locking mechanisms block other clients, reducing concurrency.

Question 7

What is a common pattern for achieving message persistence in Redis Pub/Sub?

Using Redis Streams alongside Pub/Sub.
Configuring Redis to use a disk-based persistence mode.
Implementing a message queue system directly within Redis.
Relying on the inherent message durability of Pub/Sub.

Explanation:

While Pub/Sub itself doesn't guarantee persistence, combining it with Redis Streams allows for durable message storage and retrieval, addressing the limitation.

Question 8

How does the WATCH command help in implementing optimistic locking in Redis?

It prevents other clients from reading the watched keys.
It acquires an exclusive lock on the watched keys.
It monitors the watched keys for changes by other clients.
It sets a time-to-live (TTL) on the watched keys.

Explanation:

WATCH is used to monitor specific keys for modifications by other clients. If any watched key changes before the transaction's EXEC command, the entire transaction is aborted, preventing unintended data overwrites.

Question 9

You have a key named 'temp:data' with an expiration time set. How would you remove the expiration time and make the key persist indefinitely?

EXPIRE temp:data 0
TTL temp:data -1
PERSIST temp:data
There is no way to remove the expiration time once set

Explanation:

The PERSIST command is specifically used to remove the expiration time from a key, making it persistent.

Question 10

Which Redis command is used to retrieve geospatial points within a specified radius?

GEORADIUS
GEOSEARCH
GEOADD
GEODIST

Explanation:

The GEORADIUS command is used to query a Redis Geospatial Index and retrieve all points within a specified radius from a given center point.

Question 11

What is the purpose of using a tool like 'Redis-benchmark' in a CI/CD pipeline?

To visualize the real-time performance metrics of a Redis instance.
To configure and manage Redis clusters across multiple regions.
To simulate realistic workloads and assess Redis performance.
To automatically back up and restore Redis data at scheduled intervals.

Explanation:

Redis-benchmark is a tool for simulating Redis workloads. Integrating it into a CI/CD pipeline helps automate performance testing, ensuring that code changes don't degrade Redis performance.

Question 12

What is a key consideration when designing a system using Redis Pub/Sub for high message volume?

Implementing a mechanism to handle slow subscribers to prevent message backlog.
Ensuring that all messages are acknowledged by subscribers to prevent data loss.
Using persistent storage for all messages to facilitate auditing and replay.
Configuring Redis to prioritize Pub/Sub messages over other commands.

Explanation:

Slow subscribers can create bottlenecks in a Pub/Sub system. Strategies like pattern matching or separate channels for different message rates are crucial to address this.

Question 13

What is the primary advantage of using Redis HyperLogLogs over traditional sets for cardinality estimation?

HyperLogLogs provide exact cardinality counts.
HyperLogLogs consume significantly less memory for large cardinalities.
HyperLogLogs support range queries on the stored elements.
HyperLogLogs allow for storing duplicate elements.

Explanation:

HyperLogLogs offer an incredibly memory-efficient way to estimate the cardinality of a set. Unlike traditional sets, which store all unique elements, HyperLogLogs use a probabilistic algorithm that requires a fixed and small amount of memory, even for massive datasets.

Question 14

How does containerization with Docker benefit Redis deployments?

It automatically scales Redis instances based on real-time traffic.
It enables running multiple Redis instances on a single port.
It provides a consistent and isolated environment for Redis.
It eliminates the need for configuring Redis persistence.

Explanation:

Docker containers encapsulate Redis and its dependencies, ensuring a consistent environment across different deployment platforms. This isolation prevents conflicts and streamlines the deployment process.

Question 15

In a Redis transaction, what happens if one of the commands within the transaction fails?

The entire transaction is rolled back, and no commands are executed.
Only the failed command is skipped, and the rest of the transaction continues.
Redis throws an error and halts all operations.
The transaction remains pending until the failed command can be executed.

Explanation:

Redis transactions do not enforce atomicity in the traditional sense. If a command within a transaction fails, the others will still be executed.