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40081826
Modern Scalable Databases
Descripción
Test your knowledge of modern scalable databases, including sharding, NoSQL systems like MongoDB and Cassandra, and the trade-offs between normalized and denormalized data.
Sin etiquetas
databases
nosql
sharding
distributed systems
mongodb
cassandra
dynamodb
database design
system design
otro
Test por
Eladio Rocha
, actualizado hace 18 días
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Creado por
Eladio Rocha
hace 19 días
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Resumen del Recurso
Pregunta 1
Pregunta
What is the primary purpose of a router in a scalable database design?
Respuesta
To perform joins between shards.
To route client requests to the appropriate shard.
To store backup configurations for shards.
To hash keys for partitioning data.
Pregunta 2
Pregunta
What is a "shard" in the context of databases?
Respuesta
A method of encrypting sensitive data.
A backup server in a replica set.
A horizontal partition of a database.
A tool for monitoring database traffic.
Pregunta 3
Pregunta
What is a major advantage of sharding in database systems?
Respuesta
It eliminates the need for backups.
It increases both scalability and redundancy.
It simplifies complex SQL queries.
It reduces the need for a router.
Pregunta 4
Pregunta
What is a replica set in MongoDB?
Respuesta
A set of configuration servers.
A collection of shards distributed across regions.
A primary server and its associated secondary servers for redundancy.
A group of shards that handle write-heavy traffic.
Pregunta 5
Pregunta
How does MongoDB ensure high availability when a primary server fails?
Respuesta
Traffic is rerouted to the config server.
Secondary servers automatically elect a new primary.
The router assigns new shards dynamically.
The primary server is rebooted automatically.
Pregunta 6
Pregunta
What does "eventual consistency" mean in the context of Cassandra?
Respuesta
Data is always immediately consistent across all nodes.
Data might take time to propagate across nodes, leading to temporary inconsistencies.
Data must be manually synchronized across nodes.
Consistency is not guaranteed due to system failures.
Pregunta 7
Pregunta
What is the "celebrity problem" in sharded databases?
Respuesta
High traffic on specific shards causes uneven load distribution.
Celebrities’ data is stored differently for security reasons.
All shards are overloaded with high read and write requests.
Certain shards fail to replicate data efficiently.
Pregunta 8
Pregunta
What is re-sharding, and why is it challenging?
Respuesta
Redistributing data when adding or removing shards, which requires fault-tolerant methods.
Creating backups for new shards added to the system.
Replicating data across all shards during traffic spikes.
Distributing write-heavy traffic across existing shards.
Pregunta 9
Pregunta
What is a key advantage of using a normalized database schema?
Respuesta
It minimizes storage space and simplifies updates.
It allows faster reads with fewer database hits.
It duplicates data for high performance.
It eliminates the need for joins between tables.
Pregunta 10
Pregunta
Why might denormalized data be preferred in a NoSQL database?
Respuesta
It reduces redundancy and improves update efficiency..
It allows for single-query retrieval of all necessary data.
It enforces strict schema rules.
It is easier to scale horizontally.
Pregunta 11
Pregunta
What should you prioritize when designing a horizontally scalable database?
Respuesta
Using as many joins as possible for efficiency.
Designing around simple key-value lookups to avoid joins.
Avoiding hash functions for data distribution.
Relying heavily on a single primary server for consistency.
Pregunta 12
Pregunta
Which database systems are examples of NoSQL?
Respuesta
PostgreSQL and MySQL.
MongoDB, Cassandra, and DynamoDB.
Oracle and SQLite.
Redis and HBase and SQLite
Pregunta 13
Pregunta
In what scenarios might you choose to use normalized data over denormalized data in a NoSQL database?
Respuesta
When updates are frequent and space efficiency is important.
When scaling horizontally is a top priority.
When high traffic requires fewer database hits.
When you need to perform complex joins efficiently.
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