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.
Eladio Rocha
Test por Eladio Rocha, actualizado hace más de 1 año
Eladio Rocha
Creado por Eladio Rocha hace alrededor de 1 año
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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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