Replication and Sharding Fundamentals in NoSQL Systems Quiz

Explore core concepts of replication and sharding in NoSQL systems with this easy quiz. Assess your understanding of data distribution strategies, consistency, and scaling in modern database architectures.

1. Concept of Data Sharding

   What is the primary purpose of sharding data in a NoSQL database?

   1. To distribute data across multiple servers for scalability
   2. To compress data for faster access
   3. To sort data alphabetically
   4. To encrypt data for security

   Explanation: Sharding divides data between multiple servers to allow systems to scale out and handle larger workloads. Compressing data is aimed at saving space, not distributing it. Encryption focuses on data security rather than distribution. Sorting data alphabetically is unrelated to sharding and does not address scalability or distribution.

2. Replication in NoSQL Systems

   Why do NoSQL databases use replication as a key feature?

   1. To decrease storage requirements
   2. To provide high availability and fault tolerance
   3. To remove duplicate data from records
   4. To improve query parsing speed

   Explanation: Replication ensures that data is copied across several nodes, providing high availability and helping the system recover from failures. Improving query parsing speed is related to optimization, not replication. Replication usually increases, rather than decreases, storage requirements. Removing duplicate data is called deduplication, which is different from replication.

3. Shard Key Selection

   Which of the following best describes an ideal shard key for a NoSQL database?

   1. A field containing randomly generated text
   2. A field with evenly distributed values across possible entries
   3. A static field that has the same value for all records
   4. A field that often remains empty

   Explanation: An ideal shard key evenly distributes data among shards to avoid 'hot spots' and enables balanced workloads. A static field leads to all data being stored on one shard, causing imbalance. Randomly generated text might not guarantee even distribution or query efficiency. Fields that are often empty do not provide a good basis for sharding since they may concentrate data.

4. Replication Factor

   If the replication factor is set to three in a NoSQL cluster, what does this mean?

   1. Each piece of data is stored on three different nodes
   2. Only three nodes in total exist in the cluster
   3. Three users can access the data at the same time
   4. Three different types of data are available

   Explanation: Replication factor refers to how many copies of each data item are kept in the system, improving resilience. The number of cluster nodes can be greater or fewer than the replication factor, but is not directly defined by it. It does not relate to data types or simultaneous user access.

5. Horizontal vs Vertical Scaling

   What is horizontal scaling in the context of NoSQL systems using sharding?

   1. Adding more machines to handle increased data volume
   2. Changing data format to JSON only
   3. Rewriting queries for better speed
   4. Increasing the CPU and memory on a single machine

   Explanation: Horizontal scaling involves adding more physical machines to a system, which sharding enables by dividing data. Increasing CPU and memory is vertical scaling, which may not address large data distribution needs. Rewriting queries and changing data formats are optimization and configuration tasks, not scaling strategies.

6. Replication Consistency Model

   In a replicated NoSQL system, which consistency model allows some replicas to be temporarily out of sync?

   1. Linear consistency
   2. Immediate consistency
   3. Eventual consistency
   4. Strict consistency

   Explanation: Eventual consistency means updates will propagate to all replicas, but some may not be immediately updated after a write. Strict, linear, and immediate consistency models require all nodes to see the same data at the same time, which is more difficult to achieve in distributed systems.

7. Benefit of Sharding

   How does sharding benefit a NoSQL system handling massive data growth?

   1. By copying every data record to all servers for safety
   2. By splitting data so different servers handle smaller portions
   3. By avoiding the need for backup mechanisms
   4. By converting data to binary for efficiency

   Explanation: Sharding enables data to be split so no single server becomes overwhelmed, making data management and scaling easier. Copying all data to all servers is replication, not sharding. Data conversion to binary is unrelated to scaling via sharding. Sharding does not eliminate the need for backups.

8. Write Operation in Replication

   In a typical replicated NoSQL setup, what happens if the primary node handling writes becomes unavailable?

   1. All write operations are permanently lost
   2. The database automatically deletes itself
   3. No data can be read until the primary returns
   4. A secondary node is promoted to handle new write operations

   Explanation: If the primary node fails, a secondary node is often promoted to maintain write availability and prevent downtime. Data is not permanently lost due to replication copies. Deleting the database is not an intended behavior. Read operations can generally continue on other replicas.

9. Challenge in Sharded Databases

   Which of the following is a potential challenge when using sharding in a NoSQL database?

   1. Uneven data distribution leading to unbalanced load
   2. Every query is processed instantly
   3. Faster disk drives are always required
   4. All data is encrypted automatically

   Explanation: A major challenge is ensuring data is spread evenly across shards; otherwise, some servers may become hotspots. Automatic encryption is a separate feature and not a challenge specific to sharding. Disk speed is not solely dictated by sharding. Instant query processing is not a guaranteed outcome.

10. Replication and Read Operations

    How does replication in NoSQL systems help improve read scalability?

    1. All read queries must go to a single node
    2. Read queries can be distributed among multiple replica nodes
    3. Only the primary node handles both reads and writes
    4. Replication disables queries from running in parallel

    Explanation: Replication allows the system to spread read queries among multiple nodes, reducing the load on any single node and improving performance. If all reads went to one node, this advantage would be lost. Limiting queries to the primary or blocking parallelism does not leverage the benefits of replication.