Explore key concepts of high availability, fault tolerance, replication, and failure recovery in CouchDB Qu. This quiz helps users understand fundamental mechanisms ensuring data resilience and service continuity in distributed database environments.
Which feature allows CouchDB Qu to maintain up-to-date copies of data across multiple nodes for high availability?
Explanation: Replication keeps data synchronized across nodes, ensuring continued availability and resilience if a node fails. Migration refers to moving data permanently, not keeping multiple copies. Sharding spreads data into segments for scaling but does not guarantee redundancy. Shuffling is unrelated to database data protection. Replication is the concept that directly supports high availability.
In a distributed CouchDB Qu setup, what does the term 'quorum' refer to in the context of fault-tolerant writing?
Explanation: A quorum is the minimum number of nodes that must agree or respond to an operation, such as a write, to ensure consistency and fault tolerance. Backups involve entire copies, not consensus for operations. A list of deleted records is merely a changelog, while the fastest node is irrelevant for consensus. Only the quorum ensures reliable distributed operations.
If one node in a CouchDB Qu cluster becomes unavailable, how does high availability ensure client access to data?
Explanation: Due to replication, other nodes hold copies of the data and can seamlessly serve requests, maintaining availability. The system is designed so that one node's failure does not stop overall operation. The database does not need to halt, and clients are generally able to both read and write, assuming quorum is met. Losing all data on a failed node does not happen if proper replication is enabled.
When data changes occur on different nodes at the same time, what mechanism helps resolve these conflicts in CouchDB Qu?
Explanation: Multi-version concurrency control allows the database to store multiple versions of documents and resolve conflicts based on rules or timestamps. Indexing manages search and lookup speed but not conflicts. Caching temporarily stores frequently accessed data, and partitioning divides data for scaling, not conflict handling. Conflict resolution relies on handling multiple versions safely.
What occurs when a previously failed CouchDB Qu node rejoins a cluster that continued running during its absence?
Explanation: On rejoins, the node automatically pulls any data changes it missed using the built-in replication mechanism, restoring itself to current state. It's not excluded permanently from the cluster and there's no need for manual cluster restarts. Nodes do not need to erase data; instead, they update to match the current data set.
Which consistency model is commonly used in distributed CouchDB Qu environments to balance availability and network partitions?
Explanation: Eventual consistency means that all replicas will become consistent over time, allowing high availability despite temporary discrepancies during network partitions. Strict and immediate consistency demand all nodes agree instantly, which reduces availability. Fixed consistency is not a standard term. Eventual consistency supports distributed, fault-tolerant scenarios effectively.
How does load balancing contribute to high availability in a CouchDB Qu cluster with multiple nodes?
Explanation: Load balancing directs client requests across available nodes, preventing overloads and improving uptime. Sending all traffic to a single node negates availability benefits. Only using standby nodes during failure doesn't leverage full resources. Increasing memory alone does not inherently balance or distribute requests.
Which setting helps ensure that write operations are not considered successful in CouchDB Qu until written to stable storage on multiple nodes?
Explanation: A write quorum requires confirmation from a designated number of nodes, ensuring that writes survive hardware failures. Read preference refers to which nodes are prioritized for reading, not writing. Auto-indexing relates to searchability, and cache refresh doesn't guarantee long-term data durability. Only write quorums enforce data protection at write time.
During a network partition in a distributed CouchDB Qu setup, what characteristic allows the system to continue accepting reads and writes in isolated partitions?
Explanation: Partition tolerance means the system can operate despite split clusters unable to communicate, retaining functionality on both sides. Synchronous locking may halt progress during partition. Rollback logging tracks unsuccessful transactions but does not maintain availability. Static scheduling assigns workloads but doesn’t address partition scenarios.
Which practice best prevents data loss in case multiple nodes in a CouchDB Qu cluster fail at the same time?
Explanation: Keeping several data copies in different locations reduces the risk of losing all copies due to local failures or disasters. Client timeouts control wait periods but don't protect data. A single backup drive is insufficient redundancy. Restricting writes to one node centralized risk and does not prevent data loss from multiple failures.