Distributed Transaction Management Quiz

ACID is a set of properties that guarantee reliable processing of database transactions. Atomicity ensures that transactions are all-or-nothing, Consistency maintains database integrity, Isolation prevents concurrent transactions from affecting each other, and Durability guarantees that once a transaction is committed, it remains so even in the event of a failure.

In the two-phase commit protocol, the coordinator is responsible for managing the transaction process by collecting votes from all participating nodes. Based on these votes, the coordinator decides whether to commit the transaction or abort it, ensuring consistency and reliability across the distributed system.

Read Committed isolation level prevents dirty reads by ensuring that a transaction can only read committed data. However, it allows non-repeatable reads, which means that while one transaction is reading data, another can update it, preventing lost updates. This strikes a balance between consistency and performance in concurrent transactions.

Achieving atomicity in distributed systems is challenging due to network partitions and node failures, which can disrupt communication between nodes. This can lead to inconsistent states, as some nodes may not receive updates or may operate on stale data, making it difficult to ensure that all parts of the system reflect the same state at any given time.

In Raft consensus, the leader sends periodic heartbeat messages to maintain authority and ensure followers remain in sync. These messages, known as "append entries," serve to confirm the leader's status and can also include new log entries, preventing followers from timing out and initiating a new election.

A distributed deadlock occurs when two or more transactions are waiting for each other to release locks, forming a circular wait condition. In this scenario, the transactions are located on different nodes, making it a distributed system issue, as opposed to a local deadlock involving a single transaction or node.

The CAP theorem asserts that in a distributed system, it is impossible to achieve all three properties—Consistency, Availability, and Partition tolerance—simultaneously. Instead, a system can only guarantee two of these properties at any given time, highlighting the trade-offs that must be made in system design.

Optimistic concurrency control operates on the assumption that conflicts between transactions are infrequent, allowing multiple transactions to proceed without immediate locking. In contrast, pessimistic control proactively locks resources to prevent conflicts, which can lead to delays. This fundamental difference shapes how each approach manages resource access in distributed systems.

Write-ahead logging ensures durability in distributed transactions by recording changes to a log before they are applied to the database. This approach allows for recovery in case of failures, as the log can be used to replay or undo operations, thus maintaining data integrity and consistency across distributed systems.

Eventual consistency ensures that, while updates may not be immediately visible to all nodes, they will eventually be propagated throughout the system. This model allows for temporary inconsistencies, with the understanding that all nodes will converge to the same state over time, ensuring that all updates are eventually reflected across the system.

A phantom read occurs when a transaction retrieves a set of rows based on a query, but subsequent transactions insert new rows that match the query criteria before the first transaction completes. This results in the first transaction seeing different results if it re-executes the same query, highlighting issues with isolation levels in databases.

Raft is favored for its simplicity and ease of understanding compared to other consensus algorithms. It effectively manages leader election and log replication, making it suitable for distributed systems. Its design prioritizes clarity, which helps developers implement and maintain systems using this algorithm, contributing to its widespread adoption in modern applications.